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Identification of Hospitalists
A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.
There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]
The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]
Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.
METHODS
Approach to Identifying Hospitalists
In April 2014, CMS publicly released Medicare Provider Utilization and Payment data from all 880,000 providers who billed Medicare Part B in 2012. The dataset included services charged for 2012 Medicare Part B fee‐for‐service claims. The data omitted claims billed by a unique National Provider Identifier (NPI) for fewer than 10 Medicare beneficiaries. CMS assigned a specialty designation to each provider in the pay data based on the Medicare specialty billing code listed most frequently on his or her claims.
We explored the number of hospitalists in the 2012 Medicare pay data using specialty designation in combination with patterns of billing data. We first grouped physicians with specialty designations of internal medicine and family practice (IM/FP), the most common board certifications for hospitalists. We then selected 4 Healthcare Common Procedure Coding System (HCPCS) code clusters commonly associated with hospitalist practice: acute inpatient (HCPCS codes 9922199223, 9923199233, and 9923899239), observation (9921899220, 9922499226, and 99217), observation/emnpatient same day (9923499236), and critical care (9929199292). We included observation services codes given the significant role hospitalists play in their use[7, 8] and CMS incorporation of observation services for a threshold to identify and exempt hospital‐based providers in meaningful use.[9]
Analysis of Billing Thresholds and Other Codes Billed by Hospitalists
We examined the numbers of hospitalists who would be identified using a 50%, 60%, 70%, 80%, or 90% threshold, and compared the level of change in the size of the group with each change in decile.
We then analyzed the services billed by hospitalists who billed our threshold codes between 60% and 70% of the time. We looked at all codes billed with a frequency of greater than 0.1%, grouping clusters of similar services to identify patterns of clinical activity performed by these physicians.
RESULTS
The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.
Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.
| Threshold (%) | Unique NPIs | % of IM/FP Physicians | % of All Physicians |
|---|---|---|---|
| |||
| 90 | 28,473 | 16.8 | 4.3 |
| 80 | 30,866 | 18.2 | 4.6 |
| 70 | 32,834 | 19.4 | 4.9 |
| 60 | 35,116 | 20.7 | 5.3 |
| 50 | 37,646 | 22.2 | 5.7 |
We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).
| Clinical Service Cluster | HCPCS Codes Included | % |
|---|---|---|
| ||
| Threshold codes | 99217, 99219, 99220, 99221, 99222, 99223, 99231, 99232, 99233, 99238, 99239, 99291 | 64.5 |
| Office visit (new and established) | 99203, 99204, 99205, 99211, 99212, 99213, 99214, 99215 | 15.3 |
| SNF care (initial and subsequent) | 99305, 99306, 99307, 99308, 99309, 99310, 99315 | 7.1 |
| ECG‐related codes | 93000, 93010, 93042 | 2.5 |
| Routine venipuncture | 36415 | 1.0 |
| Other codes with f>0.1%* | 25 codes | 5.1 |
| Codes with f<0.1% | 439 codes | 4.5 |
| Total | 495 codes | 100.0 |
DISCUSSION
Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]
A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.
A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.
In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.
Disclosures
The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs. The authors report no conflicts of interest.
A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.
There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]
The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]
Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.
METHODS
Approach to Identifying Hospitalists
In April 2014, CMS publicly released Medicare Provider Utilization and Payment data from all 880,000 providers who billed Medicare Part B in 2012. The dataset included services charged for 2012 Medicare Part B fee‐for‐service claims. The data omitted claims billed by a unique National Provider Identifier (NPI) for fewer than 10 Medicare beneficiaries. CMS assigned a specialty designation to each provider in the pay data based on the Medicare specialty billing code listed most frequently on his or her claims.
We explored the number of hospitalists in the 2012 Medicare pay data using specialty designation in combination with patterns of billing data. We first grouped physicians with specialty designations of internal medicine and family practice (IM/FP), the most common board certifications for hospitalists. We then selected 4 Healthcare Common Procedure Coding System (HCPCS) code clusters commonly associated with hospitalist practice: acute inpatient (HCPCS codes 9922199223, 9923199233, and 9923899239), observation (9921899220, 9922499226, and 99217), observation/emnpatient same day (9923499236), and critical care (9929199292). We included observation services codes given the significant role hospitalists play in their use[7, 8] and CMS incorporation of observation services for a threshold to identify and exempt hospital‐based providers in meaningful use.[9]
Analysis of Billing Thresholds and Other Codes Billed by Hospitalists
We examined the numbers of hospitalists who would be identified using a 50%, 60%, 70%, 80%, or 90% threshold, and compared the level of change in the size of the group with each change in decile.
We then analyzed the services billed by hospitalists who billed our threshold codes between 60% and 70% of the time. We looked at all codes billed with a frequency of greater than 0.1%, grouping clusters of similar services to identify patterns of clinical activity performed by these physicians.
RESULTS
The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.
Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.
| Threshold (%) | Unique NPIs | % of IM/FP Physicians | % of All Physicians |
|---|---|---|---|
| |||
| 90 | 28,473 | 16.8 | 4.3 |
| 80 | 30,866 | 18.2 | 4.6 |
| 70 | 32,834 | 19.4 | 4.9 |
| 60 | 35,116 | 20.7 | 5.3 |
| 50 | 37,646 | 22.2 | 5.7 |
We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).
| Clinical Service Cluster | HCPCS Codes Included | % |
|---|---|---|
| ||
| Threshold codes | 99217, 99219, 99220, 99221, 99222, 99223, 99231, 99232, 99233, 99238, 99239, 99291 | 64.5 |
| Office visit (new and established) | 99203, 99204, 99205, 99211, 99212, 99213, 99214, 99215 | 15.3 |
| SNF care (initial and subsequent) | 99305, 99306, 99307, 99308, 99309, 99310, 99315 | 7.1 |
| ECG‐related codes | 93000, 93010, 93042 | 2.5 |
| Routine venipuncture | 36415 | 1.0 |
| Other codes with f>0.1%* | 25 codes | 5.1 |
| Codes with f<0.1% | 439 codes | 4.5 |
| Total | 495 codes | 100.0 |
DISCUSSION
Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]
A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.
A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.
In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.
Disclosures
The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs. The authors report no conflicts of interest.
A seminal 1996 New England Journal of Medicine article introduced the term hospitalist to describe the emerging trend of primary care physicians practicing in inpatient hospital settings.[1] Although physicians had practice patterns akin to hospitalists prior to the introduction of the term,[2] the field continues to grow and formalize as a unique specialty in medicine.
There is currently no board certification or specialty billing code associated with hospitalists. In 2009, the American Board of Internal Medicine and American Board of Family Medicine introduced a Focused Practice in Hospital Medicine optional recertification pathway.[3] However, absent a unique identifier, it remains difficult to identify the number of hospitalists practicing today. Issues with identification notwithstanding, published data consistently suggest that the number of hospitalists has grown dramatically over the last 2 decades.[4, 5, 6]
The Centers for Medicare and Medicaid Services (CMS), along with other payers, classify hospitalists based on their board certificationmost commonly internal medicine or family practice. Other approaches for more precise assessment utilized billing data or hospital designation. Saint et al. identified hospital‐based providers practicing in Washington State in 1994 using variable thresholds of billing for inpatient services.[2] In 2011, Welch et al. identified 25,787 hospitalists nationwide, using a 90% threshold of billing inpatient services in Medicare data.[6] That same year, an American Hospital Association survey identified 34,411 hospitalists based on self‐reporting.[4]
Building on the work of previous researchers, we applied an updated threshold of inpatient services in publicly available 2012 Medicare Provider Utilization and Payment Data to identify a range of hospitalists practicing in the United States. We also examine the codes billed by providers identified in different decile billing thresholds to assess the validity of using lower thresholds to identify hospitalists.
METHODS
Approach to Identifying Hospitalists
In April 2014, CMS publicly released Medicare Provider Utilization and Payment data from all 880,000 providers who billed Medicare Part B in 2012. The dataset included services charged for 2012 Medicare Part B fee‐for‐service claims. The data omitted claims billed by a unique National Provider Identifier (NPI) for fewer than 10 Medicare beneficiaries. CMS assigned a specialty designation to each provider in the pay data based on the Medicare specialty billing code listed most frequently on his or her claims.
We explored the number of hospitalists in the 2012 Medicare pay data using specialty designation in combination with patterns of billing data. We first grouped physicians with specialty designations of internal medicine and family practice (IM/FP), the most common board certifications for hospitalists. We then selected 4 Healthcare Common Procedure Coding System (HCPCS) code clusters commonly associated with hospitalist practice: acute inpatient (HCPCS codes 9922199223, 9923199233, and 9923899239), observation (9921899220, 9922499226, and 99217), observation/emnpatient same day (9923499236), and critical care (9929199292). We included observation services codes given the significant role hospitalists play in their use[7, 8] and CMS incorporation of observation services for a threshold to identify and exempt hospital‐based providers in meaningful use.[9]
Analysis of Billing Thresholds and Other Codes Billed by Hospitalists
We examined the numbers of hospitalists who would be identified using a 50%, 60%, 70%, 80%, or 90% threshold, and compared the level of change in the size of the group with each change in decile.
We then analyzed the services billed by hospitalists who billed our threshold codes between 60% and 70% of the time. We looked at all codes billed with a frequency of greater than 0.1%, grouping clusters of similar services to identify patterns of clinical activity performed by these physicians.
RESULTS
The 2012 Medicare pay data included 664,253 physicians with unique NPIs. Of these, 169,317 had IM/FP specialty designations, whereas just under half (46.25%) of those physicians billed any of the inpatient HCPCS codes associated with our threshold.
Table 1 describes the range of number of hospitalists identified by varying the threshold of inpatient services. A total of 28,473 providers bill the threshold‐associated inpatient codes almost exclusively, whereas each descending decile increases in size by an average of 7.29%.
| Threshold (%) | Unique NPIs | % of IM/FP Physicians | % of All Physicians |
|---|---|---|---|
| |||
| 90 | 28,473 | 16.8 | 4.3 |
| 80 | 30,866 | 18.2 | 4.6 |
| 70 | 32,834 | 19.4 | 4.9 |
| 60 | 35,116 | 20.7 | 5.3 |
| 50 | 37,646 | 22.2 | 5.7 |
We also analyzed billing patterns of a subset of physicians who billed our threshold codes between 60% and 70% of the time to better characterize the remainder of clinical work they perform. This group included 2282 physicians and only 56 unique HCPCS codes with frequencies greater than 0.1%. After clustering related codes, we identified 4 common code groups that account for the majority of the remaining billing beyond inpatient threshold codes (Table 2).
| Clinical Service Cluster | HCPCS Codes Included | % |
|---|---|---|
| ||
| Threshold codes | 99217, 99219, 99220, 99221, 99222, 99223, 99231, 99232, 99233, 99238, 99239, 99291 | 64.5 |
| Office visit (new and established) | 99203, 99204, 99205, 99211, 99212, 99213, 99214, 99215 | 15.3 |
| SNF care (initial and subsequent) | 99305, 99306, 99307, 99308, 99309, 99310, 99315 | 7.1 |
| ECG‐related codes | 93000, 93010, 93042 | 2.5 |
| Routine venipuncture | 36415 | 1.0 |
| Other codes with f>0.1%* | 25 codes | 5.1 |
| Codes with f<0.1% | 439 codes | 4.5 |
| Total | 495 codes | 100.0 |
DISCUSSION
Hospitalists make up approximately 5% of the practicing physicians nationwide, performing a critical role caring for hospitalized patients. Saint et al. defined a pure hospitalist as a physician who meets a 90% threshold of inpatient services.[2] This approach has been replicated in subsequent studies that used a 90% threshold to identify hospitalists.[5, 6] Our results with the same threshold reveal more than 28,000 hospitalists with nearly uniform practice patterns, a 10% growth in the number of hospitalists from the Welch et al. analysis in 2011.[6]
A threshold is not a perfect tool for identifying groups of practicing physicians, as it creates an arbitrary cutoff within a dataset. Undoubtedly our analysis could include providers who would not consider themselves hospitalists, or alternatively, appear to have a hospital‐based practice when they do not. Our results suggest that a 90% threshold may identify a majority of practicing hospitalists, but excludes providers who likely identify as hospitalists albeit with divergent practice and billing patterns.
A lower threshold may be more inclusive of the current realities of hospitalist practice, accounting for the myriad other services provided during, immediately prior to, or following a hospitalization. With hospitalists commonly practicing in diverse facility settings, rotating through rehabilitation or nursing home facilities, discharge clinics, and preoperative medicine practices, the continued use of a 90% threshold appears to exclude a sizable number of practicing hospitalists.
In the absence of a formal identifier, developing identification methodologies that account for the diversity of hospitalist practice is crucial. As physician payment transitions to value‐based reimbursement, systems must have the ability to account for and allocate the most efficient mix of providers for their patient populations. Because provider alignment and coordination are structural features of these programs, these systems‐based changes in effect require accurate identification of hospitalists, yet currently lack the tools to do so.
Disclosures
The research reported here was supported by the Department of Veterans Affairs, Veterans Health Administration. Investigator salary support is provided through the South Texas Veterans Health Care System. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs. The authors report no conflicts of interest.
Measuring Patient Experiences
The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.
Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.
METHODS
Study Design
We performed a retrospective cohort analysis at the University of Chicago Medical Center between July 2007 and June 2013. Data were acquired as part of the Hospitalist Project, an ongoing study that is used to evaluate the impact of hospitalists, and now serves as infrastructure to continue research related to hospital care at University of Chicago.[14] Patients were cared for by either the general medicine teaching service or the nonteaching hospitalist service. General medicine teaching services were composed of an attending physician who rotates for 2 weeks at a time, a second‐ or third‐year medicine resident, 1 to 2 medicine interns, and 1 to 2 medical students.[15] The attending physician assigned to the patient's hospitalization was the attending listed on the first day of hospitalization, regardless of the length of hospitalization. Nonteaching hospitalist services consisted of a single hospitalist who worked 7‐day shifts, and were assisted by a nurse practitioner/physician's assistant (NPA). The majority of attendings on the hospitalist service were less than 5 years out of residency. Both services admitted 7 days a week, with patients initially admitted to the general medicine teaching service until resident caps were met, after which all subsequent admissions were admitted to the hospitalist service. In addition, the hospitalist service is also responsible for specific patient subpopulations, such as lung and renal transplants, and oncologic patients who have previously established care with our institution.
Data Collection
During a 30‐day posthospitalization follow‐up questionnaire, patients were surveyed regarding their confidence in their ability to identify and understand the roles of their physician(s) and their perceptions of the overall coordination of care and their overall care, using a 5‐point Likert scale (1 = poor understanding to 5 = excellent understanding). Questions related to satisfaction with care and coordination were derived from the Picker‐Commonwealth Survey, a previously validated survey meant to evaluate patient‐centered care.[16] Patients were also asked to report their race, level of education, comorbid diseases, and whether they had any prior hospitalizations within 1 year. Chart review was performed to obtain patient age, gender, and hospital length of stay (LOS), and calculated Charlson Comorbidity Index (CCI).[17] Patients with missing data or responses to survey questions were excluded from final analysis. The University of Chicago Institutional Review Board approved the study protocol, and all patients provided written consented prior to participation.
Data Analysis
After initial analysis noted that outcomes were skewed, the decision was made to dichotomize the data and use logistic rather than linear regression models. Patient responses to the follow‐up phone questionnaire were dichotomized to reflect the top 2 categories (excellent and very good). Pearson 2 analysis was used to assess for any differences in demographic characteristics, disease severity, and measures of patient experience between the 2 services. To assess if service type was associated with differences in our 4 measures of patient experience, we created a 3‐level mixed‐effects logistic regression using a logit function while controlling for age, gender, race, CCI, LOS, previous hospitalizations within 1 year, level of education, and academic year. These models studied the longitudinal association between teaching service and the 4 outcome measures, while also controlling for the cluster effect of time nested within individual patients who were clustered within physicians. The model included random intercepts at both the patient and physician level and also included a random effect of service (teaching vs nonteaching) at the patient level. A Hausman test was used to determine if these random‐effects models improved fit over a fixed‐effects model, and the intraclass correlations were compared using likelihood ratio tests to determine the appropriateness of a 3‐level versus 2‐level model. Data management and 2 analyses were performed using Stata version 13.0 (StataCorp, College Station, TX), and mixed‐effects regression models were done in SuperMix (Scientific Software International, Skokie, IL).
RESULTS
In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.
| Variable | General Medicine Teaching | Nonteaching Hospitalist | P Value |
|---|---|---|---|
| |||
| Total (n) | 4,591 | 1,811 | <0.001 |
| Attending classification, hospitalist, n (%) | 1,147 (25) | 1,811 (100) | |
| Response rate, % | 61 | 57 | <0.01 |
| Age, y, mean SD | 56.2 19.4 | 57.1 16.1 | <0.01 |
| Gender, n (%) | <0.01 | ||
| Male | 1,796 (39) | 805 (44) | |
| Female | 2,795 (61) | 1,004 (56) | |
| Race, n (%) | <0.01 | ||
| African American | 3,440 (75) | 1,092 (63) | |
| White | 900 (20) | 571 (32) | |
| Asian/Pacific | 38 (1) | 17 (1) | |
| Other | 20 (1) | 10 (1) | |
| Unknown | 134 (3) | 52 (3) | |
| Charlson Comorbidity Index, n (%) | <0.001 | ||
| 0 | 1,635 (36) | 532 (29) | |
| 12 | 1,590 (35) | 675 (37) | |
| 39 | 1,366 (30) | 602 (33) | |
| Self‐reported comorbidities | |||
| Anemia/sickle cell disease | 1,201 (26) | 408 (23) | 0.003 |
| Asthma/COPD | 1,251 (28) | 432 (24) | 0.006 |
| Cancer* | 300 (7) | 371 (20) | <0.001 |
| Depression | 1,035 (23) | 411 (23) | 0.887 |
| Diabetes | 1,381 (30) | 584 (32) | 0.087 |
| Gastrointestinal | 1,140 (25) | 485 (27) | 0.104 |
| Cardiac | 1,336 (29) | 520 (29) | 0.770 |
| Hypertension | 2,566 (56) | 1,042 (58) | 0.222 |
| HIV/AIDS | 151 (3) | 40 (2) | 0.022 |
| Kidney disease | 828 (18) | 459 (25) | <0.001 |
| Liver disease | 313 (7) | 417 (23) | <0.001 |
| Stroke | 543 (12) | 201 (11) | 0.417 |
| Education level | 0.066 | ||
| High school | 2,248 (49) | 832 (46) | |
| Junior college/college | 1,878 (41) | 781 (43) | |
| Postgraduate | 388 (8) | 173 (10) | |
| Don't know | 77 (2) | 23 (1) | |
| Academic year, n (%) | <0.001 | ||
| July 2007 June 2008 | 938 (20) | 90 (5) | |
| July 2008 June 2009 | 702 (15) | 148 (8) | |
| July 2009 June 2010 | 576(13) | 85 (5) | |
| July 2010 June 2011 | 602 (13) | 138 (8) | |
| July 2011 June 2012 | 769 (17) | 574 (32) | |
| July 2012 June 2013 | 1,004 (22) | 774 (43) | |
| Length of stay, d, mean SD | 4.8 7.3 | 5.5 6.4 | <0.01 |
| Prior hospitalization (within 1 year), yes, n (%) | 2,379 (52) | 1,039 (58) | <0.01 |
Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).
From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).
A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.
| Domains in Patient Experience* | Odds Ratio (95% CI) | P Value |
|---|---|---|
| ||
| How would you rate your ability to identify the physicians and trainees on your general medicine team during the hospitalization? | ||
| Model 1 | 0.89 (0.611.11) | 0.32 |
| Model 2 | 0.98 (0.671.22) | 0.86 |
| How would you rate your understanding of the roles of the physicians and trainees on your general medicine team? | ||
| Model 1 | 1.09 (0.941.23) | 0.25 |
| Model 2 | 1.19 (0.981.36) | 0.08 |
| How would you rate the overall coordination and teamwork among the doctors and nurses who care for you during your hospital stay? | ||
| Model 1 | 0.71 (0.421.89) | 0.18 |
| Model 2 | 0.82 (0.651.20) | 0.23 |
| Overall, how would you rate the care you received at the hospital? | ||
| Model 1 | 1.33 (1.151.47) | 0.001 |
| Model 2 | 1.17 (1.011.31) | 0.04 |
DISCUSSION
This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.
The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.
Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.
Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]
Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.
Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.
Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .
All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.
Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.
CONCLUSION
In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.
Disclosures
Financial support for this work was provided by the Robert Wood Johnson Investigator Program (RWJF Grant ID 63910 PI Meltzer), a Midcareer Career Development Award from the National Institute of Aging (1 K24 AG031326‐01, PI Meltzer), and a Clinical and Translational Science Award (NIH/NCATS 2UL1TR000430‐08, PI Solway, Meltzer Core Leader). The authors report no conflicts of interest.
- Hospital Consumer Assessment of Healthcare Providers and Systems. HCAHPS fact sheet. CAHPS hospital survey August 2013. Available at: http://www.hcahpsonline.org/files/August_2013_HCAHPS_Fact_Sheet3.pdf. Accessed February 2, 2015.
- , , , et al. Transitions of Care Consensus policy statement: American College of Physicians, Society of General Internal Medicine, Society of Hospital Medicine, American Geriatrics Society, American College Of Emergency Physicians, and Society for Academic Emergency Medicine. J Hosp Med. 2009;4(6):364–370.
- Accreditation Council for Graduate Medical Education. Common program requirements. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/ProgramRequirements/CPRs2013.pdf. Accessed January 15, 2015.
- , , . Increasing a patient's ability to identify his or her attending physician using a patient room display. Arch Intern Med. 2010;170(12):1084–1085.
- , , , , , . Ability of hospitalized patients to identify their in‐hospital physicians. Arch Intern Med. 2009;169(2):199–201.
- , , , et al. Hospitalized patients' understanding of their plan of care. Mayo Clin Proc. 2010;85(1):47–52.
- , , , et al. Patient‐physician communication at hospital discharge and patients' understanding of the postdischarge treatment plan. Arch Intern Med. 1997;157(9):1026–1030.
- , , , et al. Improving inpatients' identification of their doctors: use of FACE cards. Jt Comm J Qual Patient Saf. 2009;35(12):613–619.
- , , , , , . The impact of facecards on patients' knowledge, satisfaction, trust, and agreement with hospital physicians: a pilot study. J Hosp Med. 2014;9(3):137–141.
- , , . Restructuring an inpatient resident service to improve outcomes for residents, students, and patients. Acad Med. 2011;86(12):1500–1507.
- , , . Residency training in the modern era: the pipe dream of less time to learn more, care better, and be more professional. Arch Intern Med. 2005;165(22):2561–2562.
- , , , , . Managing discontinuity in academic medical centers: strategies for a safe and effective resident sign‐out. J Hosp Med. 2006;1(4):257–266.
- , , , . Hospitalist staffing and patient satisfaction in the national Medicare population. J Hosp Med. 2013;8(3):126–131.
- , , , et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
- , , , , , . The Effects of on‐duty napping on intern sleep time and fatigue. Ann Intern Med. 2006;144(11):792–798.
- , , , et al. Patients evaluate their hospital care: a national survey. Health Aff (Millwood). 1991;10(4):254–267.
- , , , . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.
- Agency for Healthcare Research and Quality. Welcome to HCUPnet. Available at: http://hcupnet.ahrq.gov/HCUPnet.jsp?Id=F70FC59C286BADCB371(4):293–295.
- , , , et al. In the wake of the 2003 and 2011 duty hours regulations, how do internal medicine interns spend their time? J Gen Intern Med. 2013;28(8):1042–1047.
- , , , , , . The composition of intern work while on call. J Gen Intern Med. 2012;27(11):1432–1437.
- , , , et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649–655.
- , , , et al. The impact of hospitalist discontinuity on hospital cost, readmissions, and patient satisfaction. J Gen Intern Med. 2014;29(7):1004–1008.
- , , , , . Hospitalist time usage and cyclicality: opportunities to improve efficiency. J Hosp Med. 2010;5(6):329–334.
- , , , et al. Where did the day go?—a time‐motion study of hospitalists. J Hosp Med. 2010;5(6):323–328.
- , , . How hospitalists spend their time: insights on efficiency and safety. J Hosp Med. 2006;1(2):88–93.
- , , . Patient satisfaction associated with correct identification of physician's photographs. Mayo Clin Proc. 2001;76(6):604–608.
- , , , . Comparing patient outcomes of academician‐preceptors, hospitalist‐preceptors, and hospitalists on internal medicine services in an academic medical center. J Gen Intern Med. 2014;29(12):1672–1678.
- , , , . Comparison of processes and outcomes of pneumonia care between hospitalists and community‐based primary care physicians. Mayo Clin Proc. 2002;77(10):1053–1058.
- , , , , , . Outcomes of care by hospitalists, general internists, and family physicians. N Engl J Med. 2007;357(25):2589–2600.
- . A systematic review of outcomes and quality measures in adult patients cared for by hospitalists vs nonhospitalists. Mayo Clin Proc. 2009;84(3):248–254.
- , . Do hospitalist physicians improve the quality of inpatient care delivery? A systematic review of process, efficiency and outcome measures. BMC Med. 2011;9(1):58.
- , . Patients' experiences of everyday life after lung transplantation. J Clin Nurs. 2009;18(24):3472–3479.
- , , , et al. Optimal design features for surveying low‐income populations. J Health Care Poor Underserved. 2005;16(4):677–690.
The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.
Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.
METHODS
Study Design
We performed a retrospective cohort analysis at the University of Chicago Medical Center between July 2007 and June 2013. Data were acquired as part of the Hospitalist Project, an ongoing study that is used to evaluate the impact of hospitalists, and now serves as infrastructure to continue research related to hospital care at University of Chicago.[14] Patients were cared for by either the general medicine teaching service or the nonteaching hospitalist service. General medicine teaching services were composed of an attending physician who rotates for 2 weeks at a time, a second‐ or third‐year medicine resident, 1 to 2 medicine interns, and 1 to 2 medical students.[15] The attending physician assigned to the patient's hospitalization was the attending listed on the first day of hospitalization, regardless of the length of hospitalization. Nonteaching hospitalist services consisted of a single hospitalist who worked 7‐day shifts, and were assisted by a nurse practitioner/physician's assistant (NPA). The majority of attendings on the hospitalist service were less than 5 years out of residency. Both services admitted 7 days a week, with patients initially admitted to the general medicine teaching service until resident caps were met, after which all subsequent admissions were admitted to the hospitalist service. In addition, the hospitalist service is also responsible for specific patient subpopulations, such as lung and renal transplants, and oncologic patients who have previously established care with our institution.
Data Collection
During a 30‐day posthospitalization follow‐up questionnaire, patients were surveyed regarding their confidence in their ability to identify and understand the roles of their physician(s) and their perceptions of the overall coordination of care and their overall care, using a 5‐point Likert scale (1 = poor understanding to 5 = excellent understanding). Questions related to satisfaction with care and coordination were derived from the Picker‐Commonwealth Survey, a previously validated survey meant to evaluate patient‐centered care.[16] Patients were also asked to report their race, level of education, comorbid diseases, and whether they had any prior hospitalizations within 1 year. Chart review was performed to obtain patient age, gender, and hospital length of stay (LOS), and calculated Charlson Comorbidity Index (CCI).[17] Patients with missing data or responses to survey questions were excluded from final analysis. The University of Chicago Institutional Review Board approved the study protocol, and all patients provided written consented prior to participation.
Data Analysis
After initial analysis noted that outcomes were skewed, the decision was made to dichotomize the data and use logistic rather than linear regression models. Patient responses to the follow‐up phone questionnaire were dichotomized to reflect the top 2 categories (excellent and very good). Pearson 2 analysis was used to assess for any differences in demographic characteristics, disease severity, and measures of patient experience between the 2 services. To assess if service type was associated with differences in our 4 measures of patient experience, we created a 3‐level mixed‐effects logistic regression using a logit function while controlling for age, gender, race, CCI, LOS, previous hospitalizations within 1 year, level of education, and academic year. These models studied the longitudinal association between teaching service and the 4 outcome measures, while also controlling for the cluster effect of time nested within individual patients who were clustered within physicians. The model included random intercepts at both the patient and physician level and also included a random effect of service (teaching vs nonteaching) at the patient level. A Hausman test was used to determine if these random‐effects models improved fit over a fixed‐effects model, and the intraclass correlations were compared using likelihood ratio tests to determine the appropriateness of a 3‐level versus 2‐level model. Data management and 2 analyses were performed using Stata version 13.0 (StataCorp, College Station, TX), and mixed‐effects regression models were done in SuperMix (Scientific Software International, Skokie, IL).
RESULTS
In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.
| Variable | General Medicine Teaching | Nonteaching Hospitalist | P Value |
|---|---|---|---|
| |||
| Total (n) | 4,591 | 1,811 | <0.001 |
| Attending classification, hospitalist, n (%) | 1,147 (25) | 1,811 (100) | |
| Response rate, % | 61 | 57 | <0.01 |
| Age, y, mean SD | 56.2 19.4 | 57.1 16.1 | <0.01 |
| Gender, n (%) | <0.01 | ||
| Male | 1,796 (39) | 805 (44) | |
| Female | 2,795 (61) | 1,004 (56) | |
| Race, n (%) | <0.01 | ||
| African American | 3,440 (75) | 1,092 (63) | |
| White | 900 (20) | 571 (32) | |
| Asian/Pacific | 38 (1) | 17 (1) | |
| Other | 20 (1) | 10 (1) | |
| Unknown | 134 (3) | 52 (3) | |
| Charlson Comorbidity Index, n (%) | <0.001 | ||
| 0 | 1,635 (36) | 532 (29) | |
| 12 | 1,590 (35) | 675 (37) | |
| 39 | 1,366 (30) | 602 (33) | |
| Self‐reported comorbidities | |||
| Anemia/sickle cell disease | 1,201 (26) | 408 (23) | 0.003 |
| Asthma/COPD | 1,251 (28) | 432 (24) | 0.006 |
| Cancer* | 300 (7) | 371 (20) | <0.001 |
| Depression | 1,035 (23) | 411 (23) | 0.887 |
| Diabetes | 1,381 (30) | 584 (32) | 0.087 |
| Gastrointestinal | 1,140 (25) | 485 (27) | 0.104 |
| Cardiac | 1,336 (29) | 520 (29) | 0.770 |
| Hypertension | 2,566 (56) | 1,042 (58) | 0.222 |
| HIV/AIDS | 151 (3) | 40 (2) | 0.022 |
| Kidney disease | 828 (18) | 459 (25) | <0.001 |
| Liver disease | 313 (7) | 417 (23) | <0.001 |
| Stroke | 543 (12) | 201 (11) | 0.417 |
| Education level | 0.066 | ||
| High school | 2,248 (49) | 832 (46) | |
| Junior college/college | 1,878 (41) | 781 (43) | |
| Postgraduate | 388 (8) | 173 (10) | |
| Don't know | 77 (2) | 23 (1) | |
| Academic year, n (%) | <0.001 | ||
| July 2007 June 2008 | 938 (20) | 90 (5) | |
| July 2008 June 2009 | 702 (15) | 148 (8) | |
| July 2009 June 2010 | 576(13) | 85 (5) | |
| July 2010 June 2011 | 602 (13) | 138 (8) | |
| July 2011 June 2012 | 769 (17) | 574 (32) | |
| July 2012 June 2013 | 1,004 (22) | 774 (43) | |
| Length of stay, d, mean SD | 4.8 7.3 | 5.5 6.4 | <0.01 |
| Prior hospitalization (within 1 year), yes, n (%) | 2,379 (52) | 1,039 (58) | <0.01 |
Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).
From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).
A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.
| Domains in Patient Experience* | Odds Ratio (95% CI) | P Value |
|---|---|---|
| ||
| How would you rate your ability to identify the physicians and trainees on your general medicine team during the hospitalization? | ||
| Model 1 | 0.89 (0.611.11) | 0.32 |
| Model 2 | 0.98 (0.671.22) | 0.86 |
| How would you rate your understanding of the roles of the physicians and trainees on your general medicine team? | ||
| Model 1 | 1.09 (0.941.23) | 0.25 |
| Model 2 | 1.19 (0.981.36) | 0.08 |
| How would you rate the overall coordination and teamwork among the doctors and nurses who care for you during your hospital stay? | ||
| Model 1 | 0.71 (0.421.89) | 0.18 |
| Model 2 | 0.82 (0.651.20) | 0.23 |
| Overall, how would you rate the care you received at the hospital? | ||
| Model 1 | 1.33 (1.151.47) | 0.001 |
| Model 2 | 1.17 (1.011.31) | 0.04 |
DISCUSSION
This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.
The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.
Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.
Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]
Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.
Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.
Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .
All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.
Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.
CONCLUSION
In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.
Disclosures
Financial support for this work was provided by the Robert Wood Johnson Investigator Program (RWJF Grant ID 63910 PI Meltzer), a Midcareer Career Development Award from the National Institute of Aging (1 K24 AG031326‐01, PI Meltzer), and a Clinical and Translational Science Award (NIH/NCATS 2UL1TR000430‐08, PI Solway, Meltzer Core Leader). The authors report no conflicts of interest.
The hospitalized patient experience has become an area of increased focus for hospitals given the recent coupling of patient satisfaction to reimbursement rates for Medicare patients.[1] Although patient experiences are multifactorial, 1 component is the relationship that hospitalized patients develop with their inpatient physicians. In recognition of the importance of this relationship, several organizations including the Society of Hospital Medicine, Society of General Internal Medicine, American College of Physicians, the American College of Emergency Physicians, and the Accreditation Council for Graduate Medical Education have recommended that patients know and understand who is guiding their care at all times during their hospitalization.[2, 3] Unfortunately, previous studies have shown that hospitalized patients often lack the ability to identify[4, 5] and understand their course of care.[6, 7] This may be due to numerous clinical factors including lack of a prior relationship, rapid pace of clinical care, and the frequent transitions of care found in both hospitalists and general medicine teaching services.[5, 8, 9] Regardless of the cause, one could hypothesize that patients who are unable to identify or understand the role of their physician may be less informed about their hospitalization, which may lead to further confusion, dissatisfaction, and ultimately a poor experience.
Given the proliferation of nonteaching hospitalist services in teaching hospitals, it is important to understand if patient experiences differ between general medicine teaching and hospitalist services. Several reasons could explain why patient experiences may vary on these services. For example, patients on a hospitalist service will likely interact with a single physician caretaker, which may give a feeling of more personalized care. In contrast, patients on general medicine teaching services are cared for by larger teams of residents under the supervision of an attending physician. Residents are also subjected to duty‐hour restrictions, clinic responsibilities, and other educational requirements that may impede the continuity of care for hospitalized patients.[10, 11, 12] Although 1 study has shown that hospitalist‐intensive hospitals perform better on patient satisfaction measures,[13] no study to date has compared patient‐reported experiences on general medicine teaching and nonteaching hospitalist services. This study aimed to evaluate the hospitalized patient experience on both teaching and nonteaching hospitalist services by assessing several patient‐reported measures of their experience, namely their confidence in their ability to identify their physician(s), understand their roles, and their rating of both the coordination and overall care.
METHODS
Study Design
We performed a retrospective cohort analysis at the University of Chicago Medical Center between July 2007 and June 2013. Data were acquired as part of the Hospitalist Project, an ongoing study that is used to evaluate the impact of hospitalists, and now serves as infrastructure to continue research related to hospital care at University of Chicago.[14] Patients were cared for by either the general medicine teaching service or the nonteaching hospitalist service. General medicine teaching services were composed of an attending physician who rotates for 2 weeks at a time, a second‐ or third‐year medicine resident, 1 to 2 medicine interns, and 1 to 2 medical students.[15] The attending physician assigned to the patient's hospitalization was the attending listed on the first day of hospitalization, regardless of the length of hospitalization. Nonteaching hospitalist services consisted of a single hospitalist who worked 7‐day shifts, and were assisted by a nurse practitioner/physician's assistant (NPA). The majority of attendings on the hospitalist service were less than 5 years out of residency. Both services admitted 7 days a week, with patients initially admitted to the general medicine teaching service until resident caps were met, after which all subsequent admissions were admitted to the hospitalist service. In addition, the hospitalist service is also responsible for specific patient subpopulations, such as lung and renal transplants, and oncologic patients who have previously established care with our institution.
Data Collection
During a 30‐day posthospitalization follow‐up questionnaire, patients were surveyed regarding their confidence in their ability to identify and understand the roles of their physician(s) and their perceptions of the overall coordination of care and their overall care, using a 5‐point Likert scale (1 = poor understanding to 5 = excellent understanding). Questions related to satisfaction with care and coordination were derived from the Picker‐Commonwealth Survey, a previously validated survey meant to evaluate patient‐centered care.[16] Patients were also asked to report their race, level of education, comorbid diseases, and whether they had any prior hospitalizations within 1 year. Chart review was performed to obtain patient age, gender, and hospital length of stay (LOS), and calculated Charlson Comorbidity Index (CCI).[17] Patients with missing data or responses to survey questions were excluded from final analysis. The University of Chicago Institutional Review Board approved the study protocol, and all patients provided written consented prior to participation.
Data Analysis
After initial analysis noted that outcomes were skewed, the decision was made to dichotomize the data and use logistic rather than linear regression models. Patient responses to the follow‐up phone questionnaire were dichotomized to reflect the top 2 categories (excellent and very good). Pearson 2 analysis was used to assess for any differences in demographic characteristics, disease severity, and measures of patient experience between the 2 services. To assess if service type was associated with differences in our 4 measures of patient experience, we created a 3‐level mixed‐effects logistic regression using a logit function while controlling for age, gender, race, CCI, LOS, previous hospitalizations within 1 year, level of education, and academic year. These models studied the longitudinal association between teaching service and the 4 outcome measures, while also controlling for the cluster effect of time nested within individual patients who were clustered within physicians. The model included random intercepts at both the patient and physician level and also included a random effect of service (teaching vs nonteaching) at the patient level. A Hausman test was used to determine if these random‐effects models improved fit over a fixed‐effects model, and the intraclass correlations were compared using likelihood ratio tests to determine the appropriateness of a 3‐level versus 2‐level model. Data management and 2 analyses were performed using Stata version 13.0 (StataCorp, College Station, TX), and mixed‐effects regression models were done in SuperMix (Scientific Software International, Skokie, IL).
RESULTS
In total, 14,855 patients were enrolled during their hospitalization with 57% and 61% completing the 30‐day follow‐up survey on the hospitalist and general medicine teaching service, respectively. In total, 4131 (69%) and 4322 (48%) of the hospitalist and general medicine services, respectively, either did not answer all survey questions, or were missing basic demographic data, and thus were excluded. Data from 4591 patients on the general medicine teaching (52% of those enrolled at hospitalization) and 1811 on the hospitalist service (31% of those enrolled at hospitalization) were used for final analysis (Figure 1). Respondents were predominantly female (61% and 56%), African American (75% and 63%), with a mean age of 56.2 (19.4) and 57.1 (16.1) years, for the general medicine teaching and hospitalist services, respectively. A majority of patients (71% and 66%) had a CCI of 0 to 3 on both services. There were differences in self‐reported comorbidities between the 2 groups, with hospitalist services having a higher prevalence of cancer (20% vs 7%), renal disease (25% vs 18%), and liver disease (23% vs 7%). Patients on the hospitalist service had a longer mean LOS (5.5 vs 4.8 days), a greater percentage of a hospitalization within 1 year (58% vs 52%), and a larger proportion who were admitted in 2011 to 2013 compared to 2007 to 2010 (75% vs 39%), when compared to the general medicine teaching services. Median LOS and interquartile ranges were similar between both groups. Although most baseline demographics were statistically different between the 2 groups (Table 1), these differences were likely clinically insignificant. Compared to those who responded to the follow‐up survey, nonresponders were more likely to be African American (73% and 64%, P < 0.001) and female (60% and 56%, P < 0.01). The nonresponders were more likely to be hospitalized in the past 1 year (62% and 53%, P < 0.001) and have a lower CCI (CCI 03 [75% and 80%, P < 0.001]) compared to responders. Demographics between responders and nonresponders were also statistically different from one another.
| Variable | General Medicine Teaching | Nonteaching Hospitalist | P Value |
|---|---|---|---|
| |||
| Total (n) | 4,591 | 1,811 | <0.001 |
| Attending classification, hospitalist, n (%) | 1,147 (25) | 1,811 (100) | |
| Response rate, % | 61 | 57 | <0.01 |
| Age, y, mean SD | 56.2 19.4 | 57.1 16.1 | <0.01 |
| Gender, n (%) | <0.01 | ||
| Male | 1,796 (39) | 805 (44) | |
| Female | 2,795 (61) | 1,004 (56) | |
| Race, n (%) | <0.01 | ||
| African American | 3,440 (75) | 1,092 (63) | |
| White | 900 (20) | 571 (32) | |
| Asian/Pacific | 38 (1) | 17 (1) | |
| Other | 20 (1) | 10 (1) | |
| Unknown | 134 (3) | 52 (3) | |
| Charlson Comorbidity Index, n (%) | <0.001 | ||
| 0 | 1,635 (36) | 532 (29) | |
| 12 | 1,590 (35) | 675 (37) | |
| 39 | 1,366 (30) | 602 (33) | |
| Self‐reported comorbidities | |||
| Anemia/sickle cell disease | 1,201 (26) | 408 (23) | 0.003 |
| Asthma/COPD | 1,251 (28) | 432 (24) | 0.006 |
| Cancer* | 300 (7) | 371 (20) | <0.001 |
| Depression | 1,035 (23) | 411 (23) | 0.887 |
| Diabetes | 1,381 (30) | 584 (32) | 0.087 |
| Gastrointestinal | 1,140 (25) | 485 (27) | 0.104 |
| Cardiac | 1,336 (29) | 520 (29) | 0.770 |
| Hypertension | 2,566 (56) | 1,042 (58) | 0.222 |
| HIV/AIDS | 151 (3) | 40 (2) | 0.022 |
| Kidney disease | 828 (18) | 459 (25) | <0.001 |
| Liver disease | 313 (7) | 417 (23) | <0.001 |
| Stroke | 543 (12) | 201 (11) | 0.417 |
| Education level | 0.066 | ||
| High school | 2,248 (49) | 832 (46) | |
| Junior college/college | 1,878 (41) | 781 (43) | |
| Postgraduate | 388 (8) | 173 (10) | |
| Don't know | 77 (2) | 23 (1) | |
| Academic year, n (%) | <0.001 | ||
| July 2007 June 2008 | 938 (20) | 90 (5) | |
| July 2008 June 2009 | 702 (15) | 148 (8) | |
| July 2009 June 2010 | 576(13) | 85 (5) | |
| July 2010 June 2011 | 602 (13) | 138 (8) | |
| July 2011 June 2012 | 769 (17) | 574 (32) | |
| July 2012 June 2013 | 1,004 (22) | 774 (43) | |
| Length of stay, d, mean SD | 4.8 7.3 | 5.5 6.4 | <0.01 |
| Prior hospitalization (within 1 year), yes, n (%) | 2,379 (52) | 1,039 (58) | <0.01 |
Unadjusted results revealed that patients on the hospitalist service were more confident in their abilities to identify their physician(s) (50% vs 45%, P < 0.001), perceived greater ability in understanding the role of their physician(s) (54% vs 50%, P < 0.001), and reported greater satisfaction with coordination and teamwork (68% vs 64%, P = 0.006) and with overall care (73% vs 67%, P < 0.001) (Figure 2).
From the mixed‐effects regression models it was discovered that admission to the hospitalist service was associated with a higher odds ratio (OR) of reporting overall care as excellent or very good (OR: 1.33; 95% confidence interval [CI]: 1.15‐1.47). There was no difference between services in patients' ability to identify their physician(s) (OR: 0.89; 95% CI: 0.61‐1.11), in patients reporting a better understanding of the role of their physician(s) (OR: 1.09; 95% CI: 0.94‐1.23), or in their rating of overall coordination and teamwork (OR: 0.71; 95% CI: 0.42‐1.89).
A subgroup analysis was performed on the 25% of hospitalist attendings in the general medicine teaching service comparing this cohort to the hospitalist services, and it was found that patients perceived better overall care on the hospitalist service (OR: 1.17; 95% CI: 1.01‐ 1.31) than on the general medicine service (Table 2). All other domains in the subgroup analysis were not statistically significant. Finally, an ordinal logistic regression was performed for each of these outcomes, but it did not show any major differences compared to the logistic regression of dichotomous outcomes.
| Domains in Patient Experience* | Odds Ratio (95% CI) | P Value |
|---|---|---|
| ||
| How would you rate your ability to identify the physicians and trainees on your general medicine team during the hospitalization? | ||
| Model 1 | 0.89 (0.611.11) | 0.32 |
| Model 2 | 0.98 (0.671.22) | 0.86 |
| How would you rate your understanding of the roles of the physicians and trainees on your general medicine team? | ||
| Model 1 | 1.09 (0.941.23) | 0.25 |
| Model 2 | 1.19 (0.981.36) | 0.08 |
| How would you rate the overall coordination and teamwork among the doctors and nurses who care for you during your hospital stay? | ||
| Model 1 | 0.71 (0.421.89) | 0.18 |
| Model 2 | 0.82 (0.651.20) | 0.23 |
| Overall, how would you rate the care you received at the hospital? | ||
| Model 1 | 1.33 (1.151.47) | 0.001 |
| Model 2 | 1.17 (1.011.31) | 0.04 |
DISCUSSION
This study is the first to directly compare measures of patient experience on hospitalist and general medicine teaching services in a large, multiyear comparison across multiple domains. In adjusted analysis, we found that patients on nonteaching hospitalist services rated their overall care better than those on general medicine teaching services, whereas no differences in patients' ability to identify their physician(s), understand their role in their care, or rating of coordination of care were found. Although the magnitude of the differences in rating of overall care may appear small, it remains noteworthy because of the recent focus on patient experience at the reimbursement level, where small differences in performance can lead to large changes in payment. Because of the observational design of this study, it is important to consider mechanisms that could account for our findings.
The first are the structural differences between the 2 services. Our subgroup analysis comparing patients rating of overall care on a general medicine service with a hospitalist attending to a pure hospitalist cohort found a significant difference between the groups, indicating that the structural differences between the 2 groups may be a significant contributor to patient satisfaction ratings. Under the care of a hospitalist service, a patient would only interact with a single physician on a daily basis, possibly leading to a more meaningful relationship and improved communication between patient and provider. Alternatively, while on a general medicine teaching service, patients would likely interact with multiple physicians, as a result making their confidence in their ability to identify and perception at understanding physicians' roles more challenging.[18] This dilemma is further compounded by duty hour restrictions, which have subsequently led to increased fragmentation in housestaff scheduling. The patient experience on the general medicine teaching service may be further complicated by recent data that show residents spend a minority of time in direct patient care,[19, 20] which could additionally contribute to patients' inability to understand who their physicians are and to the decreased satisfaction with their care. This combination of structural complexity, duty hour reform, and reduced direct patient interaction would likely decrease the chance a patient will interact with the same resident on a consistent basis,[5, 21] thus making the ability to truly understand who their caretakers are, and the role they play, more difficult.
Another contributing factor could be the use of NPAs on our hospitalist service. Given that these providers often see the patient on a more continual basis, hospitalized patients' exposure to a single, continuous caretaker may be a factor in our findings.[22] Furthermore, with studies showing that hospitalists also spend a small fraction of their day in direct patient care,[23, 24, 25] the use of NPAs may allow our hospitalists to spend greater amounts of time with their patients, thus improving patients' rating of their overall care and influencing their perceived ability to understand their physician's role.
Although there was no difference between general medicine teaching and hospitalist services with respect to patient understanding of their roles, our data suggest that both groups would benefit from interventions to target this area. Focused attempts at improving patient's ability to identify and explain the roles of their inpatient physician(s) have been performed. For example, previous studies have attempted to improve a patient's ability to identify their physician through physician facecards[8, 9] or the use of other simple interventions (ie, bedside whiteboards).[4, 26] Results from such interventions are mixed, as they have demonstrated the capacity to improve patients' ability to identify who their physician is, whereas few have shown any appreciable improvement in patient satisfaction.[26]
Although our findings suggest that structural differences in team composition may be a possible explanation, it is also important to consider how the quality of care a patient receives affects their experience. For instance, hospitalists have been shown to produce moderate improvements in patient‐centered outcomes such as 30‐day readmission[27] and hospital length of stay[14, 28, 29, 30, 31] when compared to other care providers, which in turn could be reflected in the patient's perception of their overall care. In a large national study of acute care hospitals using the Hospital Consumer Assessment of Healthcare Providers and Systems survey, Chen and colleagues found that for most measures of patient satisfaction, hospitals with greater use of hospitalist care were associated with better patient‐centered care.[13] These outcomes were in part driven by patient‐centered domains such as discharge planning, pain control, and medication management. It is possible that patients are sensitive to the improved outcomes that are associated with hospitalist services, and reflect this in their measures of patient satisfaction.
Last, because this is an observational study and not a randomized trial, it is possible that the clinical differences in the patients cared for by these services could have led to our findings. Although the clinical significance of the differences in patient demographics were small, patients seen on the hospitalist service were more likely to be older white males, with a slightly longer LOS, greater comorbidities, and more hospitalizations in the previous year than those seen on the general medicine teaching service. Additionally, our hospitalist service frequently cares for highly specific subpopulations (ie, liver and renal transplant patients, and oncology patients), which could have influenced our results. For example, transplant patients who may be very grateful for their second chance, are preferentially admitted to the hospitalist service, which could have biased our results in favor of hospitalists.[32] Unfortunately, we were unable to control for all such factors.
Although we hope that multivariable analysis can adjust for many of these differences, we are not able to account for possible unmeasured confounders such as time of day of admission, health literacy, personality differences, physician turnover, or nursing and other ancillary care that could contribute to these findings. In addition to its observational study design, our study has several other limitations. First, our study was performed at a single institution, thus limiting its generalizability. Second, as a retrospective study based on observational data, no definitive conclusions regarding causality can be made. Third, although our response rate was low, it is comparable to other studies that have examined underserved populations.[33, 34] Fourth, because our survey was performed 30 days after hospitalization, this may impart imprecision on our outcomes measures. Finally, we were not able to mitigate selection bias through imputation for missing data .
All together, given the small absolute differences between the groups in patients' ratings of their overall care compared to large differences in possible confounders, these findings call for further exploration into the significance and possible mechanisms of these outcomes. Our study raises the potential possibility that the structural component of a care team may play a role in overall patient satisfaction. If this is the case, future studies of team structure could help inform how best to optimize this component for the patient experience. On the other hand, if process differences are to explain our findings, it is important to distill the types of processes hospitalists are using to improve the patient experience and potentially export this to resident services.
Finally, if similar results were found in other institutions, these findings could have implications on how hospitals respond to new payment models that are linked to patient‐experience measures. For example, the Hospital Value‐Based Purchasing Program currently links the Centers for Medicare and Medicaid Services payments to a set of quality measures that consist of (1) clinical processes of care (70%) and (2) the patient experience (30%).[1] Given this linkage, any small changes in the domain of patient satisfaction could have large payment implications on a national level.
CONCLUSION
In summary, in this large‐scale multiyear study, patients cared for by a nonteaching hospitalist service reported greater satisfaction with their overall care than patients cared for by a general medicine teaching service. This difference could be mediated by the structural differences between these 2 services. As hospitals seek to optimize patient experiences in an era where reimbursement models are now being linked to patient‐experience measures, future work should focus on further understanding the mechanisms for these findings.
Disclosures
Financial support for this work was provided by the Robert Wood Johnson Investigator Program (RWJF Grant ID 63910 PI Meltzer), a Midcareer Career Development Award from the National Institute of Aging (1 K24 AG031326‐01, PI Meltzer), and a Clinical and Translational Science Award (NIH/NCATS 2UL1TR000430‐08, PI Solway, Meltzer Core Leader). The authors report no conflicts of interest.
- Hospital Consumer Assessment of Healthcare Providers and Systems. HCAHPS fact sheet. CAHPS hospital survey August 2013. Available at: http://www.hcahpsonline.org/files/August_2013_HCAHPS_Fact_Sheet3.pdf. Accessed February 2, 2015.
- , , , et al. Transitions of Care Consensus policy statement: American College of Physicians, Society of General Internal Medicine, Society of Hospital Medicine, American Geriatrics Society, American College Of Emergency Physicians, and Society for Academic Emergency Medicine. J Hosp Med. 2009;4(6):364–370.
- Accreditation Council for Graduate Medical Education. Common program requirements. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/ProgramRequirements/CPRs2013.pdf. Accessed January 15, 2015.
- , , . Increasing a patient's ability to identify his or her attending physician using a patient room display. Arch Intern Med. 2010;170(12):1084–1085.
- , , , , , . Ability of hospitalized patients to identify their in‐hospital physicians. Arch Intern Med. 2009;169(2):199–201.
- , , , et al. Hospitalized patients' understanding of their plan of care. Mayo Clin Proc. 2010;85(1):47–52.
- , , , et al. Patient‐physician communication at hospital discharge and patients' understanding of the postdischarge treatment plan. Arch Intern Med. 1997;157(9):1026–1030.
- , , , et al. Improving inpatients' identification of their doctors: use of FACE cards. Jt Comm J Qual Patient Saf. 2009;35(12):613–619.
- , , , , , . The impact of facecards on patients' knowledge, satisfaction, trust, and agreement with hospital physicians: a pilot study. J Hosp Med. 2014;9(3):137–141.
- , , . Restructuring an inpatient resident service to improve outcomes for residents, students, and patients. Acad Med. 2011;86(12):1500–1507.
- , , . Residency training in the modern era: the pipe dream of less time to learn more, care better, and be more professional. Arch Intern Med. 2005;165(22):2561–2562.
- , , , , . Managing discontinuity in academic medical centers: strategies for a safe and effective resident sign‐out. J Hosp Med. 2006;1(4):257–266.
- , , , . Hospitalist staffing and patient satisfaction in the national Medicare population. J Hosp Med. 2013;8(3):126–131.
- , , , et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
- , , , , , . The Effects of on‐duty napping on intern sleep time and fatigue. Ann Intern Med. 2006;144(11):792–798.
- , , , et al. Patients evaluate their hospital care: a national survey. Health Aff (Millwood). 1991;10(4):254–267.
- , , , . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.
- Agency for Healthcare Research and Quality. Welcome to HCUPnet. Available at: http://hcupnet.ahrq.gov/HCUPnet.jsp?Id=F70FC59C286BADCB371(4):293–295.
- , , , et al. In the wake of the 2003 and 2011 duty hours regulations, how do internal medicine interns spend their time? J Gen Intern Med. 2013;28(8):1042–1047.
- , , , , , . The composition of intern work while on call. J Gen Intern Med. 2012;27(11):1432–1437.
- , , , et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649–655.
- , , , et al. The impact of hospitalist discontinuity on hospital cost, readmissions, and patient satisfaction. J Gen Intern Med. 2014;29(7):1004–1008.
- , , , , . Hospitalist time usage and cyclicality: opportunities to improve efficiency. J Hosp Med. 2010;5(6):329–334.
- , , , et al. Where did the day go?—a time‐motion study of hospitalists. J Hosp Med. 2010;5(6):323–328.
- , , . How hospitalists spend their time: insights on efficiency and safety. J Hosp Med. 2006;1(2):88–93.
- , , . Patient satisfaction associated with correct identification of physician's photographs. Mayo Clin Proc. 2001;76(6):604–608.
- , , , . Comparing patient outcomes of academician‐preceptors, hospitalist‐preceptors, and hospitalists on internal medicine services in an academic medical center. J Gen Intern Med. 2014;29(12):1672–1678.
- , , , . Comparison of processes and outcomes of pneumonia care between hospitalists and community‐based primary care physicians. Mayo Clin Proc. 2002;77(10):1053–1058.
- , , , , , . Outcomes of care by hospitalists, general internists, and family physicians. N Engl J Med. 2007;357(25):2589–2600.
- . A systematic review of outcomes and quality measures in adult patients cared for by hospitalists vs nonhospitalists. Mayo Clin Proc. 2009;84(3):248–254.
- , . Do hospitalist physicians improve the quality of inpatient care delivery? A systematic review of process, efficiency and outcome measures. BMC Med. 2011;9(1):58.
- , . Patients' experiences of everyday life after lung transplantation. J Clin Nurs. 2009;18(24):3472–3479.
- , , , et al. Optimal design features for surveying low‐income populations. J Health Care Poor Underserved. 2005;16(4):677–690.
- Hospital Consumer Assessment of Healthcare Providers and Systems. HCAHPS fact sheet. CAHPS hospital survey August 2013. Available at: http://www.hcahpsonline.org/files/August_2013_HCAHPS_Fact_Sheet3.pdf. Accessed February 2, 2015.
- , , , et al. Transitions of Care Consensus policy statement: American College of Physicians, Society of General Internal Medicine, Society of Hospital Medicine, American Geriatrics Society, American College Of Emergency Physicians, and Society for Academic Emergency Medicine. J Hosp Med. 2009;4(6):364–370.
- Accreditation Council for Graduate Medical Education. Common program requirements. Available at: http://www.acgme.org/acgmeweb/Portals/0/PFAssets/ProgramRequirements/CPRs2013.pdf. Accessed January 15, 2015.
- , , . Increasing a patient's ability to identify his or her attending physician using a patient room display. Arch Intern Med. 2010;170(12):1084–1085.
- , , , , , . Ability of hospitalized patients to identify their in‐hospital physicians. Arch Intern Med. 2009;169(2):199–201.
- , , , et al. Hospitalized patients' understanding of their plan of care. Mayo Clin Proc. 2010;85(1):47–52.
- , , , et al. Patient‐physician communication at hospital discharge and patients' understanding of the postdischarge treatment plan. Arch Intern Med. 1997;157(9):1026–1030.
- , , , et al. Improving inpatients' identification of their doctors: use of FACE cards. Jt Comm J Qual Patient Saf. 2009;35(12):613–619.
- , , , , , . The impact of facecards on patients' knowledge, satisfaction, trust, and agreement with hospital physicians: a pilot study. J Hosp Med. 2014;9(3):137–141.
- , , . Restructuring an inpatient resident service to improve outcomes for residents, students, and patients. Acad Med. 2011;86(12):1500–1507.
- , , . Residency training in the modern era: the pipe dream of less time to learn more, care better, and be more professional. Arch Intern Med. 2005;165(22):2561–2562.
- , , , , . Managing discontinuity in academic medical centers: strategies for a safe and effective resident sign‐out. J Hosp Med. 2006;1(4):257–266.
- , , , . Hospitalist staffing and patient satisfaction in the national Medicare population. J Hosp Med. 2013;8(3):126–131.
- , , , et al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137(11):866–874.
- , , , , , . The Effects of on‐duty napping on intern sleep time and fatigue. Ann Intern Med. 2006;144(11):792–798.
- , , , et al. Patients evaluate their hospital care: a national survey. Health Aff (Millwood). 1991;10(4):254–267.
- , , , . A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–383.
- Agency for Healthcare Research and Quality. Welcome to HCUPnet. Available at: http://hcupnet.ahrq.gov/HCUPnet.jsp?Id=F70FC59C286BADCB371(4):293–295.
- , , , et al. In the wake of the 2003 and 2011 duty hours regulations, how do internal medicine interns spend their time? J Gen Intern Med. 2013;28(8):1042–1047.
- , , , , , . The composition of intern work while on call. J Gen Intern Med. 2012;27(11):1432–1437.
- , , , et al. Effect of the 2011 vs 2003 duty hour regulation‐compliant models on sleep duration, trainee education, and continuity of patient care among internal medicine house staff: a randomized trial. JAMA Intern Med. 2013;173(8):649–655.
- , , , et al. The impact of hospitalist discontinuity on hospital cost, readmissions, and patient satisfaction. J Gen Intern Med. 2014;29(7):1004–1008.
- , , , , . Hospitalist time usage and cyclicality: opportunities to improve efficiency. J Hosp Med. 2010;5(6):329–334.
- , , , et al. Where did the day go?—a time‐motion study of hospitalists. J Hosp Med. 2010;5(6):323–328.
- , , . How hospitalists spend their time: insights on efficiency and safety. J Hosp Med. 2006;1(2):88–93.
- , , . Patient satisfaction associated with correct identification of physician's photographs. Mayo Clin Proc. 2001;76(6):604–608.
- , , , . Comparing patient outcomes of academician‐preceptors, hospitalist‐preceptors, and hospitalists on internal medicine services in an academic medical center. J Gen Intern Med. 2014;29(12):1672–1678.
- , , , . Comparison of processes and outcomes of pneumonia care between hospitalists and community‐based primary care physicians. Mayo Clin Proc. 2002;77(10):1053–1058.
- , , , , , . Outcomes of care by hospitalists, general internists, and family physicians. N Engl J Med. 2007;357(25):2589–2600.
- . A systematic review of outcomes and quality measures in adult patients cared for by hospitalists vs nonhospitalists. Mayo Clin Proc. 2009;84(3):248–254.
- , . Do hospitalist physicians improve the quality of inpatient care delivery? A systematic review of process, efficiency and outcome measures. BMC Med. 2011;9(1):58.
- , . Patients' experiences of everyday life after lung transplantation. J Clin Nurs. 2009;18(24):3472–3479.
- , , , et al. Optimal design features for surveying low‐income populations. J Health Care Poor Underserved. 2005;16(4):677–690.
© 2015 Society of Hospital Medicine
Updates in Perioperative Medicine
Given the rapid expansion of the field of perioperative medicine, clinicians need to remain apprised of the current evidence to ensure optimization of patient care. In this update, we review 10 key articles from the perioperative literature, with the goal of summarizing the most clinically important evidence over the past year. This summary of recent literature in perioperative medicine is derived from the Update in Perioperative Medicine sessions presented at the 10th Annual Perioperative Medicine Summit and the Society of General Internal Medicine 38th Annual Meeting. A systematic search strategy was used to identify pertinent articles, and the following were selected by the authors based on their relevance to the clinical practice of perioperative medicine.
PERIOPERATIVE CARDIOVASCULAR CARE
Fleisher LA, Fleischmann KE, Auerbach AD, et al. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. Circulation. 2014;130:e278e333.
Background
The American College of Cardiology/American Heart Association (ACC/AHA) perioperative guideline provides recommendations for the evaluation and management of cardiovascular disease in patients undergoing noncardiac surgery.
Findings
The new guideline combines the evaluation of surgery‐ and patient‐specific risk in the algorithm for preoperative cardiovascular evaluation into a single step and recommends the use of 1 of 3 tools: the Revised Cardiac Risk Index (RCRI),[1] National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator,[2] or the NSQIP‐derived myocardial infarction and cardiac arrest calculator.[3] Estimation of risk is also simplified by stratification into only 2 groups: low risk (risk of major adverse cardiac event <1%) and elevated risk (1% risk). Coronary evaluation can be considered for patients with elevated cardiac risk and poor functional capacity, but is advised only if the results would alter perioperative management. For example, a patient with very high risk who has evidence of ischemia on stress testing may choose to forego surgery. Preoperative coronary revascularization is only indicated for patients meeting criteria in the nonsurgical setting.
For patients with previous percutaneous coronary intervention, the ACC/AHA has not changed its recommendations to optimally delay surgery for at least 30 days after bare‐metal stenting and at least 1 year after drug‐eluting stent (DES) placement. However, in patients with a DES placed 6 to 12 months previously, surgery can be performed if the risks of surgical delay outweigh the risks of DES thrombosis. After any type of coronary stenting, dual antiplatelet therapy should be continued uninterrupted through the first 4 to 6 weeks and even later whenever feasible. If not possible, aspirin therapy should be maintained through surgery unless bleeding risk is too high.
The guideline recommends perioperative continuation of ‐blockers in patients taking them chronically. Preoperative initiation of ‐blocker therapy may be considered for patients with myocardial ischemia on stress testing or 3 RCRI factors and should be started far enough in advance to allow determination of patient's tolerance prior to surgery.
Cautions
Many recommendations are based on data from nonrandomized trials or expert opinion, and the data in areas such as perioperative ‐blockade continue to evolve.
Implications
The ACC/AHA guideline continues to be a critically valuable resource for hospitalists providing perioperative care to noncardiac surgery patients.
Wijeysundera DN, Duncan D, Nkonde‐Price C, et al. Perioperative beta blockade in noncardiac surgery: a systematic review for the 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines.
J Am Coll Cardiol. 2014;64(22):24062425.
Background
Various clinical trials have reported conflicting results regarding the efficacy and safety of perioperative ‐blockers resulting in guideline committees changing their recommendations. Because of questions raised regarding the scientific integrity of the DECREASE (Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography)‐I[4] and DECREASE‐IV[5] trials as well as the dosing of ‐blockers in POISE (PeriOperative Ischemic Evaluation) study,[6] this systematic review was performed in conjunction with the ACC/AHA guideline update[7] to evaluate the data with and without these trials.
Findings
Sixteen randomized control trials (RCTs) (n=12,043) and 1 cohort study (n=348) were included in the analysis. Perioperative ‐blockers were associated with a reduction in nonfatal myocardial infarction (MI) (relative risk [RR]: 0.69; 95% confidence interval [CI]: 0.58‐0.82; P<0.001) but an increase in bradycardia (RR: 2.61; 95% CI: 2.18‐3.12), hypotension (RR: 1.47; 95% CI: 1.34‐1.6), and nonfatal strokes (RR: 1.76; 95% CI: 1.07‐2.91; P=0.02). The POISE trial was the only one demonstrating a statistically significant increase in stroke.
The major discrepancy between the DECREASE trials and the other RCTs was related to mortalitya reduction in both cardiovascular and all‐cause death in DECREASE but an increased risk of all‐cause death in the other trials.
Cautions
Because of its size, the POISE trial heavily influences the results, particularly for mortality and stroke. Including the DECREASE trials reduces the otherwise increased risk for death to a null effect. Exclusion of the POISE and DECREASE trials leaves few data to make conclusions about safety and efficacy of perioperative ‐blockade. Several cohort studies have found metoprolol to be associated with worse outcomes than with atenolol or bisoprolol (which were preferred by the European Society of Cardiology guidelines).[8]
Implications
Perioperative ‐blockade started within 1 day of noncardiac surgery was associated with fewer nonfatal MIs but at the cost of an increase in hypotension, bradycardia, and a possible increase in stroke and death. Long‐term ‐blockade should be continued perioperatively, whereas the decision to initiate a ‐blocker should be individualized. If starting a ‐blocker perioperatively, it should be done 2 days before surgery.
Botto F, Alonso‐Coello P, Chan MT, et al.; on behalf of The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Investigators. Myocardial injury after noncardiac surgery: a large, international, prospective cohort study establishing diagnostic criteria, characteristics, predictors, and 30‐day outcomes. Anesthesiology. 2014;120(3):564578.
Background
Many patients sustain myocardial injury in the perioperative period as evidenced by troponin elevations, but most do not meet diagnostic criteria for MI. Myocardial injury after noncardiac surgery (MINS) is defined as prognostically relevant myocardial injury due to ischemia that occurs within 30 days after noncardiac surgery. This international, prospective cohort study of 15,065 patients 45 years old who underwent in‐patient noncardiac surgery determined diagnostic criteria, characteristics, predictors, and 30‐day outcomes of MINS.
Findings
The diagnostic criterion for MINS was a peak troponin T level 0.03 ng/mL judged to be due to an ischemic etiology. Twelve independent predictors of MINS were identified including age 75 years, known cardiovascular disease or risk factors, and surgical factors. MINS was an independent predictor of 30‐day mortality (adjusted hazard ratio [HR]: 3.87; 95% CI: 2.96‐5.08). Age >75 years, ST elevation, or new left bundle branch block, and anterior ischemic findings were independent predictors of 30‐day mortality among patients with MINS.
Cautions
Although screening high‐risk surgical patients without signs or symptoms of ischemia with postoperative troponins will increase the frequency of diagnosing MINS, evidence for an effective treatment has not yet been established. The ACC/AHA guidelines state that routine screening is of uncertain benefit for this reason.
Implications
Because MINS is common and carries a poor 30‐day prognosis, clinical trials are needed to determine when to obtain postoperative troponins and how to prevent and treat this complication.[9] Some observational data from POISE suggest that aspirin and statins can reduce the risk of 30‐day mortality in patients with postoperative MIs.
Devereaux PJ, Mrkobrada M, Sessler DI, et al. for the POISE‐2 Investigators. Aspirin in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):14941503.
Devereaux PJ, Sessler DI, Leslie K, et al. for the POISE‐2 Investigators. Clonidine in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):15041513.
Background
Medical risk reduction with aspirin and other agents in perioperative patients remains controversial. The POISE‐2 trial is a blinded RCT examining the effects of aspirin and clonidine on outcomes in >10,000 noncardiac surgery patients at risk of cardiovascular complications. The aspirin arm of the study included the initiation group and the continuation stratum, as well as placebo. Patients in the clonidine portion of the trial received 0.2 mg of clonidine or placebo daily for the same time periods.
Findings
The primary outcome was a composite of death or nonfatal MI within 30 days of surgery. Outcomes were similar in patients initiated or continued on aspirin. No difference was seen between aspirin or placebo in the primary outcome (7.0% vs 7.1%; HR: 0.86; 95% CI: 0.86‐1.15; P=0.92). There were no differences in rates of MI, venous thromboembolism, or stroke. Major bleeding rates were higher in aspirin versus placebo‐treated patients (4.6% vs 3.8%; HR: 1.23; 95% CI: 1.01‐1.49; P=0.04).
Clonidine did not alter the composite outcome of death or nonfatal MI (7.3% vs 6.8%; HR: 1.08; 95% CI: 0.93‐1.26; P=0.29). Clinically significant hypotension, bradycardia, and nonfatal cardiac arrest were more common in clonidine‐treated patients, although no difference was detected in stroke rates.
Cautions
Although patients in the trial had cardiovascular risk factors, <24% of patients had known coronary artery disease, and <5% had coronary stents. Conclusions based on this trial regarding perioperative management of antiplatelet therapy should not include patients with coronary artery stents.
Implications
Aspirin started before surgery and continued perioperatively did not decrease the rate of death or nonfatal MI but increased the risk of major bleeding. Perioperative management of aspirin needs to be undertaken in the context of cardiac and bleeding risks. Clonidine also did not improve outcomes and increased the risk of bradycardia and hypotension. Current guidelines recommend against using alpha‐2 agonists for prevention of perioperative cardiac events7; however, patients already on alpha‐2 agonists should not stop them abruptly.
PERIOPERATIVE PULMONARY CARE
Mutter TC, Chateau D, Moffatt M, et al. A matched cohort study of postoperative outcomes in obstructive sleep apnea: could preoperative diagnosis and treatment prevent complications? Anesthesiology. 2014;121(4):707718.
Background
An increasing body of literature associates obstructive sleep apnea (OSA) with an increased risk of postoperative complications. Despite evidence of risk, potential benefits of preoperative diagnosis and treatment of OSA remain unclear.
Findings
Using databases to identify patients prescribed continuous positive airway pressure (CPAP) therapy, the study compared postoperative outcomes of patients who underwent surgery any time after polysomnography (PSG) and CPAP prescription (diagnosed OSA [DOSA]) and those who had surgery during the 5 years preceding their PSG (undiagnosed OSA [UOSA]). These patients were matched with patients who underwent the same procedure for the same indication and had no insurance claims for PSG or diagnosis of sleep‐disordered breathing.
After multivariate analysis, OSA of any type was associated with increased pulmonary complications (odds ratio [OR]: 2.08; 95% CI: 1.35‐2.19). However, no significant differences in respiratory outcomes were noted between DOSA patients (N=2640) and those with UOSA (N=1571). DOSA patients did have fewer cardiovascular complications than UOSA patients (OR: 0.34; 95% CI: 0.15‐0.77). Only severe OSA (apnea‐hypopnea index >30) was associated with increased pulmonary and cardiovascular complications.
Cautions
Although this study suggests an association between preoperative diagnosis and treatment of OSA and reduced cardiovascular complications, the results are not definitive due to the inability to control for all confounding variables in a retrospective study utilizing an administrative database.
Implications
OSA is an important risk factor for postoperative complications, and this study suggests that preoperative treatment with CPAP is associated with reduced risk of cardiovascular complications, particularly in patients with severe OSA. Future controlled trials should focus on the risk‐reduction potential of preoperative diagnosis and treatment of OSA.
Mazo V, Sabat S, Canet J, et al. Prospective external validation of a predictive score for postoperative pulmonary complications. Anesthesiology. 2014;121:219231.
Background
In 2010, Canet et al. published a novel risk index, the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) index, to provide a quantitative estimate of the risk of postoperative pulmonary complications (PPCs).[10]
In the current report, Mazo and colleagues studied the ARISCAT index in a broader sample to characterize its accuracy in predicting PPC risk. The ARISCAT index is derived from clinical risk factors: (1) age, (2) preoperative oxygen saturation, (3) respiratory infection in the prior month, (4) anemia, (5) surgical site, (6) duration of surgery, and (7) emergency surgery, with varying weights based on the strength of the association in a multivariable analysis. This score can be calculated via addition of these weighted risk factors, with a score>45 equal to high risk for PPC.
Findings
Examining 5099 patients from 63 European hospitals, the authors definition of PPC included respiratory failure, pulmonary infection, pleural effusion, atelectasis, pneumothorax, bronchospasm, and aspiration pneumonitis. PPC rates were as follows: low risk (3.39%), intermediate risk (12.98%), and high risk (38.01%). The positive likelihood ratio for PPC among the highest risk group was 7.12. The C statistic for fit was 0.80. Observed PPC rates were higher than predicted for the low (3.39% vs 0.87%) and intermediate (12.98% vs 7.82%) risk groups.
Cautions
The calibration slopes were less than ideal in all subsamples, with the Western European sample performing better than the other geographic areas; suggesting that the coefficients on the ARISCAT index may benefit from recalibration to match specific populations.
Implications
This is the first major pulmonary risk index that has been externally validated. Its use of readily available clinical information, simplicity, and accuracy in estimating PPC risk make it an important addition to the toolkit during a preoperative evaluation.
PERIOPERATIVE ATRIAL FIBRILLATION/ANTICOAGULATION
Gialdini G, Nearing K, Bhave P, et al. Perioperative atrial fibrillation and the long term risk of ischemic stroke. JAMA. 2014;312(6):616622.
Background
New‐onset atrial fibrillation (AF) is the most common perioperative arrhythmia.[11] However, little is known regarding the long‐term risks of ischemic stroke in patients who develop perioperative AF. This retrospective cohort study examined adults with no preexisting history of AF, hospitalized for surgery, and discharged free of cerebrovascular disease between 2007 and 2011 (n=1,729,360).
Findings
Of the eligible patients, 1.43% (95% CI: 1.41%‐1.45%) developed perioperative AF, and 0.81% (95% CI: 0.79%‐0.82%) had a stroke up to 1 year after discharge. Perioperative AF was associated with subsequent stroke after both cardiac (HR: 1.3; 95% CI: 1.1‐1.6) and noncardiac surgery (HR: 2; 95% CI: 1.7‐2.3). The association with stroke was stronger for perioperative AF after noncardiac versus cardiac surgery (P<0.001 for interaction).
Cautions
This is a retrospective cohort study, using claims data to identify AF and stroke. Data on duration of the perioperative AF episodes or use of antithrombotic therapies were not available.
Implications
The association found between perioperative AF and long‐term risk of ischemic stroke may suggest that perioperative AF, especially after noncardiac surgery, should be treated aggressively in terms of thromboembolic risk; however, further data will be required to validate this association.
Van Diepen S, Youngson E, Ezekowitz J, McAlister F. Which risk score best predicts perioperative outcomes in nonvalvular atrial fibrillation patients undergoing noncardiac surgery? Am Heart J. 2014;168(1):6067.
Background
Patients with nonvalvular AF (NVAF) are at increased risk for adverse perioperative outcomes after noncardiac surgery.[12] The RCRI is commonly used to predict perioperative cardiovascular events for all patients, including those with NVAF, though AF is not part of this risk assessment. The goal of this retrospective cohort study was to examine the prognostic utility of already existing NVAF risk indices, including the CHADS2 (Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, prior stroke or transient ischemic attack), CHA2DS2‐VASc (Congestive heart failure; Hypertension; Age 75 years; Diabetes mellitus; Stroke, TIA, or thromboembolism [TE]; Vascular disease; Age 65 to 74 years; Sex category [female]), and R2CHADS2 (Renal dysfunction, Congestive heart failure, Hypertension, Age, Diabetes, Stroke/TIA) for perioperative outcomes in patients undergoing noncardiac surgery.
Findings
A population dataset of NVAF patients (n=32,160) who underwent noncardiac surgery was examined, with outcome measures including 30‐day mortality, stroke, TIA, or systemic embolism. The incidence of the 30‐day composite outcome was 4.2% and the C indices were 0.65 for the RCRI, 0.67 for CHADS2, 0.67 for CHA2DS2‐VASc, and 0.68 for R2CHADS2. The Net Reclassification Index (NRI), a measure evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors, was calculated. All NVAF scores performed better than the RCRI for predicting mortality risk (NRI: 12.3%, 8.4%, and 13.3% respectively, all P<0.01).
Cautions
Patients in the highest risk category by RCRI appear to have an unadjusted higher 30‐day mortality risk (8%) than that predicted by the other 3 scores (5%, 5.6%, and 5%), indicating that these risk scores should not completely supplant the RCRI for risk stratification in this population. In addition, the overall improvement in predictive capacity of the CHADS2, CHA2DS2‐VASc, and R2CHADS2, although superior to the RCRI, is modest.
Implications
These findings indicate that the preoperative risk stratification for patients with NVAF can be improved by utilizing the CHADS2, CHA2DS2‐VASc, or R2CHADS2 scores when undergoing noncardiac surgery. For patients with NVAF identified as high risk for adverse outcomes, this assessment can be integrated into the preoperative discussion on the risks/benefits of surgery.
Steinberg BA, Peterson ED, Kim S, et al. Use and outcomes associated with bridging during anticoagulation interruptions in patients with atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT‐AF). Circulation. 2015;131:488494
Background
Oral anticoagulation (OAC) significantly reduces the risk of stroke in patients with AF. Many AF patients on long‐term anticoagulation undergo procedures requiring temporary interruption of OAC. Although guidelines have been published on when and how to initiate bridging therapy, they are based on observational data. Thus, it remains unclear which patients should receive bridging anticoagulation.
Findings
This is a US registry of outpatients with AF with temporary interruptions of OAC for a procedure. Of 7372 patients treated with OAC, 2803 overall interruption events occurred in 2200 patients (30%). Bridging anticoagulants were used in 24% (n=665). Bleeding events were more common in bridged than nonbridged patients (5.0% vs 1.3%; adjusted OR: 3.84; P<0.0001). The overall composite end point of myocardial infarction, stroke or systemic embolism, major bleeding, hospitalization, or death within 30 days was significantly higher in patients receiving bridging (13% vs 6.3%; adjusted OR: 1.94; P=0.0001). This statistically significant increase in the composite outcome, which includes cardiovascular events, is most likely in part secondary to inclusion of bleeding events. The recently published BRIDGE (Bridging Anticoagulation in Patients who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery) trial did not find a statistically significant difference in cardiovascular events between bridged and nonbridged patients.[13]
Cautions
Although patients who were bridged appear to have had more comorbidities and a higher mean CHADS2 score than patients who were not bridged, it is difficult to determine which population of patients may be high risk enough to warrant bridging, as indicated by current American College of Chest Physicians guidelines, as this was not evaluated in this study
Implications
The use of bridging anticoagulation was significantly associated with higher overall bleeding and adverse event rates. The BRIDGE trial also found that forgoing bridging anticoagulation decreased the risk of major bleeding in patients with AF and was noninferior to bridging for the prevention of arterial TE.[13]
- , , , et al. Derivation and prospective evaluation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100:1043–1049.
- , , , et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833–842.
- , , , et al. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation. 2011;124:381–387.
- , , , et al. The effect of bisoprolol on perioperative mortality and myocardial infarction in high‐risk patients undergoing vascular surgery. Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. N Engl J Med. 1999;341(24):1789–1794.
- , , , et al; Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. Bisoprolol and fluvastatin for the reduction of perioperative cardiac mortality and myocardial infarction in intermediate‐risk patients undergoing noncardiovascular surgery: a randomized controlled trial (DECREASE‐IV). Ann Surg. 2009;249(6):921–926.
- POISE Study Group, , , , et al. Effects of extended‐release metoprolol succinate in patients undergoing non‐cardiac surgery (POISE trial): a randomised controlled trial. Lancet. 2008;371(9627):1839–1847.
- , , , et al. American College of Cardiology; American Heart Association. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol. 2014;64(22):e77–e137.
- , , , et al. 2014 ESC/ESA Guidelines on non‐cardiac surgery: cardiovascular assessment and management: The Joint Task Force on non‐cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur Heart J. 2014;35(35):2383–431.
- , , , et al. The long‐term impact of early cardiovascular therapy intensification for postoperative troponin elevation after major vascular surgery. Anesth Analg. 2014;119(5):1053–1063.
- , , , et al. ARISCAT Group: Prediction of postoperative pulmonary complications in a population‐based surgical cohort. Anesthesiology. 2010;113:1338–1350.
- , . Noncardiac surgery: postoperative arrhythmias. Crit Care Med. 2000;28(10 suppl):N145–N150.
- , , , et al. Incidence, predictors, and outcomes associated with postoperative atrial fibrillation after major cardiac surgery. Am Heart J. 2012;164(6):918–924.
- , , , et al. Perioperative bridging anticoagulation in patients with atrial fibrillation. N Engl J Med. 2015;373(9):823–833.
Given the rapid expansion of the field of perioperative medicine, clinicians need to remain apprised of the current evidence to ensure optimization of patient care. In this update, we review 10 key articles from the perioperative literature, with the goal of summarizing the most clinically important evidence over the past year. This summary of recent literature in perioperative medicine is derived from the Update in Perioperative Medicine sessions presented at the 10th Annual Perioperative Medicine Summit and the Society of General Internal Medicine 38th Annual Meeting. A systematic search strategy was used to identify pertinent articles, and the following were selected by the authors based on their relevance to the clinical practice of perioperative medicine.
PERIOPERATIVE CARDIOVASCULAR CARE
Fleisher LA, Fleischmann KE, Auerbach AD, et al. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. Circulation. 2014;130:e278e333.
Background
The American College of Cardiology/American Heart Association (ACC/AHA) perioperative guideline provides recommendations for the evaluation and management of cardiovascular disease in patients undergoing noncardiac surgery.
Findings
The new guideline combines the evaluation of surgery‐ and patient‐specific risk in the algorithm for preoperative cardiovascular evaluation into a single step and recommends the use of 1 of 3 tools: the Revised Cardiac Risk Index (RCRI),[1] National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator,[2] or the NSQIP‐derived myocardial infarction and cardiac arrest calculator.[3] Estimation of risk is also simplified by stratification into only 2 groups: low risk (risk of major adverse cardiac event <1%) and elevated risk (1% risk). Coronary evaluation can be considered for patients with elevated cardiac risk and poor functional capacity, but is advised only if the results would alter perioperative management. For example, a patient with very high risk who has evidence of ischemia on stress testing may choose to forego surgery. Preoperative coronary revascularization is only indicated for patients meeting criteria in the nonsurgical setting.
For patients with previous percutaneous coronary intervention, the ACC/AHA has not changed its recommendations to optimally delay surgery for at least 30 days after bare‐metal stenting and at least 1 year after drug‐eluting stent (DES) placement. However, in patients with a DES placed 6 to 12 months previously, surgery can be performed if the risks of surgical delay outweigh the risks of DES thrombosis. After any type of coronary stenting, dual antiplatelet therapy should be continued uninterrupted through the first 4 to 6 weeks and even later whenever feasible. If not possible, aspirin therapy should be maintained through surgery unless bleeding risk is too high.
The guideline recommends perioperative continuation of ‐blockers in patients taking them chronically. Preoperative initiation of ‐blocker therapy may be considered for patients with myocardial ischemia on stress testing or 3 RCRI factors and should be started far enough in advance to allow determination of patient's tolerance prior to surgery.
Cautions
Many recommendations are based on data from nonrandomized trials or expert opinion, and the data in areas such as perioperative ‐blockade continue to evolve.
Implications
The ACC/AHA guideline continues to be a critically valuable resource for hospitalists providing perioperative care to noncardiac surgery patients.
Wijeysundera DN, Duncan D, Nkonde‐Price C, et al. Perioperative beta blockade in noncardiac surgery: a systematic review for the 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines.
J Am Coll Cardiol. 2014;64(22):24062425.
Background
Various clinical trials have reported conflicting results regarding the efficacy and safety of perioperative ‐blockers resulting in guideline committees changing their recommendations. Because of questions raised regarding the scientific integrity of the DECREASE (Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography)‐I[4] and DECREASE‐IV[5] trials as well as the dosing of ‐blockers in POISE (PeriOperative Ischemic Evaluation) study,[6] this systematic review was performed in conjunction with the ACC/AHA guideline update[7] to evaluate the data with and without these trials.
Findings
Sixteen randomized control trials (RCTs) (n=12,043) and 1 cohort study (n=348) were included in the analysis. Perioperative ‐blockers were associated with a reduction in nonfatal myocardial infarction (MI) (relative risk [RR]: 0.69; 95% confidence interval [CI]: 0.58‐0.82; P<0.001) but an increase in bradycardia (RR: 2.61; 95% CI: 2.18‐3.12), hypotension (RR: 1.47; 95% CI: 1.34‐1.6), and nonfatal strokes (RR: 1.76; 95% CI: 1.07‐2.91; P=0.02). The POISE trial was the only one demonstrating a statistically significant increase in stroke.
The major discrepancy between the DECREASE trials and the other RCTs was related to mortalitya reduction in both cardiovascular and all‐cause death in DECREASE but an increased risk of all‐cause death in the other trials.
Cautions
Because of its size, the POISE trial heavily influences the results, particularly for mortality and stroke. Including the DECREASE trials reduces the otherwise increased risk for death to a null effect. Exclusion of the POISE and DECREASE trials leaves few data to make conclusions about safety and efficacy of perioperative ‐blockade. Several cohort studies have found metoprolol to be associated with worse outcomes than with atenolol or bisoprolol (which were preferred by the European Society of Cardiology guidelines).[8]
Implications
Perioperative ‐blockade started within 1 day of noncardiac surgery was associated with fewer nonfatal MIs but at the cost of an increase in hypotension, bradycardia, and a possible increase in stroke and death. Long‐term ‐blockade should be continued perioperatively, whereas the decision to initiate a ‐blocker should be individualized. If starting a ‐blocker perioperatively, it should be done 2 days before surgery.
Botto F, Alonso‐Coello P, Chan MT, et al.; on behalf of The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Investigators. Myocardial injury after noncardiac surgery: a large, international, prospective cohort study establishing diagnostic criteria, characteristics, predictors, and 30‐day outcomes. Anesthesiology. 2014;120(3):564578.
Background
Many patients sustain myocardial injury in the perioperative period as evidenced by troponin elevations, but most do not meet diagnostic criteria for MI. Myocardial injury after noncardiac surgery (MINS) is defined as prognostically relevant myocardial injury due to ischemia that occurs within 30 days after noncardiac surgery. This international, prospective cohort study of 15,065 patients 45 years old who underwent in‐patient noncardiac surgery determined diagnostic criteria, characteristics, predictors, and 30‐day outcomes of MINS.
Findings
The diagnostic criterion for MINS was a peak troponin T level 0.03 ng/mL judged to be due to an ischemic etiology. Twelve independent predictors of MINS were identified including age 75 years, known cardiovascular disease or risk factors, and surgical factors. MINS was an independent predictor of 30‐day mortality (adjusted hazard ratio [HR]: 3.87; 95% CI: 2.96‐5.08). Age >75 years, ST elevation, or new left bundle branch block, and anterior ischemic findings were independent predictors of 30‐day mortality among patients with MINS.
Cautions
Although screening high‐risk surgical patients without signs or symptoms of ischemia with postoperative troponins will increase the frequency of diagnosing MINS, evidence for an effective treatment has not yet been established. The ACC/AHA guidelines state that routine screening is of uncertain benefit for this reason.
Implications
Because MINS is common and carries a poor 30‐day prognosis, clinical trials are needed to determine when to obtain postoperative troponins and how to prevent and treat this complication.[9] Some observational data from POISE suggest that aspirin and statins can reduce the risk of 30‐day mortality in patients with postoperative MIs.
Devereaux PJ, Mrkobrada M, Sessler DI, et al. for the POISE‐2 Investigators. Aspirin in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):14941503.
Devereaux PJ, Sessler DI, Leslie K, et al. for the POISE‐2 Investigators. Clonidine in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):15041513.
Background
Medical risk reduction with aspirin and other agents in perioperative patients remains controversial. The POISE‐2 trial is a blinded RCT examining the effects of aspirin and clonidine on outcomes in >10,000 noncardiac surgery patients at risk of cardiovascular complications. The aspirin arm of the study included the initiation group and the continuation stratum, as well as placebo. Patients in the clonidine portion of the trial received 0.2 mg of clonidine or placebo daily for the same time periods.
Findings
The primary outcome was a composite of death or nonfatal MI within 30 days of surgery. Outcomes were similar in patients initiated or continued on aspirin. No difference was seen between aspirin or placebo in the primary outcome (7.0% vs 7.1%; HR: 0.86; 95% CI: 0.86‐1.15; P=0.92). There were no differences in rates of MI, venous thromboembolism, or stroke. Major bleeding rates were higher in aspirin versus placebo‐treated patients (4.6% vs 3.8%; HR: 1.23; 95% CI: 1.01‐1.49; P=0.04).
Clonidine did not alter the composite outcome of death or nonfatal MI (7.3% vs 6.8%; HR: 1.08; 95% CI: 0.93‐1.26; P=0.29). Clinically significant hypotension, bradycardia, and nonfatal cardiac arrest were more common in clonidine‐treated patients, although no difference was detected in stroke rates.
Cautions
Although patients in the trial had cardiovascular risk factors, <24% of patients had known coronary artery disease, and <5% had coronary stents. Conclusions based on this trial regarding perioperative management of antiplatelet therapy should not include patients with coronary artery stents.
Implications
Aspirin started before surgery and continued perioperatively did not decrease the rate of death or nonfatal MI but increased the risk of major bleeding. Perioperative management of aspirin needs to be undertaken in the context of cardiac and bleeding risks. Clonidine also did not improve outcomes and increased the risk of bradycardia and hypotension. Current guidelines recommend against using alpha‐2 agonists for prevention of perioperative cardiac events7; however, patients already on alpha‐2 agonists should not stop them abruptly.
PERIOPERATIVE PULMONARY CARE
Mutter TC, Chateau D, Moffatt M, et al. A matched cohort study of postoperative outcomes in obstructive sleep apnea: could preoperative diagnosis and treatment prevent complications? Anesthesiology. 2014;121(4):707718.
Background
An increasing body of literature associates obstructive sleep apnea (OSA) with an increased risk of postoperative complications. Despite evidence of risk, potential benefits of preoperative diagnosis and treatment of OSA remain unclear.
Findings
Using databases to identify patients prescribed continuous positive airway pressure (CPAP) therapy, the study compared postoperative outcomes of patients who underwent surgery any time after polysomnography (PSG) and CPAP prescription (diagnosed OSA [DOSA]) and those who had surgery during the 5 years preceding their PSG (undiagnosed OSA [UOSA]). These patients were matched with patients who underwent the same procedure for the same indication and had no insurance claims for PSG or diagnosis of sleep‐disordered breathing.
After multivariate analysis, OSA of any type was associated with increased pulmonary complications (odds ratio [OR]: 2.08; 95% CI: 1.35‐2.19). However, no significant differences in respiratory outcomes were noted between DOSA patients (N=2640) and those with UOSA (N=1571). DOSA patients did have fewer cardiovascular complications than UOSA patients (OR: 0.34; 95% CI: 0.15‐0.77). Only severe OSA (apnea‐hypopnea index >30) was associated with increased pulmonary and cardiovascular complications.
Cautions
Although this study suggests an association between preoperative diagnosis and treatment of OSA and reduced cardiovascular complications, the results are not definitive due to the inability to control for all confounding variables in a retrospective study utilizing an administrative database.
Implications
OSA is an important risk factor for postoperative complications, and this study suggests that preoperative treatment with CPAP is associated with reduced risk of cardiovascular complications, particularly in patients with severe OSA. Future controlled trials should focus on the risk‐reduction potential of preoperative diagnosis and treatment of OSA.
Mazo V, Sabat S, Canet J, et al. Prospective external validation of a predictive score for postoperative pulmonary complications. Anesthesiology. 2014;121:219231.
Background
In 2010, Canet et al. published a novel risk index, the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) index, to provide a quantitative estimate of the risk of postoperative pulmonary complications (PPCs).[10]
In the current report, Mazo and colleagues studied the ARISCAT index in a broader sample to characterize its accuracy in predicting PPC risk. The ARISCAT index is derived from clinical risk factors: (1) age, (2) preoperative oxygen saturation, (3) respiratory infection in the prior month, (4) anemia, (5) surgical site, (6) duration of surgery, and (7) emergency surgery, with varying weights based on the strength of the association in a multivariable analysis. This score can be calculated via addition of these weighted risk factors, with a score>45 equal to high risk for PPC.
Findings
Examining 5099 patients from 63 European hospitals, the authors definition of PPC included respiratory failure, pulmonary infection, pleural effusion, atelectasis, pneumothorax, bronchospasm, and aspiration pneumonitis. PPC rates were as follows: low risk (3.39%), intermediate risk (12.98%), and high risk (38.01%). The positive likelihood ratio for PPC among the highest risk group was 7.12. The C statistic for fit was 0.80. Observed PPC rates were higher than predicted for the low (3.39% vs 0.87%) and intermediate (12.98% vs 7.82%) risk groups.
Cautions
The calibration slopes were less than ideal in all subsamples, with the Western European sample performing better than the other geographic areas; suggesting that the coefficients on the ARISCAT index may benefit from recalibration to match specific populations.
Implications
This is the first major pulmonary risk index that has been externally validated. Its use of readily available clinical information, simplicity, and accuracy in estimating PPC risk make it an important addition to the toolkit during a preoperative evaluation.
PERIOPERATIVE ATRIAL FIBRILLATION/ANTICOAGULATION
Gialdini G, Nearing K, Bhave P, et al. Perioperative atrial fibrillation and the long term risk of ischemic stroke. JAMA. 2014;312(6):616622.
Background
New‐onset atrial fibrillation (AF) is the most common perioperative arrhythmia.[11] However, little is known regarding the long‐term risks of ischemic stroke in patients who develop perioperative AF. This retrospective cohort study examined adults with no preexisting history of AF, hospitalized for surgery, and discharged free of cerebrovascular disease between 2007 and 2011 (n=1,729,360).
Findings
Of the eligible patients, 1.43% (95% CI: 1.41%‐1.45%) developed perioperative AF, and 0.81% (95% CI: 0.79%‐0.82%) had a stroke up to 1 year after discharge. Perioperative AF was associated with subsequent stroke after both cardiac (HR: 1.3; 95% CI: 1.1‐1.6) and noncardiac surgery (HR: 2; 95% CI: 1.7‐2.3). The association with stroke was stronger for perioperative AF after noncardiac versus cardiac surgery (P<0.001 for interaction).
Cautions
This is a retrospective cohort study, using claims data to identify AF and stroke. Data on duration of the perioperative AF episodes or use of antithrombotic therapies were not available.
Implications
The association found between perioperative AF and long‐term risk of ischemic stroke may suggest that perioperative AF, especially after noncardiac surgery, should be treated aggressively in terms of thromboembolic risk; however, further data will be required to validate this association.
Van Diepen S, Youngson E, Ezekowitz J, McAlister F. Which risk score best predicts perioperative outcomes in nonvalvular atrial fibrillation patients undergoing noncardiac surgery? Am Heart J. 2014;168(1):6067.
Background
Patients with nonvalvular AF (NVAF) are at increased risk for adverse perioperative outcomes after noncardiac surgery.[12] The RCRI is commonly used to predict perioperative cardiovascular events for all patients, including those with NVAF, though AF is not part of this risk assessment. The goal of this retrospective cohort study was to examine the prognostic utility of already existing NVAF risk indices, including the CHADS2 (Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, prior stroke or transient ischemic attack), CHA2DS2‐VASc (Congestive heart failure; Hypertension; Age 75 years; Diabetes mellitus; Stroke, TIA, or thromboembolism [TE]; Vascular disease; Age 65 to 74 years; Sex category [female]), and R2CHADS2 (Renal dysfunction, Congestive heart failure, Hypertension, Age, Diabetes, Stroke/TIA) for perioperative outcomes in patients undergoing noncardiac surgery.
Findings
A population dataset of NVAF patients (n=32,160) who underwent noncardiac surgery was examined, with outcome measures including 30‐day mortality, stroke, TIA, or systemic embolism. The incidence of the 30‐day composite outcome was 4.2% and the C indices were 0.65 for the RCRI, 0.67 for CHADS2, 0.67 for CHA2DS2‐VASc, and 0.68 for R2CHADS2. The Net Reclassification Index (NRI), a measure evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors, was calculated. All NVAF scores performed better than the RCRI for predicting mortality risk (NRI: 12.3%, 8.4%, and 13.3% respectively, all P<0.01).
Cautions
Patients in the highest risk category by RCRI appear to have an unadjusted higher 30‐day mortality risk (8%) than that predicted by the other 3 scores (5%, 5.6%, and 5%), indicating that these risk scores should not completely supplant the RCRI for risk stratification in this population. In addition, the overall improvement in predictive capacity of the CHADS2, CHA2DS2‐VASc, and R2CHADS2, although superior to the RCRI, is modest.
Implications
These findings indicate that the preoperative risk stratification for patients with NVAF can be improved by utilizing the CHADS2, CHA2DS2‐VASc, or R2CHADS2 scores when undergoing noncardiac surgery. For patients with NVAF identified as high risk for adverse outcomes, this assessment can be integrated into the preoperative discussion on the risks/benefits of surgery.
Steinberg BA, Peterson ED, Kim S, et al. Use and outcomes associated with bridging during anticoagulation interruptions in patients with atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT‐AF). Circulation. 2015;131:488494
Background
Oral anticoagulation (OAC) significantly reduces the risk of stroke in patients with AF. Many AF patients on long‐term anticoagulation undergo procedures requiring temporary interruption of OAC. Although guidelines have been published on when and how to initiate bridging therapy, they are based on observational data. Thus, it remains unclear which patients should receive bridging anticoagulation.
Findings
This is a US registry of outpatients with AF with temporary interruptions of OAC for a procedure. Of 7372 patients treated with OAC, 2803 overall interruption events occurred in 2200 patients (30%). Bridging anticoagulants were used in 24% (n=665). Bleeding events were more common in bridged than nonbridged patients (5.0% vs 1.3%; adjusted OR: 3.84; P<0.0001). The overall composite end point of myocardial infarction, stroke or systemic embolism, major bleeding, hospitalization, or death within 30 days was significantly higher in patients receiving bridging (13% vs 6.3%; adjusted OR: 1.94; P=0.0001). This statistically significant increase in the composite outcome, which includes cardiovascular events, is most likely in part secondary to inclusion of bleeding events. The recently published BRIDGE (Bridging Anticoagulation in Patients who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery) trial did not find a statistically significant difference in cardiovascular events between bridged and nonbridged patients.[13]
Cautions
Although patients who were bridged appear to have had more comorbidities and a higher mean CHADS2 score than patients who were not bridged, it is difficult to determine which population of patients may be high risk enough to warrant bridging, as indicated by current American College of Chest Physicians guidelines, as this was not evaluated in this study
Implications
The use of bridging anticoagulation was significantly associated with higher overall bleeding and adverse event rates. The BRIDGE trial also found that forgoing bridging anticoagulation decreased the risk of major bleeding in patients with AF and was noninferior to bridging for the prevention of arterial TE.[13]
Given the rapid expansion of the field of perioperative medicine, clinicians need to remain apprised of the current evidence to ensure optimization of patient care. In this update, we review 10 key articles from the perioperative literature, with the goal of summarizing the most clinically important evidence over the past year. This summary of recent literature in perioperative medicine is derived from the Update in Perioperative Medicine sessions presented at the 10th Annual Perioperative Medicine Summit and the Society of General Internal Medicine 38th Annual Meeting. A systematic search strategy was used to identify pertinent articles, and the following were selected by the authors based on their relevance to the clinical practice of perioperative medicine.
PERIOPERATIVE CARDIOVASCULAR CARE
Fleisher LA, Fleischmann KE, Auerbach AD, et al. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. Circulation. 2014;130:e278e333.
Background
The American College of Cardiology/American Heart Association (ACC/AHA) perioperative guideline provides recommendations for the evaluation and management of cardiovascular disease in patients undergoing noncardiac surgery.
Findings
The new guideline combines the evaluation of surgery‐ and patient‐specific risk in the algorithm for preoperative cardiovascular evaluation into a single step and recommends the use of 1 of 3 tools: the Revised Cardiac Risk Index (RCRI),[1] National Surgical Quality Improvement Program (NSQIP) Surgical Risk Calculator,[2] or the NSQIP‐derived myocardial infarction and cardiac arrest calculator.[3] Estimation of risk is also simplified by stratification into only 2 groups: low risk (risk of major adverse cardiac event <1%) and elevated risk (1% risk). Coronary evaluation can be considered for patients with elevated cardiac risk and poor functional capacity, but is advised only if the results would alter perioperative management. For example, a patient with very high risk who has evidence of ischemia on stress testing may choose to forego surgery. Preoperative coronary revascularization is only indicated for patients meeting criteria in the nonsurgical setting.
For patients with previous percutaneous coronary intervention, the ACC/AHA has not changed its recommendations to optimally delay surgery for at least 30 days after bare‐metal stenting and at least 1 year after drug‐eluting stent (DES) placement. However, in patients with a DES placed 6 to 12 months previously, surgery can be performed if the risks of surgical delay outweigh the risks of DES thrombosis. After any type of coronary stenting, dual antiplatelet therapy should be continued uninterrupted through the first 4 to 6 weeks and even later whenever feasible. If not possible, aspirin therapy should be maintained through surgery unless bleeding risk is too high.
The guideline recommends perioperative continuation of ‐blockers in patients taking them chronically. Preoperative initiation of ‐blocker therapy may be considered for patients with myocardial ischemia on stress testing or 3 RCRI factors and should be started far enough in advance to allow determination of patient's tolerance prior to surgery.
Cautions
Many recommendations are based on data from nonrandomized trials or expert opinion, and the data in areas such as perioperative ‐blockade continue to evolve.
Implications
The ACC/AHA guideline continues to be a critically valuable resource for hospitalists providing perioperative care to noncardiac surgery patients.
Wijeysundera DN, Duncan D, Nkonde‐Price C, et al. Perioperative beta blockade in noncardiac surgery: a systematic review for the 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines.
J Am Coll Cardiol. 2014;64(22):24062425.
Background
Various clinical trials have reported conflicting results regarding the efficacy and safety of perioperative ‐blockers resulting in guideline committees changing their recommendations. Because of questions raised regarding the scientific integrity of the DECREASE (Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography)‐I[4] and DECREASE‐IV[5] trials as well as the dosing of ‐blockers in POISE (PeriOperative Ischemic Evaluation) study,[6] this systematic review was performed in conjunction with the ACC/AHA guideline update[7] to evaluate the data with and without these trials.
Findings
Sixteen randomized control trials (RCTs) (n=12,043) and 1 cohort study (n=348) were included in the analysis. Perioperative ‐blockers were associated with a reduction in nonfatal myocardial infarction (MI) (relative risk [RR]: 0.69; 95% confidence interval [CI]: 0.58‐0.82; P<0.001) but an increase in bradycardia (RR: 2.61; 95% CI: 2.18‐3.12), hypotension (RR: 1.47; 95% CI: 1.34‐1.6), and nonfatal strokes (RR: 1.76; 95% CI: 1.07‐2.91; P=0.02). The POISE trial was the only one demonstrating a statistically significant increase in stroke.
The major discrepancy between the DECREASE trials and the other RCTs was related to mortalitya reduction in both cardiovascular and all‐cause death in DECREASE but an increased risk of all‐cause death in the other trials.
Cautions
Because of its size, the POISE trial heavily influences the results, particularly for mortality and stroke. Including the DECREASE trials reduces the otherwise increased risk for death to a null effect. Exclusion of the POISE and DECREASE trials leaves few data to make conclusions about safety and efficacy of perioperative ‐blockade. Several cohort studies have found metoprolol to be associated with worse outcomes than with atenolol or bisoprolol (which were preferred by the European Society of Cardiology guidelines).[8]
Implications
Perioperative ‐blockade started within 1 day of noncardiac surgery was associated with fewer nonfatal MIs but at the cost of an increase in hypotension, bradycardia, and a possible increase in stroke and death. Long‐term ‐blockade should be continued perioperatively, whereas the decision to initiate a ‐blocker should be individualized. If starting a ‐blocker perioperatively, it should be done 2 days before surgery.
Botto F, Alonso‐Coello P, Chan MT, et al.; on behalf of The Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) Investigators. Myocardial injury after noncardiac surgery: a large, international, prospective cohort study establishing diagnostic criteria, characteristics, predictors, and 30‐day outcomes. Anesthesiology. 2014;120(3):564578.
Background
Many patients sustain myocardial injury in the perioperative period as evidenced by troponin elevations, but most do not meet diagnostic criteria for MI. Myocardial injury after noncardiac surgery (MINS) is defined as prognostically relevant myocardial injury due to ischemia that occurs within 30 days after noncardiac surgery. This international, prospective cohort study of 15,065 patients 45 years old who underwent in‐patient noncardiac surgery determined diagnostic criteria, characteristics, predictors, and 30‐day outcomes of MINS.
Findings
The diagnostic criterion for MINS was a peak troponin T level 0.03 ng/mL judged to be due to an ischemic etiology. Twelve independent predictors of MINS were identified including age 75 years, known cardiovascular disease or risk factors, and surgical factors. MINS was an independent predictor of 30‐day mortality (adjusted hazard ratio [HR]: 3.87; 95% CI: 2.96‐5.08). Age >75 years, ST elevation, or new left bundle branch block, and anterior ischemic findings were independent predictors of 30‐day mortality among patients with MINS.
Cautions
Although screening high‐risk surgical patients without signs or symptoms of ischemia with postoperative troponins will increase the frequency of diagnosing MINS, evidence for an effective treatment has not yet been established. The ACC/AHA guidelines state that routine screening is of uncertain benefit for this reason.
Implications
Because MINS is common and carries a poor 30‐day prognosis, clinical trials are needed to determine when to obtain postoperative troponins and how to prevent and treat this complication.[9] Some observational data from POISE suggest that aspirin and statins can reduce the risk of 30‐day mortality in patients with postoperative MIs.
Devereaux PJ, Mrkobrada M, Sessler DI, et al. for the POISE‐2 Investigators. Aspirin in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):14941503.
Devereaux PJ, Sessler DI, Leslie K, et al. for the POISE‐2 Investigators. Clonidine in patients undergoing noncardiac surgery. N Engl J Med. 2014; 370(16):15041513.
Background
Medical risk reduction with aspirin and other agents in perioperative patients remains controversial. The POISE‐2 trial is a blinded RCT examining the effects of aspirin and clonidine on outcomes in >10,000 noncardiac surgery patients at risk of cardiovascular complications. The aspirin arm of the study included the initiation group and the continuation stratum, as well as placebo. Patients in the clonidine portion of the trial received 0.2 mg of clonidine or placebo daily for the same time periods.
Findings
The primary outcome was a composite of death or nonfatal MI within 30 days of surgery. Outcomes were similar in patients initiated or continued on aspirin. No difference was seen between aspirin or placebo in the primary outcome (7.0% vs 7.1%; HR: 0.86; 95% CI: 0.86‐1.15; P=0.92). There were no differences in rates of MI, venous thromboembolism, or stroke. Major bleeding rates were higher in aspirin versus placebo‐treated patients (4.6% vs 3.8%; HR: 1.23; 95% CI: 1.01‐1.49; P=0.04).
Clonidine did not alter the composite outcome of death or nonfatal MI (7.3% vs 6.8%; HR: 1.08; 95% CI: 0.93‐1.26; P=0.29). Clinically significant hypotension, bradycardia, and nonfatal cardiac arrest were more common in clonidine‐treated patients, although no difference was detected in stroke rates.
Cautions
Although patients in the trial had cardiovascular risk factors, <24% of patients had known coronary artery disease, and <5% had coronary stents. Conclusions based on this trial regarding perioperative management of antiplatelet therapy should not include patients with coronary artery stents.
Implications
Aspirin started before surgery and continued perioperatively did not decrease the rate of death or nonfatal MI but increased the risk of major bleeding. Perioperative management of aspirin needs to be undertaken in the context of cardiac and bleeding risks. Clonidine also did not improve outcomes and increased the risk of bradycardia and hypotension. Current guidelines recommend against using alpha‐2 agonists for prevention of perioperative cardiac events7; however, patients already on alpha‐2 agonists should not stop them abruptly.
PERIOPERATIVE PULMONARY CARE
Mutter TC, Chateau D, Moffatt M, et al. A matched cohort study of postoperative outcomes in obstructive sleep apnea: could preoperative diagnosis and treatment prevent complications? Anesthesiology. 2014;121(4):707718.
Background
An increasing body of literature associates obstructive sleep apnea (OSA) with an increased risk of postoperative complications. Despite evidence of risk, potential benefits of preoperative diagnosis and treatment of OSA remain unclear.
Findings
Using databases to identify patients prescribed continuous positive airway pressure (CPAP) therapy, the study compared postoperative outcomes of patients who underwent surgery any time after polysomnography (PSG) and CPAP prescription (diagnosed OSA [DOSA]) and those who had surgery during the 5 years preceding their PSG (undiagnosed OSA [UOSA]). These patients were matched with patients who underwent the same procedure for the same indication and had no insurance claims for PSG or diagnosis of sleep‐disordered breathing.
After multivariate analysis, OSA of any type was associated with increased pulmonary complications (odds ratio [OR]: 2.08; 95% CI: 1.35‐2.19). However, no significant differences in respiratory outcomes were noted between DOSA patients (N=2640) and those with UOSA (N=1571). DOSA patients did have fewer cardiovascular complications than UOSA patients (OR: 0.34; 95% CI: 0.15‐0.77). Only severe OSA (apnea‐hypopnea index >30) was associated with increased pulmonary and cardiovascular complications.
Cautions
Although this study suggests an association between preoperative diagnosis and treatment of OSA and reduced cardiovascular complications, the results are not definitive due to the inability to control for all confounding variables in a retrospective study utilizing an administrative database.
Implications
OSA is an important risk factor for postoperative complications, and this study suggests that preoperative treatment with CPAP is associated with reduced risk of cardiovascular complications, particularly in patients with severe OSA. Future controlled trials should focus on the risk‐reduction potential of preoperative diagnosis and treatment of OSA.
Mazo V, Sabat S, Canet J, et al. Prospective external validation of a predictive score for postoperative pulmonary complications. Anesthesiology. 2014;121:219231.
Background
In 2010, Canet et al. published a novel risk index, the Assess Respiratory Risk in Surgical Patients in Catalonia (ARISCAT) index, to provide a quantitative estimate of the risk of postoperative pulmonary complications (PPCs).[10]
In the current report, Mazo and colleagues studied the ARISCAT index in a broader sample to characterize its accuracy in predicting PPC risk. The ARISCAT index is derived from clinical risk factors: (1) age, (2) preoperative oxygen saturation, (3) respiratory infection in the prior month, (4) anemia, (5) surgical site, (6) duration of surgery, and (7) emergency surgery, with varying weights based on the strength of the association in a multivariable analysis. This score can be calculated via addition of these weighted risk factors, with a score>45 equal to high risk for PPC.
Findings
Examining 5099 patients from 63 European hospitals, the authors definition of PPC included respiratory failure, pulmonary infection, pleural effusion, atelectasis, pneumothorax, bronchospasm, and aspiration pneumonitis. PPC rates were as follows: low risk (3.39%), intermediate risk (12.98%), and high risk (38.01%). The positive likelihood ratio for PPC among the highest risk group was 7.12. The C statistic for fit was 0.80. Observed PPC rates were higher than predicted for the low (3.39% vs 0.87%) and intermediate (12.98% vs 7.82%) risk groups.
Cautions
The calibration slopes were less than ideal in all subsamples, with the Western European sample performing better than the other geographic areas; suggesting that the coefficients on the ARISCAT index may benefit from recalibration to match specific populations.
Implications
This is the first major pulmonary risk index that has been externally validated. Its use of readily available clinical information, simplicity, and accuracy in estimating PPC risk make it an important addition to the toolkit during a preoperative evaluation.
PERIOPERATIVE ATRIAL FIBRILLATION/ANTICOAGULATION
Gialdini G, Nearing K, Bhave P, et al. Perioperative atrial fibrillation and the long term risk of ischemic stroke. JAMA. 2014;312(6):616622.
Background
New‐onset atrial fibrillation (AF) is the most common perioperative arrhythmia.[11] However, little is known regarding the long‐term risks of ischemic stroke in patients who develop perioperative AF. This retrospective cohort study examined adults with no preexisting history of AF, hospitalized for surgery, and discharged free of cerebrovascular disease between 2007 and 2011 (n=1,729,360).
Findings
Of the eligible patients, 1.43% (95% CI: 1.41%‐1.45%) developed perioperative AF, and 0.81% (95% CI: 0.79%‐0.82%) had a stroke up to 1 year after discharge. Perioperative AF was associated with subsequent stroke after both cardiac (HR: 1.3; 95% CI: 1.1‐1.6) and noncardiac surgery (HR: 2; 95% CI: 1.7‐2.3). The association with stroke was stronger for perioperative AF after noncardiac versus cardiac surgery (P<0.001 for interaction).
Cautions
This is a retrospective cohort study, using claims data to identify AF and stroke. Data on duration of the perioperative AF episodes or use of antithrombotic therapies were not available.
Implications
The association found between perioperative AF and long‐term risk of ischemic stroke may suggest that perioperative AF, especially after noncardiac surgery, should be treated aggressively in terms of thromboembolic risk; however, further data will be required to validate this association.
Van Diepen S, Youngson E, Ezekowitz J, McAlister F. Which risk score best predicts perioperative outcomes in nonvalvular atrial fibrillation patients undergoing noncardiac surgery? Am Heart J. 2014;168(1):6067.
Background
Patients with nonvalvular AF (NVAF) are at increased risk for adverse perioperative outcomes after noncardiac surgery.[12] The RCRI is commonly used to predict perioperative cardiovascular events for all patients, including those with NVAF, though AF is not part of this risk assessment. The goal of this retrospective cohort study was to examine the prognostic utility of already existing NVAF risk indices, including the CHADS2 (Congestive heart failure, Hypertension, Age 75 years, Diabetes mellitus, prior stroke or transient ischemic attack), CHA2DS2‐VASc (Congestive heart failure; Hypertension; Age 75 years; Diabetes mellitus; Stroke, TIA, or thromboembolism [TE]; Vascular disease; Age 65 to 74 years; Sex category [female]), and R2CHADS2 (Renal dysfunction, Congestive heart failure, Hypertension, Age, Diabetes, Stroke/TIA) for perioperative outcomes in patients undergoing noncardiac surgery.
Findings
A population dataset of NVAF patients (n=32,160) who underwent noncardiac surgery was examined, with outcome measures including 30‐day mortality, stroke, TIA, or systemic embolism. The incidence of the 30‐day composite outcome was 4.2% and the C indices were 0.65 for the RCRI, 0.67 for CHADS2, 0.67 for CHA2DS2‐VASc, and 0.68 for R2CHADS2. The Net Reclassification Index (NRI), a measure evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors, was calculated. All NVAF scores performed better than the RCRI for predicting mortality risk (NRI: 12.3%, 8.4%, and 13.3% respectively, all P<0.01).
Cautions
Patients in the highest risk category by RCRI appear to have an unadjusted higher 30‐day mortality risk (8%) than that predicted by the other 3 scores (5%, 5.6%, and 5%), indicating that these risk scores should not completely supplant the RCRI for risk stratification in this population. In addition, the overall improvement in predictive capacity of the CHADS2, CHA2DS2‐VASc, and R2CHADS2, although superior to the RCRI, is modest.
Implications
These findings indicate that the preoperative risk stratification for patients with NVAF can be improved by utilizing the CHADS2, CHA2DS2‐VASc, or R2CHADS2 scores when undergoing noncardiac surgery. For patients with NVAF identified as high risk for adverse outcomes, this assessment can be integrated into the preoperative discussion on the risks/benefits of surgery.
Steinberg BA, Peterson ED, Kim S, et al. Use and outcomes associated with bridging during anticoagulation interruptions in patients with atrial fibrillation: findings from the Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT‐AF). Circulation. 2015;131:488494
Background
Oral anticoagulation (OAC) significantly reduces the risk of stroke in patients with AF. Many AF patients on long‐term anticoagulation undergo procedures requiring temporary interruption of OAC. Although guidelines have been published on when and how to initiate bridging therapy, they are based on observational data. Thus, it remains unclear which patients should receive bridging anticoagulation.
Findings
This is a US registry of outpatients with AF with temporary interruptions of OAC for a procedure. Of 7372 patients treated with OAC, 2803 overall interruption events occurred in 2200 patients (30%). Bridging anticoagulants were used in 24% (n=665). Bleeding events were more common in bridged than nonbridged patients (5.0% vs 1.3%; adjusted OR: 3.84; P<0.0001). The overall composite end point of myocardial infarction, stroke or systemic embolism, major bleeding, hospitalization, or death within 30 days was significantly higher in patients receiving bridging (13% vs 6.3%; adjusted OR: 1.94; P=0.0001). This statistically significant increase in the composite outcome, which includes cardiovascular events, is most likely in part secondary to inclusion of bleeding events. The recently published BRIDGE (Bridging Anticoagulation in Patients who Require Temporary Interruption of Warfarin Therapy for an Elective Invasive Procedure or Surgery) trial did not find a statistically significant difference in cardiovascular events between bridged and nonbridged patients.[13]
Cautions
Although patients who were bridged appear to have had more comorbidities and a higher mean CHADS2 score than patients who were not bridged, it is difficult to determine which population of patients may be high risk enough to warrant bridging, as indicated by current American College of Chest Physicians guidelines, as this was not evaluated in this study
Implications
The use of bridging anticoagulation was significantly associated with higher overall bleeding and adverse event rates. The BRIDGE trial also found that forgoing bridging anticoagulation decreased the risk of major bleeding in patients with AF and was noninferior to bridging for the prevention of arterial TE.[13]
- , , , et al. Derivation and prospective evaluation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100:1043–1049.
- , , , et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833–842.
- , , , et al. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation. 2011;124:381–387.
- , , , et al. The effect of bisoprolol on perioperative mortality and myocardial infarction in high‐risk patients undergoing vascular surgery. Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. N Engl J Med. 1999;341(24):1789–1794.
- , , , et al; Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. Bisoprolol and fluvastatin for the reduction of perioperative cardiac mortality and myocardial infarction in intermediate‐risk patients undergoing noncardiovascular surgery: a randomized controlled trial (DECREASE‐IV). Ann Surg. 2009;249(6):921–926.
- POISE Study Group, , , , et al. Effects of extended‐release metoprolol succinate in patients undergoing non‐cardiac surgery (POISE trial): a randomised controlled trial. Lancet. 2008;371(9627):1839–1847.
- , , , et al. American College of Cardiology; American Heart Association. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol. 2014;64(22):e77–e137.
- , , , et al. 2014 ESC/ESA Guidelines on non‐cardiac surgery: cardiovascular assessment and management: The Joint Task Force on non‐cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur Heart J. 2014;35(35):2383–431.
- , , , et al. The long‐term impact of early cardiovascular therapy intensification for postoperative troponin elevation after major vascular surgery. Anesth Analg. 2014;119(5):1053–1063.
- , , , et al. ARISCAT Group: Prediction of postoperative pulmonary complications in a population‐based surgical cohort. Anesthesiology. 2010;113:1338–1350.
- , . Noncardiac surgery: postoperative arrhythmias. Crit Care Med. 2000;28(10 suppl):N145–N150.
- , , , et al. Incidence, predictors, and outcomes associated with postoperative atrial fibrillation after major cardiac surgery. Am Heart J. 2012;164(6):918–924.
- , , , et al. Perioperative bridging anticoagulation in patients with atrial fibrillation. N Engl J Med. 2015;373(9):823–833.
- , , , et al. Derivation and prospective evaluation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation. 1999;100:1043–1049.
- , , , et al. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons. J Am Coll Surg. 2013;217(5):833–842.
- , , , et al. Development and validation of a risk calculator for prediction of cardiac risk after surgery. Circulation. 2011;124:381–387.
- , , , et al. The effect of bisoprolol on perioperative mortality and myocardial infarction in high‐risk patients undergoing vascular surgery. Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. N Engl J Med. 1999;341(24):1789–1794.
- , , , et al; Dutch Echocardiographic Cardiac Risk Evaluation Applying Stress Echocardiography Study Group. Bisoprolol and fluvastatin for the reduction of perioperative cardiac mortality and myocardial infarction in intermediate‐risk patients undergoing noncardiovascular surgery: a randomized controlled trial (DECREASE‐IV). Ann Surg. 2009;249(6):921–926.
- POISE Study Group, , , , et al. Effects of extended‐release metoprolol succinate in patients undergoing non‐cardiac surgery (POISE trial): a randomised controlled trial. Lancet. 2008;371(9627):1839–1847.
- , , , et al. American College of Cardiology; American Heart Association. 2014 ACC/AHA guideline on perioperative cardiovascular evaluation and management of patients undergoing noncardiac surgery: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. J Am Coll Cardiol. 2014;64(22):e77–e137.
- , , , et al. 2014 ESC/ESA Guidelines on non‐cardiac surgery: cardiovascular assessment and management: The Joint Task Force on non‐cardiac surgery: cardiovascular assessment and management of the European Society of Cardiology (ESC) and the European Society of Anaesthesiology (ESA). Eur Heart J. 2014;35(35):2383–431.
- , , , et al. The long‐term impact of early cardiovascular therapy intensification for postoperative troponin elevation after major vascular surgery. Anesth Analg. 2014;119(5):1053–1063.
- , , , et al. ARISCAT Group: Prediction of postoperative pulmonary complications in a population‐based surgical cohort. Anesthesiology. 2010;113:1338–1350.
- , . Noncardiac surgery: postoperative arrhythmias. Crit Care Med. 2000;28(10 suppl):N145–N150.
- , , , et al. Incidence, predictors, and outcomes associated with postoperative atrial fibrillation after major cardiac surgery. Am Heart J. 2012;164(6):918–924.
- , , , et al. Perioperative bridging anticoagulation in patients with atrial fibrillation. N Engl J Med. 2015;373(9):823–833.
Pediatric Admission and Readmission
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
Enhancing Dermatology Education: Resident Presentation Opportunities
Dermatology residency is busy with 3 years of clinical duties, academic responsibilities, and administrative work. In addition, it is a time to maximize educational experiences in dermatology from didactics to hands-on learning. It also is a time to take advantage of special opportunities that are available to residents, including attending academic meetings and giving oral and/or poster presentations. Major dermatology conferences often have designated sessions for residents that provide an excellent chance for residents to share interesting cases or present their research. This article provides a review of selected presentation opportunities available to residents at the major academic dermatology meetings.
American Academy of Dermatology
The Annual Meeting of the American Academy of Dermatology (AAD) accepts abstracts for oral presentation from both residents and fellows for its “Residents and Fellows Symposium” and “Gross and Microscopic Symposium.” The “Residents and Fellows Symposium” is an opportunity to present either clinical or laboratory research in a 9-minute oral format. Up to 20 abstracts are chosen for presentation along with 4 alternate abstracts. Furthermore, awards are given to the top 3 abstracts in both the clinical and laboratory categories. Those accepted for the “Gross and Microscopic Symposium” give a 5-minute oral presentation of a case with interesting clinical and histopathological findings. Submission guidelines for these presentations are available on the AAD Web site (https://www.aad.org/symposium/am2016).
Residents and fellows also are eligible to submit abstracts for the AAD’s electronic poster exhibits and presentations. The posters are presented electronically and are displayed and/or are available to be viewed throughout the meeting. The abstracts are blind reviewed by the Poster Exhibits Task Force on a scale from 1 (unsatisfactory) to 10 (outstanding). Presenters with abstracts that receive a passing score (2.5 or higher) by judges are allowed to discuss their poster in a live 5-minute oral presentation.
The AAD’s Summer Academy Meeting, which also takes place annually, does not have separate resident-specific poster or oral presentation sessions; however, it does offer an electronic poster exhibit and presentation session.
Pediatric Dermatology
The Annual Meeting of the Society for Pediatric Dermatology (https://pedsderm.net/meetings/annual-meeting/) accepts abstract submissions for its “Cases of the Year” session as well as poster presentations. Residents, medical students, and fellows who are chosen for a “Cases of the Year” or poster presentation are eligible for a travel award that is available on a competitive basis. The American Academy of Pediatrics’ Section on Dermatology also offers an additional travel award for a resident or fellow who presents a case or poster at the Annual Meeting of the Society for Pediatric Dermatology.
American Society for Dermatologic Surgery
The American Society for Dermatologic Surgery has an Annual Meeting (https://www.asds.net/ annualmeeting/) that includes a competitive “Resident Oral Abstracts” session. If selected, residents give a 5-minute presentation and abstracts are published in the Annual Meeting program book.
American Society of Dermatopathology
The American Society of Dermatopathology Annual Meeting has several opportunities for residents and fellows to present abstracts (https://www.asdp.org/meetings-events/annual-meeting/52nd/call-for -abtracts/). Submissions to the “General Abstracts” category are selected for either oral or poster presentation. Ambitious dermatology or pathology residents may choose to submit their case report abstracts to the “Duel in Dermatopathology” competition, which includes an oral presentation and publication of abstracts in the meeting program book. Finally, the “Dermatopathology Fellows Abstract” category is a special category for dermatopathology fellows to present an oral or poster presentation. Any resident or fellow who is accepted for oral or poster presentations is eligible for a “Physician-in-Training Award” (except winners of the “Duel in Dermatopathology” competition), which are granted to the best oral and poster presentations.
Conclusion
Beyond dermatology residency, there are many opportunities for resident education through attendance at academic meetings as well as presentation of case reports and research. The major dermatology meetings often have specific sessions to give residents a chance to share their work or interesting cases. This guide may be helpful to residents who are hoping for such venues to enhance their education and even their curriculum vitae.
Dermatology residency is busy with 3 years of clinical duties, academic responsibilities, and administrative work. In addition, it is a time to maximize educational experiences in dermatology from didactics to hands-on learning. It also is a time to take advantage of special opportunities that are available to residents, including attending academic meetings and giving oral and/or poster presentations. Major dermatology conferences often have designated sessions for residents that provide an excellent chance for residents to share interesting cases or present their research. This article provides a review of selected presentation opportunities available to residents at the major academic dermatology meetings.
American Academy of Dermatology
The Annual Meeting of the American Academy of Dermatology (AAD) accepts abstracts for oral presentation from both residents and fellows for its “Residents and Fellows Symposium” and “Gross and Microscopic Symposium.” The “Residents and Fellows Symposium” is an opportunity to present either clinical or laboratory research in a 9-minute oral format. Up to 20 abstracts are chosen for presentation along with 4 alternate abstracts. Furthermore, awards are given to the top 3 abstracts in both the clinical and laboratory categories. Those accepted for the “Gross and Microscopic Symposium” give a 5-minute oral presentation of a case with interesting clinical and histopathological findings. Submission guidelines for these presentations are available on the AAD Web site (https://www.aad.org/symposium/am2016).
Residents and fellows also are eligible to submit abstracts for the AAD’s electronic poster exhibits and presentations. The posters are presented electronically and are displayed and/or are available to be viewed throughout the meeting. The abstracts are blind reviewed by the Poster Exhibits Task Force on a scale from 1 (unsatisfactory) to 10 (outstanding). Presenters with abstracts that receive a passing score (2.5 or higher) by judges are allowed to discuss their poster in a live 5-minute oral presentation.
The AAD’s Summer Academy Meeting, which also takes place annually, does not have separate resident-specific poster or oral presentation sessions; however, it does offer an electronic poster exhibit and presentation session.
Pediatric Dermatology
The Annual Meeting of the Society for Pediatric Dermatology (https://pedsderm.net/meetings/annual-meeting/) accepts abstract submissions for its “Cases of the Year” session as well as poster presentations. Residents, medical students, and fellows who are chosen for a “Cases of the Year” or poster presentation are eligible for a travel award that is available on a competitive basis. The American Academy of Pediatrics’ Section on Dermatology also offers an additional travel award for a resident or fellow who presents a case or poster at the Annual Meeting of the Society for Pediatric Dermatology.
American Society for Dermatologic Surgery
The American Society for Dermatologic Surgery has an Annual Meeting (https://www.asds.net/ annualmeeting/) that includes a competitive “Resident Oral Abstracts” session. If selected, residents give a 5-minute presentation and abstracts are published in the Annual Meeting program book.
American Society of Dermatopathology
The American Society of Dermatopathology Annual Meeting has several opportunities for residents and fellows to present abstracts (https://www.asdp.org/meetings-events/annual-meeting/52nd/call-for -abtracts/). Submissions to the “General Abstracts” category are selected for either oral or poster presentation. Ambitious dermatology or pathology residents may choose to submit their case report abstracts to the “Duel in Dermatopathology” competition, which includes an oral presentation and publication of abstracts in the meeting program book. Finally, the “Dermatopathology Fellows Abstract” category is a special category for dermatopathology fellows to present an oral or poster presentation. Any resident or fellow who is accepted for oral or poster presentations is eligible for a “Physician-in-Training Award” (except winners of the “Duel in Dermatopathology” competition), which are granted to the best oral and poster presentations.
Conclusion
Beyond dermatology residency, there are many opportunities for resident education through attendance at academic meetings as well as presentation of case reports and research. The major dermatology meetings often have specific sessions to give residents a chance to share their work or interesting cases. This guide may be helpful to residents who are hoping for such venues to enhance their education and even their curriculum vitae.
Dermatology residency is busy with 3 years of clinical duties, academic responsibilities, and administrative work. In addition, it is a time to maximize educational experiences in dermatology from didactics to hands-on learning. It also is a time to take advantage of special opportunities that are available to residents, including attending academic meetings and giving oral and/or poster presentations. Major dermatology conferences often have designated sessions for residents that provide an excellent chance for residents to share interesting cases or present their research. This article provides a review of selected presentation opportunities available to residents at the major academic dermatology meetings.
American Academy of Dermatology
The Annual Meeting of the American Academy of Dermatology (AAD) accepts abstracts for oral presentation from both residents and fellows for its “Residents and Fellows Symposium” and “Gross and Microscopic Symposium.” The “Residents and Fellows Symposium” is an opportunity to present either clinical or laboratory research in a 9-minute oral format. Up to 20 abstracts are chosen for presentation along with 4 alternate abstracts. Furthermore, awards are given to the top 3 abstracts in both the clinical and laboratory categories. Those accepted for the “Gross and Microscopic Symposium” give a 5-minute oral presentation of a case with interesting clinical and histopathological findings. Submission guidelines for these presentations are available on the AAD Web site (https://www.aad.org/symposium/am2016).
Residents and fellows also are eligible to submit abstracts for the AAD’s electronic poster exhibits and presentations. The posters are presented electronically and are displayed and/or are available to be viewed throughout the meeting. The abstracts are blind reviewed by the Poster Exhibits Task Force on a scale from 1 (unsatisfactory) to 10 (outstanding). Presenters with abstracts that receive a passing score (2.5 or higher) by judges are allowed to discuss their poster in a live 5-minute oral presentation.
The AAD’s Summer Academy Meeting, which also takes place annually, does not have separate resident-specific poster or oral presentation sessions; however, it does offer an electronic poster exhibit and presentation session.
Pediatric Dermatology
The Annual Meeting of the Society for Pediatric Dermatology (https://pedsderm.net/meetings/annual-meeting/) accepts abstract submissions for its “Cases of the Year” session as well as poster presentations. Residents, medical students, and fellows who are chosen for a “Cases of the Year” or poster presentation are eligible for a travel award that is available on a competitive basis. The American Academy of Pediatrics’ Section on Dermatology also offers an additional travel award for a resident or fellow who presents a case or poster at the Annual Meeting of the Society for Pediatric Dermatology.
American Society for Dermatologic Surgery
The American Society for Dermatologic Surgery has an Annual Meeting (https://www.asds.net/ annualmeeting/) that includes a competitive “Resident Oral Abstracts” session. If selected, residents give a 5-minute presentation and abstracts are published in the Annual Meeting program book.
American Society of Dermatopathology
The American Society of Dermatopathology Annual Meeting has several opportunities for residents and fellows to present abstracts (https://www.asdp.org/meetings-events/annual-meeting/52nd/call-for -abtracts/). Submissions to the “General Abstracts” category are selected for either oral or poster presentation. Ambitious dermatology or pathology residents may choose to submit their case report abstracts to the “Duel in Dermatopathology” competition, which includes an oral presentation and publication of abstracts in the meeting program book. Finally, the “Dermatopathology Fellows Abstract” category is a special category for dermatopathology fellows to present an oral or poster presentation. Any resident or fellow who is accepted for oral or poster presentations is eligible for a “Physician-in-Training Award” (except winners of the “Duel in Dermatopathology” competition), which are granted to the best oral and poster presentations.
Conclusion
Beyond dermatology residency, there are many opportunities for resident education through attendance at academic meetings as well as presentation of case reports and research. The major dermatology meetings often have specific sessions to give residents a chance to share their work or interesting cases. This guide may be helpful to residents who are hoping for such venues to enhance their education and even their curriculum vitae.
New atypical antipsychotic FDA approved for use in bipolar I and schizophrenia
The Food and Drug Administration on Sept. 17 approved cariprazine, an atypical antipsychotic, for the acute treatment of manic or mixed episodes in bipolar I disorder and schizophrenia in adults.
Results from three separate controlled trials in adults with manic or mixed episodes of bipolar I disorder showed cariprazine (Vraylar) was associated with improved total scores on the Young Mania Rating Scale (YMRS), compared with placebo. In three separate placebo-controlled trials in adults with schizophrenia, the study drug was associated with improvements in Positive and Negative Syndrome Scale (PANSS) total scores, compared with placebo. Cariprazine also demonstrated efficacy in the Clinical Global Impressions–Severity (CGI-S) rating scale, which was the secondary efficacy endpoint in the respective trials for each condition. In all, 2,700 persons were enrolled in the trials.
The recommended dose of cariprazine in adults with bipolar I is once daily at 3-6 mg per day. For schizophrenia in adults, 1.5-6 mg/day is the recommended dose.
Adverse reactions occurring in at least 5% of the study population and at a rate of twice that in the placebo groups were extrapyramidal symptoms, akathisia, dyspepsia, vomiting, somnolence, and restlessness in the bipolar group. In the group with schizophrenia, the most commonly reported adverse events were extrapyramidal symptoms and akathisia.
Cariprazine is a dopamine-2 and dopamine-3 receptor partial agonist, tending toward the D3 receptor. Although its mechanism of action in schizophrenia and bipolar I disorder is unknown, the drug’s codeveloper, Gedeon Richter said in a statement that cariprazine’s efficacy “could be mediated through a combination of partial agonist activity at central D2 and serotonin 5-HT1A receptors and antagonist activity at serotonin 5-HT2A receptors.” In the United States and Canada, the drug is licensed to Actavis, now Allergan. Vraylar is manufactured by Forest Laboratories.
Data indicating the drug’s ability to improve flat affect in schizophrenia were presented at this year’s annual congress of the European College of Neuropsychopharmacology in Amsterdam. According to Gedeon Richter and Allergan, cariprazine also is being investigated for the treatment of bipolar depression and as adjunctive treatment for major depressive disorder in adults.
On Twitter @whitneymcknight
*This article was updated 9/18/2015.
The Food and Drug Administration on Sept. 17 approved cariprazine, an atypical antipsychotic, for the acute treatment of manic or mixed episodes in bipolar I disorder and schizophrenia in adults.
Results from three separate controlled trials in adults with manic or mixed episodes of bipolar I disorder showed cariprazine (Vraylar) was associated with improved total scores on the Young Mania Rating Scale (YMRS), compared with placebo. In three separate placebo-controlled trials in adults with schizophrenia, the study drug was associated with improvements in Positive and Negative Syndrome Scale (PANSS) total scores, compared with placebo. Cariprazine also demonstrated efficacy in the Clinical Global Impressions–Severity (CGI-S) rating scale, which was the secondary efficacy endpoint in the respective trials for each condition. In all, 2,700 persons were enrolled in the trials.
The recommended dose of cariprazine in adults with bipolar I is once daily at 3-6 mg per day. For schizophrenia in adults, 1.5-6 mg/day is the recommended dose.
Adverse reactions occurring in at least 5% of the study population and at a rate of twice that in the placebo groups were extrapyramidal symptoms, akathisia, dyspepsia, vomiting, somnolence, and restlessness in the bipolar group. In the group with schizophrenia, the most commonly reported adverse events were extrapyramidal symptoms and akathisia.
Cariprazine is a dopamine-2 and dopamine-3 receptor partial agonist, tending toward the D3 receptor. Although its mechanism of action in schizophrenia and bipolar I disorder is unknown, the drug’s codeveloper, Gedeon Richter said in a statement that cariprazine’s efficacy “could be mediated through a combination of partial agonist activity at central D2 and serotonin 5-HT1A receptors and antagonist activity at serotonin 5-HT2A receptors.” In the United States and Canada, the drug is licensed to Actavis, now Allergan. Vraylar is manufactured by Forest Laboratories.
Data indicating the drug’s ability to improve flat affect in schizophrenia were presented at this year’s annual congress of the European College of Neuropsychopharmacology in Amsterdam. According to Gedeon Richter and Allergan, cariprazine also is being investigated for the treatment of bipolar depression and as adjunctive treatment for major depressive disorder in adults.
On Twitter @whitneymcknight
*This article was updated 9/18/2015.
The Food and Drug Administration on Sept. 17 approved cariprazine, an atypical antipsychotic, for the acute treatment of manic or mixed episodes in bipolar I disorder and schizophrenia in adults.
Results from three separate controlled trials in adults with manic or mixed episodes of bipolar I disorder showed cariprazine (Vraylar) was associated with improved total scores on the Young Mania Rating Scale (YMRS), compared with placebo. In three separate placebo-controlled trials in adults with schizophrenia, the study drug was associated with improvements in Positive and Negative Syndrome Scale (PANSS) total scores, compared with placebo. Cariprazine also demonstrated efficacy in the Clinical Global Impressions–Severity (CGI-S) rating scale, which was the secondary efficacy endpoint in the respective trials for each condition. In all, 2,700 persons were enrolled in the trials.
The recommended dose of cariprazine in adults with bipolar I is once daily at 3-6 mg per day. For schizophrenia in adults, 1.5-6 mg/day is the recommended dose.
Adverse reactions occurring in at least 5% of the study population and at a rate of twice that in the placebo groups were extrapyramidal symptoms, akathisia, dyspepsia, vomiting, somnolence, and restlessness in the bipolar group. In the group with schizophrenia, the most commonly reported adverse events were extrapyramidal symptoms and akathisia.
Cariprazine is a dopamine-2 and dopamine-3 receptor partial agonist, tending toward the D3 receptor. Although its mechanism of action in schizophrenia and bipolar I disorder is unknown, the drug’s codeveloper, Gedeon Richter said in a statement that cariprazine’s efficacy “could be mediated through a combination of partial agonist activity at central D2 and serotonin 5-HT1A receptors and antagonist activity at serotonin 5-HT2A receptors.” In the United States and Canada, the drug is licensed to Actavis, now Allergan. Vraylar is manufactured by Forest Laboratories.
Data indicating the drug’s ability to improve flat affect in schizophrenia were presented at this year’s annual congress of the European College of Neuropsychopharmacology in Amsterdam. According to Gedeon Richter and Allergan, cariprazine also is being investigated for the treatment of bipolar depression and as adjunctive treatment for major depressive disorder in adults.
On Twitter @whitneymcknight
*This article was updated 9/18/2015.
VIDEO: CDC urges flu shots for all eligible patients
WASHINGTON – While influenza vaccination rates have increased in recent years, work still needs to be done to achieve the Centers for Disease Control and Prevention’s goal of at least 70% vaccination.
“Vaccination is the single-most-important step people can take to protect themselves from influenza,” Dr. Tom Frieden, CDC director said at a press conference called by his agency and the National Foundation for Infectious Diseases (NFID). He urged people to get their influenza vaccination and make sure their children do as well.
The CDC estimates that 47% of U.S. residents aged 6 months or older received an influenza vaccination in the last flu season. The only age group that meets the federal 70% benchmark is the 6-23 months age group, with about 75% coverage. Children aged 2-4 years have a vaccination rate of 68%; adults aged 65 years and older have a vaccination rate of 67%; and 62% of children aged 5-12 years get vaccinated. The lowest vaccination rate is among adults aged 18-49 years, of whom only 40% get vaccinated.
Dr. Frieden was joined at the press event by Dr. William Schaffner, NFID medical director; Dr. Wendy Sue Swanson of Seattle Children’s Hospital; and Dr. Kathleen Neuzil, director of the Center for Vaccine Development at the University of Maryland, Baltimore.
In this interview, Dr. Neuzil discusses which strains of influenza are expected to be dominant in the coming flu season, whether to expect a strain mutation similar to what happened last season, the importance of getting children vaccinated, and pneumococcal vaccination for children and older adults.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
WASHINGTON – While influenza vaccination rates have increased in recent years, work still needs to be done to achieve the Centers for Disease Control and Prevention’s goal of at least 70% vaccination.
“Vaccination is the single-most-important step people can take to protect themselves from influenza,” Dr. Tom Frieden, CDC director said at a press conference called by his agency and the National Foundation for Infectious Diseases (NFID). He urged people to get their influenza vaccination and make sure their children do as well.
The CDC estimates that 47% of U.S. residents aged 6 months or older received an influenza vaccination in the last flu season. The only age group that meets the federal 70% benchmark is the 6-23 months age group, with about 75% coverage. Children aged 2-4 years have a vaccination rate of 68%; adults aged 65 years and older have a vaccination rate of 67%; and 62% of children aged 5-12 years get vaccinated. The lowest vaccination rate is among adults aged 18-49 years, of whom only 40% get vaccinated.
Dr. Frieden was joined at the press event by Dr. William Schaffner, NFID medical director; Dr. Wendy Sue Swanson of Seattle Children’s Hospital; and Dr. Kathleen Neuzil, director of the Center for Vaccine Development at the University of Maryland, Baltimore.
In this interview, Dr. Neuzil discusses which strains of influenza are expected to be dominant in the coming flu season, whether to expect a strain mutation similar to what happened last season, the importance of getting children vaccinated, and pneumococcal vaccination for children and older adults.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
WASHINGTON – While influenza vaccination rates have increased in recent years, work still needs to be done to achieve the Centers for Disease Control and Prevention’s goal of at least 70% vaccination.
“Vaccination is the single-most-important step people can take to protect themselves from influenza,” Dr. Tom Frieden, CDC director said at a press conference called by his agency and the National Foundation for Infectious Diseases (NFID). He urged people to get their influenza vaccination and make sure their children do as well.
The CDC estimates that 47% of U.S. residents aged 6 months or older received an influenza vaccination in the last flu season. The only age group that meets the federal 70% benchmark is the 6-23 months age group, with about 75% coverage. Children aged 2-4 years have a vaccination rate of 68%; adults aged 65 years and older have a vaccination rate of 67%; and 62% of children aged 5-12 years get vaccinated. The lowest vaccination rate is among adults aged 18-49 years, of whom only 40% get vaccinated.
Dr. Frieden was joined at the press event by Dr. William Schaffner, NFID medical director; Dr. Wendy Sue Swanson of Seattle Children’s Hospital; and Dr. Kathleen Neuzil, director of the Center for Vaccine Development at the University of Maryland, Baltimore.
In this interview, Dr. Neuzil discusses which strains of influenza are expected to be dominant in the coming flu season, whether to expect a strain mutation similar to what happened last season, the importance of getting children vaccinated, and pneumococcal vaccination for children and older adults.
The video associated with this article is no longer available on this site. Please view all of our videos on the MDedge YouTube channel
AT A CDC/NFID PRESS CONFERENCE
Using an Electronic Health Record-Based Registry to Improve Pediatric Sickle Cell Care
From the Department of Pediatrics, Boston University School of Medicine, Boston Medical Center, Boston, MA.
This article is the second in our Hemoglobinopathy Learning Collaborative series. See the related editorial by Oyeku et al in the February 2014 issue of JCOM. (—Ed.)
Abstract
- Objective: To describe the development and use of an electronic health record (EHR)–based sickle cell disease (SCD) registry for children with SCD to enhance case management and quality improvement (QI) efforts at an urban, academic, safety net institution.
- Methods: Using national guidelines and the literature, we created quality metrics for pediatric SCD that focused on vaccination delivery and use of transcranial Doppler screening and hydroxyurea. We revised EHR forms for SCD care and created an EHR-based SCD registry that permitted monthly and annual reporting on quality metrics.
- Results: From 2008 to 2012, the percentage of children with SCD vaccinated for influenza increased from 52% to 65%, and for meningococcus from 53% to 70%. After licensure of PCV13 in 2010, the percentage of children vaccinated rose to 69% in 2012. Results for PPV23 were mixed: 87% to 91% received ≥1 dose, but the rate for receiving the second dose declined from 76% to 64%. Percentage of children screened annually with transcranial Doppler consistently ranged from 62% to 73% during the 5 years. QI initiatives in 2012–2013 led to increased influenza vaccination, from 65% to 83%, and increased hydroxyurea use, from 52% to 73%.
- Conclusion: In this study, a practical, replicable and feasible approach for improving the quality of SCD care combined the collaboration of a multidisciplinary team, an EHR-based disease registry, and QI initiatives. Additional work is needed to define and measure all elements of high-quality care for children with SCD and link process measures to clinical outcomes.
Sickle cell disease (SCD) is the most commonly inherited disorder in the United States, affecting approximately 100,000 individuals and 1 in 400 African American births [1,2]. The use of preventive strategies, such as immunizations [3], transcranial Doppler screening and transfusion protocols [4,5], and hydroxyurea therapy [6,7] has contributed to decreased morbidity and mortality among children with SCD [8,9]. However, a substantial gap exists between the care that children with SCD should receive and the care they actually receive [10–12]. An essential component of any effort that seeks to improve care is the ability to measure care processes and outcomes in a way that can drive quality improvement (QI) initiatives. Registries serve a vital role in quality improvement activities for many pediatric conditions, including inflammatory bowel disease [13] and cystic fibrosis [14]. However, there are no national or nationally representative registries currently available for children with SCD [15]. There is a pressing need for better information systems and tools that can be used in mainstream clinical settings to measure clinical performance with respect to quality indicators [16] if the goals of high quality care and better quality of life are to be achieved for children with SCD.
Electronic health records (EHRs) have been successfully used to improve the quality of care and enhance performance measurement in select institutions [17,18], and adoption of EHRs is growing. The 2009 American Recovery and Reinvestment Act allocated $20.8 billion in incentives to assist providers to adopt and “meaningfully use” EHRs [19,20]. As of 2011, 39% of office-based providers have implemented at least a basic EHR [21], up from 17% in 2008 [22]. The effective use of EHRs depends on collaboration between technical and medical experts so that functionality is achieved and clinical quality is appropriately measured. In addition, few EHRs contain specialized content for the care of persons with SCD.
While independent registries have been shown to be effective in improving care [13,14,23], they involve extra time and effort for data entry, can be difficult and expensive to maintain, and may not be feasible for many systems that care for SCD patients. In this paper, we describe the development and use of our EHR-based SCD registry for children with SCD, including our efforts to engage key technical and clinical experts to develop an EHR that is tailored to the outpatient workflow and data collection of quality measures and implement a fully functional system that collects data on quality measures to support case management and continuous QI.
Methods
This study was conducted at Boston Medical Center, New England’s largest safety net hospital, which cares for 190 children with SCD ages 0 to 21 years. The outpatient EHR (Centricity, GE) has been in use since 2000 and is used for all aspects of outpatient care, including ordering of immunizations and tests, electronic prescription writing, and referrals to specialty care.
Outcome Measures
Vaccines: The Centers for Disease Control and Prevention (CDC) recommends vaccinating children with SCD [26] against influenza annually, given their susceptibility to the influenza virus [24,27]. The CDC also recommends the 23-valent pneumococcal polysaccharide vaccine (PPV23 2-dose series) and 13-valent pneumococcal conjugate vaccine (PCV13, per childhood routine vaccine schedule for young children and 1 catch-up dose for children previously vaccinated with PCV7), and meningococcal vaccine (2-dose series), given patients’ functional asplenic status [25,28].
Transcranial Doppler screening can identify children with hemoglobin (Hb) SS and Hb S-β0 thalassemia at higher risk of stroke, which may be prevented through hypertransfusion programs [4]. Screening is recommended annually for these children ages 2 to 16 years [25].
Hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia is an established practice [29,30]. We consider hydroxyurea therapy for all children 2 years and older with Hb SS and Hb S-β0 thalassemia, given the recently published safety data from the Baby-HUG trial [7] and the benefits of hydroxyurea among children and adults with SCD [6,31–35].
EHR-based Registry
Our EHR-based SCD registry includes 3 key components: (1) forms to support detailed documentation at the point-of-care (ie, clinic visit); (2) a registry management form to allow the QI team to identify patients to be included or excluded from the registry; and (3) a central data warehouse to support quality measurement and improvement.
Documentation in the EHR is performed using a set of customized templates or “forms.” These forms allow documentation of care provision in a structured way. The discrete data elements are stored within the data warehousing system that supports the EHR. The SCD forms used in this project were a revised version of existing forms used by our pediatric hematologists for the past 6 years. The primary goal was to improve efficiency in a patient encounter and enhance data collection efforts. In particular, several changes were made to enhance data collection for quality measures included in the SCD registry. First, we collected genotype in a standardized way to better define subpopulations of SCD patients, as some of the care provided is dictated by genotype. We also expanded data capture for transcranial Doppler screening to include date of last screening to prompt scheduling. For hydroxyurea, the forms now capture if hydroxyurea has been prescribed, and if not, why (eg, declined, not indicated); adherence, current dose, and routine labs for monitoring are also listed to aid in clinical decision-making. Finally, the forms were revised to prominently display the subset of immunizations important to SCD (described above) to assess if the patient is current.
Within the new forms, we collected all data elements important to providing care to children with SCD. Several new items existed in other parts of the EHR and were automatically pulled into the forms, including laboratory results, medications and immunizations. Other new data elements required manual entry by providers based on EHR review, as they had previously not been documented, documented on an ad hoc basis, or found as free text within notes (eg, number of ED visits and hospitalizations in the past year). Initial completion of these forms took approximately 10 to 15 minutes per patient, as many of these data elements were not individually captured prior to this work; documentation for subsequent comprehensive visits required an additional 5 to 10 minutes per chart. Currently, the 3 pediatric hematologists regularly use the SCD forms for routine visits.
The registry management form was also created by the EHR design team. Although this form is separate from the SCD forms, it was readily accessible to the clinical team to quickly check whether patients should be included or excluded from the SCD registry. In this way, inactive patients could be removed and new patients could be included. This form was completed for all active pediatric patients with SCD as of February 2013 using data from a separately maintained clinical database. For patients who were new to the pediatric hematology practice between July 2012 and February 2013 (eg, infants born during this period, patients transferring care), we manually determined a registry start date in order to calculate accurate denominators for each measure. New patients were entered into the SCD registry by members of the care team on an ad hoc basis, and biannual searches of problem lists were planned to ensure the pediatric SCD registry was complete using the SCD-related ICD-9 codes 282.6, 282.41 and 282.4 to encompass all sickle hemoglobinopathies, including sickle cell thalassemia.
For this project, we were fortunate to have a well-established clinical data warehouse into which the medical center’s EHR data is copied nightly. In addition, the medical center already had multiple chronic disease registries and a framework for evaluating and sharing QI data. We were able to add SCD to this existing infrastructure, which was helpful since a secure and HIPAA-compliant location to post these patient-level reports had been previously identified.
We paid for 40 hours of technical staff time using grant funds to create reports using data collected in the EHR for patients who were actively in the SCD registry per the registry management form. Using these data, summary reports for our key SCD metrics were generated on both an annual and monthly basis. We tested and refined our key SCD metrics over a 4-month period to ensure that we had defined the numerators and denominators for each care process accurately. For example, children become eligible for influenza vaccine at 6 months of age, therefore, the eligible denominator would exclude infants < 6 months of age (Table 1). In addition, lists of patient names and phone numbers were automatically generated to identify those in need of care elements, facilitating both case management and continuous improvement for these measures, replacing the need for all external clinical databases.
Data Analysis
For children included in the SCD registry, we calculated the proportion who were appropriately vaccinated and received transcranial Doppler screening each year for the 5-year period 2008–2012. For the period July 2012–June 2013, we calculated the proportion of children with SCD in the registry who received influenza vaccine and children with Hb SS and Hb S-β0 thalassemia who were prescribed hydroxyurea.
This study was approved by the Boston University Medical Campus institutional review board.
Results
For influenza vaccination for the 2012–2013 season, only 49% of children were vaccinated as of November. This proportion increased after outreach 
From July 2012 to June 2013, our rates of hydroxyurea use increased from 52% to 73% among eligible patients.
Discussion
In this paper we report on a practical approach for improving the quality of care for persons with SCD that combines the collaboration of a multidisciplinary team, the use of the EHR to create a disease registry, and QI initiatives. We identified where high-quality care is provided and where further attention is needed, and enhanced our case management capabilities with the generation of patient lists identifying those who are in need of care elements. We also used our registry to track care provision, achieving rates of influenza vaccination of 82% and hydroxyurea use to 73% as of June 2013. From these results, we have shown that our EHR can be used for registry management activities and provide real-time clinical data on the care that is provided, and can lead to improved performance on process measures important in the care for children with SCD.
After adjusting to the revised workflow required by the new SCD forms, the pediatric hematology team found them to be useful in tracking important clinical measures. They reported that the most important change was that all routine elements of SCD care, such as dates of last visits to pediatric subspecialists and receipt of recommended routine SCD care, were embedded into their note. This eliminated the need to search previous documents to find dates of the last cardiology visit or influenza immunizations and increased the likelihood that gaps in care would be addressed by the provider during the course of a clinic visit, thereby streamlining clinic workflow.
Healthy People 2020 recommend vaccination rates of 80% and 90% for influenza and PCV13 vaccines, respectively, in the general pediatric population [36]. We have met this goal for the influenza vaccine, but have room to improve for other recommended vaccines for children with SCD. Ultimately, our goal is to provide these vaccines to 100% of children with SCD at our institution. One barrier to achieving high vaccination rates is the lack of provider knowledge on the creation of catch-up vaccine schedules. A study of primary care providers showed that they frequently omitted vaccines when creating catch-up schedules, including the pneumococcal conjugate vaccine for healthy children [37]. Another hurdle is coordination of care between primary and specialty care, as these vaccines could be given in either setting. A recently published study found that only 20% of children with SCD had care coordination between primary and specialty care [38]. Promoting shared responsibility and information on the administration of vaccinations for children with SCD between primary and subspecialty care, and the development of state-wide immunization registries, may help alleviate these challenges.
In this study, our rates of hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia are higher than in other reported studies [12]. We promote hydroxyurea use in this population of children based on the recently published safety data in infants and young children with Hb SS and Hb S-β0 thalassemia [7,32,39] and the significant benefits seen in adults, including improved survival [6,34,35,40]. Future efforts will include tracking outcomes, including the rates of acute chest syndrome and pain episodes, among children who are and are not taking hydroxyurea.
In this study, we found approximately 70% of eligible children were screened with transcranial Doppler each year from 2008–2012, which is higher than the 45% annual screening rate reported in the literature [10]. One reason our transcranial Doppler screening rates may be higher is that a technician is available to perform these tests on certain days that coincide with the pediatric hematology clinic, allowing patients and families to get this test and have a clinic visit on the same day. However, choosing a 12-month period for receipt of transcranial Doppler screening may be too conservative for centers who do not have such ready access to screening; reporting receipt of transcranial Doppler screening within a 15-month time period may be more appropriate and achievable.
Our study has several limitations. First, it was conducted in a single center with well-established electronic data systems, which are not available in many centers. Our hope is that this model can be replicated by others who seek to use EHR to improve the care of persons with SCD. Second, this work was performed in Massachusetts, a state with near-universal health care insurance coverage. As the Affordable Care Act is implemented nationally [41], other states may see improved performance on quality metrics as more people obtain health insurance. Third, although the EHR was designed to improve data capture for clinical care and quality initiatives, advanced clinical decision support systems were not incorporated due to the limitations of the EHR. The use of prompts for needed clinical care may further enhance performance on these measures. Fourth, this study is limited to children with SCD, who are traditionally monitored more closely than their adult counterparts. Efforts are currently underway to replicate these efforts with adults with SCD at our institution. Finally, the quality metrics in this study are process measures in the delivery of high quality SCD care. Future efforts will focus on linking outcomes to these measures, such as hydroxyurea use to reduce the frequency of acute chest syndrome and painful episodes.
Effective use of health information technology has proven challenging [42,43]. Although there are data that suggest that information technology has improved quality of care by increasing adherence to guidelines, enhancing disease surveillance, and decreasing medication errors, most of the high-quality literature to date comes from 4 research institutions [18]. We found that health IT can be effectively harnessed when end-users are engaged in the process of EHR design, there is a strong commitment to improve workflow and support documentation needs of end-users, the design of the EHR supports data collection for quality measures, and most importantly, there is close collaboration among those with overlapping technical, clinical, and health services research expertise.
There have been many calls for the creation of rare disease registries, as 6% to 8% of the population will develop one in their lifetime [44]. In 2010, the NIH’s Office of Rare Diseases Research funded 30 organizations with and without patient registries, and charged them with the creation of a common data collection template for rare diseases to be used internationally [45]. Common data collection elements for SCD, such as those used in our program, could be used in EHRs across US centers in an effort to improve the quality of care for these children. Although this work may be challenging for centers using large enterprise EHR systems, given the costs associated with modifications, once developed the content can often be shared easily with others using the same system. This would provide the opportunity to compare uniform data across institutions and facilitate learning nationally on ways to improve care. In addition, these efforts may serve as the beginnings of a national registry for pediatric SCD.
In conclusion, contemporary SCD care can lead to improved survival and quality of life, but only if the right care is delivered at the right time. In this study, we present our initial findings from the implementation of a population-based information system for children with SCD. Future efforts are needed to define and measure all elements of high quality care, and link improvements in the delivery of high quality care to outcomes for children and adults with SCD longitudinally.
Appendix. Additional Sickle Cell Disease Forms
Acknowledgments: We would like to thank David Botts for his tireless efforts in creating the sickle cell forms within our EHR. We would also like to thank Barry Zuckerman for his support of this project.
Corresponding author: Patricia Kavanagh, MD, Boston University School of Medicine/Boston Medical Center, 88 E Newton St, Vose Hall 3rd Fl, Boston, MA 02118.
Funding/support: This work was supported by the Health Resources and Services Administration Sickle Cell Disease and Newborn Screening Program, grant #U38MC22215. The authors have also actively participated in the Hemoglobinopathy Learning Collaborative, a quality improvement forum coordinated by HRSA and the National Initiative for Children’s Healthcare Quality.
Financial disclosures: None.
1. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Preventive Med 2010;38(4 Suppl):S512–S521.
2. Steinberg MH. Management of sickle cell disease. N Engl J Med 1999;340:1021–30.
3. Adamkiewicz TV, Silk BJ, Howgate J, et al. Effectiveness of the 7-valent pneumococcal conjugate vaccine in children with sickle cell disease in the first decade of life. Pediatrics 2008;121:562–9.
4. Adams RJ, McKie VC, Hsu L, et al. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial doppler ultrasonography. N Engl J Med 1998;339:5–1.
5. Adams RJ, Brambilla D, Optimizing Primary Stroke Prevention in Sickle Cell Anemia Trial I. Discontinuing prophylactic transfusions used to prevent stroke in sickle cell disease.[see comment]. N Engl J Med 2005;353:2769–78.
6. Charache S, Terrin ML, Moore RD, et al. Effect of hydroxyurea on the frequency of painful crises in sickle cell anemia. N Engl J Med 1995;332:1317–22.
7. Wang WC, Ware RE, Miller ST, et al. Hydroxycarbamide in very young children with sickle-cell anaemia: A multicentre, randomised, controlled trial (baby hug). Lancet 2011;377:1663–72.
8. Quinn CT, Rogers ZR, McCavit TL, Buchanan GR. Improved survival of children and adolescents with sickle cell disease. Blood 2010;115:3447–52.
9. Hamideh D, Alvarez O. Sickle cell disease related mortality in the united states (1999–2009). Pediatr Blood Cancer 2013;60:1482–6.
10. Raphael JL, Shetty PB, Liu H, et al. A critical assessment of transcranial doppler screening rates in a large pediatric sickle cell center: Opportunities to improve healthcare quality. Pediatr Blood Cancer 2008;51:647–51.
11. Sox CM, Cooper WO, Koepsell TD, et al. Provision of pneumococcal prophylaxis for publicly insured children with sickle cell disease. JAMA 2003;290:1057–61.
12. Oyeku SO, Driscoll MC, Cohen HW, et al. Parental and other factors associated with hydroxyurea use for pediatric sickle cell disease. Pediatr Blood Cancer 2013;60:653–58.
13. Crandall WV, Margolis PA, Kappelman MD, et al. Improved outcomes in a quality improvement collaborative for pediatric inflammatory bowel disease. Pediatrics 2012;129:e1030–e1041.
14. Schechter MS, Margolis P. Improving subspecialty healthcare: Lessons from cystic fibrosis. J Pediatr 2005;147:295–301.
15. Smith LA, Oyeku SO, Homer C, Zuckerman B. Sickle cell disease: A question of equity and quality. Pediatrics 2006;117:1763–70.
16. Wang CJ, Kavanagh PL, Little AA, et al. Quality-of-care indicators for children with sickle cell disease. Pediatrics 2011;128:484–93.
17. Jha AK, Perlin JB, Kizer KW, Dudley RA. Effect of the transformation of the veterans affairs health care system on the quality of care. N Engl J Med 2003;348:2218–27.
18. Chaudhry B, Wang J, Wu S, et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006;144:742–52.
19. American recovery and reinvestment act of 2009. Obey D, Frank B, Gordon B, et al., trans. 111th Congress of the United States.
20. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010;363:501–4.
21. Electronic health record adoption by office-based providers. Office of National Coordinator for Health Information Technology. U.S. Department of Health and Human Services. Accessed 15 Jul 2013.
22. DesRoches CM, Campbell EG, Rao SR, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med 2008;359:50–60.
23. Tricco AC, Ivers NM, Grimshaw JM, et al. Effectiveness of quality improvement strategies on the management of diabetes: A systematic review and meta-analysis. Lancet 379:2252–61.
24. Bundy DG, Strouse JJ, Casella JF, Miller MR. Burden of influenza-related hospitalizations among children with sickle cell disease. Pediatrics 2010;125:234–43.
25. National Heart Lung and Blood Institute. The management of sickle cell disease. NIH Pub No. 02-2117. Bethesda, MD: National Institutes of Health; 2002.
26. Centers for Disease Control and Prevention. Immunization schedules. Accessed 5 Jan 2013 at www.cdc.gov/vaccines/schedules/index.html.
27. Strouse JJ, Reller ME, Bundy DG, et al. Severe pandemic h1n1 and seasonal influenza in children and young adults with sickle cell disease. Blood 2010;116:3431–4.
28. Pilishvili T, Zell ER, Farley MM, et al. Risk factors for invasive pneumococcal disease in children in the era of conjugate vaccine use. Pediatrics 2010;126:e9–17.
29. Heeney MM, Ware RE. Hydroxyurea for children with sickle cell disease. Pediatr Clin North Am 008;55:483–501.
30. Ware RE. How I use hydroxyurea to treat young patients with sickle cell anemia. Blood 2010;115:5300–11.
31. Ferster A, Vermylen C, Cornu G, et al. Hydroxyurea for treatment of severe sickle cell anemia: a pediatric clinical trial. Blood 1996;88:1960–4.
32. Strouse JJ, Lanzkron S, Beach MC, et al. Hydroxyurea for sickle cell disease: a systematic review for efficacy and toxicity in children. Pediatrics 2008;122:1332–42.
33. Hankins JS, Ware RE, Rogers ZR, et al. Long-term hydroxyurea therapy for infants with sickle cell anemia: the husoft extension study. Blood 2005;106:2269–75.
34. Steinberg MH, McCarthy WF, Castro O, et al. The risks and benefits of long-term use of hydroxyurea in sickle cell anemia: a 17.5-year follow-up. Am J Hematol 2010;85:403–8.
35. Voskaridou E, Christoulas D, Bilalis A, et al. The effect of prolonged administration of hydroxyurea on morbidity and mortality in adult patients with sickle cell syndromes: results of a 17-year, single-center trial (lashs). Blood 2010;115:2354–63.
36. Healthy people 2020. Immunization and infectious diseases. Accessed 3 Jun 2013 at www.healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx?topicid=23.
37. Cohen NJ, Lauderdale DS, Shete PB, et al. Physician knowledge of catch-up regimens and contraindications for childhood immunizations. Pediatrics 2003;111:925–32.
38. Raphael JL, Rattler TL, Kowalkowski MA, et al. The medical home experience among children with sickle cell disease. Pediatr Blood Cancer 2013;60:275–80.
39. Strouse JJ, Heeney MM. Hydroxyurea for the treatment of sickle cell disease: efficacy, barriers, toxicity, and management in children. Pediatr Blood Cancer 2012;59:365–71.
40. Steinberg MH, Barton F, Castro O, et al. Effect of hydroxyurea on mortality and morbidity in adult sickle cell anemia: risks and benefits up to 9 years of treatment. JAMA 2003;289:1645–51.
41. Patient protection and affordable care act, US Pub. L. No. 111-148, §2702, 124 stat. 119, 318-319. 2010.
42. Harrison M, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care: an interactive sociotechnical analysis. J Am Med Inform Assoc 2007;14:542–9.
43. Haux R. Health information systems – past, present, future. Int J Med Informatics 2006;75:268–81.
44. Schieppati A, Henter J-I, Daina E, Aperia A. Why rare diseases are an important medical and social issue. Lancet 2008;371:2039–41.
45. Office of Rare Diseases Research National Institutes of Health. Rare diseases and related terms. Accessed 28 Jun 2013 at www.rarediseases.info.nih.gov/rarediseaselist.aspx.
From the Department of Pediatrics, Boston University School of Medicine, Boston Medical Center, Boston, MA.
This article is the second in our Hemoglobinopathy Learning Collaborative series. See the related editorial by Oyeku et al in the February 2014 issue of JCOM. (—Ed.)
Abstract
- Objective: To describe the development and use of an electronic health record (EHR)–based sickle cell disease (SCD) registry for children with SCD to enhance case management and quality improvement (QI) efforts at an urban, academic, safety net institution.
- Methods: Using national guidelines and the literature, we created quality metrics for pediatric SCD that focused on vaccination delivery and use of transcranial Doppler screening and hydroxyurea. We revised EHR forms for SCD care and created an EHR-based SCD registry that permitted monthly and annual reporting on quality metrics.
- Results: From 2008 to 2012, the percentage of children with SCD vaccinated for influenza increased from 52% to 65%, and for meningococcus from 53% to 70%. After licensure of PCV13 in 2010, the percentage of children vaccinated rose to 69% in 2012. Results for PPV23 were mixed: 87% to 91% received ≥1 dose, but the rate for receiving the second dose declined from 76% to 64%. Percentage of children screened annually with transcranial Doppler consistently ranged from 62% to 73% during the 5 years. QI initiatives in 2012–2013 led to increased influenza vaccination, from 65% to 83%, and increased hydroxyurea use, from 52% to 73%.
- Conclusion: In this study, a practical, replicable and feasible approach for improving the quality of SCD care combined the collaboration of a multidisciplinary team, an EHR-based disease registry, and QI initiatives. Additional work is needed to define and measure all elements of high-quality care for children with SCD and link process measures to clinical outcomes.
Sickle cell disease (SCD) is the most commonly inherited disorder in the United States, affecting approximately 100,000 individuals and 1 in 400 African American births [1,2]. The use of preventive strategies, such as immunizations [3], transcranial Doppler screening and transfusion protocols [4,5], and hydroxyurea therapy [6,7] has contributed to decreased morbidity and mortality among children with SCD [8,9]. However, a substantial gap exists between the care that children with SCD should receive and the care they actually receive [10–12]. An essential component of any effort that seeks to improve care is the ability to measure care processes and outcomes in a way that can drive quality improvement (QI) initiatives. Registries serve a vital role in quality improvement activities for many pediatric conditions, including inflammatory bowel disease [13] and cystic fibrosis [14]. However, there are no national or nationally representative registries currently available for children with SCD [15]. There is a pressing need for better information systems and tools that can be used in mainstream clinical settings to measure clinical performance with respect to quality indicators [16] if the goals of high quality care and better quality of life are to be achieved for children with SCD.
Electronic health records (EHRs) have been successfully used to improve the quality of care and enhance performance measurement in select institutions [17,18], and adoption of EHRs is growing. The 2009 American Recovery and Reinvestment Act allocated $20.8 billion in incentives to assist providers to adopt and “meaningfully use” EHRs [19,20]. As of 2011, 39% of office-based providers have implemented at least a basic EHR [21], up from 17% in 2008 [22]. The effective use of EHRs depends on collaboration between technical and medical experts so that functionality is achieved and clinical quality is appropriately measured. In addition, few EHRs contain specialized content for the care of persons with SCD.
While independent registries have been shown to be effective in improving care [13,14,23], they involve extra time and effort for data entry, can be difficult and expensive to maintain, and may not be feasible for many systems that care for SCD patients. In this paper, we describe the development and use of our EHR-based SCD registry for children with SCD, including our efforts to engage key technical and clinical experts to develop an EHR that is tailored to the outpatient workflow and data collection of quality measures and implement a fully functional system that collects data on quality measures to support case management and continuous QI.
Methods
This study was conducted at Boston Medical Center, New England’s largest safety net hospital, which cares for 190 children with SCD ages 0 to 21 years. The outpatient EHR (Centricity, GE) has been in use since 2000 and is used for all aspects of outpatient care, including ordering of immunizations and tests, electronic prescription writing, and referrals to specialty care.
Outcome Measures
Vaccines: The Centers for Disease Control and Prevention (CDC) recommends vaccinating children with SCD [26] against influenza annually, given their susceptibility to the influenza virus [24,27]. The CDC also recommends the 23-valent pneumococcal polysaccharide vaccine (PPV23 2-dose series) and 13-valent pneumococcal conjugate vaccine (PCV13, per childhood routine vaccine schedule for young children and 1 catch-up dose for children previously vaccinated with PCV7), and meningococcal vaccine (2-dose series), given patients’ functional asplenic status [25,28].
Transcranial Doppler screening can identify children with hemoglobin (Hb) SS and Hb S-β0 thalassemia at higher risk of stroke, which may be prevented through hypertransfusion programs [4]. Screening is recommended annually for these children ages 2 to 16 years [25].
Hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia is an established practice [29,30]. We consider hydroxyurea therapy for all children 2 years and older with Hb SS and Hb S-β0 thalassemia, given the recently published safety data from the Baby-HUG trial [7] and the benefits of hydroxyurea among children and adults with SCD [6,31–35].
EHR-based Registry
Our EHR-based SCD registry includes 3 key components: (1) forms to support detailed documentation at the point-of-care (ie, clinic visit); (2) a registry management form to allow the QI team to identify patients to be included or excluded from the registry; and (3) a central data warehouse to support quality measurement and improvement.
Documentation in the EHR is performed using a set of customized templates or “forms.” These forms allow documentation of care provision in a structured way. The discrete data elements are stored within the data warehousing system that supports the EHR. The SCD forms used in this project were a revised version of existing forms used by our pediatric hematologists for the past 6 years. The primary goal was to improve efficiency in a patient encounter and enhance data collection efforts. In particular, several changes were made to enhance data collection for quality measures included in the SCD registry. First, we collected genotype in a standardized way to better define subpopulations of SCD patients, as some of the care provided is dictated by genotype. We also expanded data capture for transcranial Doppler screening to include date of last screening to prompt scheduling. For hydroxyurea, the forms now capture if hydroxyurea has been prescribed, and if not, why (eg, declined, not indicated); adherence, current dose, and routine labs for monitoring are also listed to aid in clinical decision-making. Finally, the forms were revised to prominently display the subset of immunizations important to SCD (described above) to assess if the patient is current.
Within the new forms, we collected all data elements important to providing care to children with SCD. Several new items existed in other parts of the EHR and were automatically pulled into the forms, including laboratory results, medications and immunizations. Other new data elements required manual entry by providers based on EHR review, as they had previously not been documented, documented on an ad hoc basis, or found as free text within notes (eg, number of ED visits and hospitalizations in the past year). Initial completion of these forms took approximately 10 to 15 minutes per patient, as many of these data elements were not individually captured prior to this work; documentation for subsequent comprehensive visits required an additional 5 to 10 minutes per chart. Currently, the 3 pediatric hematologists regularly use the SCD forms for routine visits.
The registry management form was also created by the EHR design team. Although this form is separate from the SCD forms, it was readily accessible to the clinical team to quickly check whether patients should be included or excluded from the SCD registry. In this way, inactive patients could be removed and new patients could be included. This form was completed for all active pediatric patients with SCD as of February 2013 using data from a separately maintained clinical database. For patients who were new to the pediatric hematology practice between July 2012 and February 2013 (eg, infants born during this period, patients transferring care), we manually determined a registry start date in order to calculate accurate denominators for each measure. New patients were entered into the SCD registry by members of the care team on an ad hoc basis, and biannual searches of problem lists were planned to ensure the pediatric SCD registry was complete using the SCD-related ICD-9 codes 282.6, 282.41 and 282.4 to encompass all sickle hemoglobinopathies, including sickle cell thalassemia.
For this project, we were fortunate to have a well-established clinical data warehouse into which the medical center’s EHR data is copied nightly. In addition, the medical center already had multiple chronic disease registries and a framework for evaluating and sharing QI data. We were able to add SCD to this existing infrastructure, which was helpful since a secure and HIPAA-compliant location to post these patient-level reports had been previously identified.
We paid for 40 hours of technical staff time using grant funds to create reports using data collected in the EHR for patients who were actively in the SCD registry per the registry management form. Using these data, summary reports for our key SCD metrics were generated on both an annual and monthly basis. We tested and refined our key SCD metrics over a 4-month period to ensure that we had defined the numerators and denominators for each care process accurately. For example, children become eligible for influenza vaccine at 6 months of age, therefore, the eligible denominator would exclude infants < 6 months of age (Table 1). In addition, lists of patient names and phone numbers were automatically generated to identify those in need of care elements, facilitating both case management and continuous improvement for these measures, replacing the need for all external clinical databases.
Data Analysis
For children included in the SCD registry, we calculated the proportion who were appropriately vaccinated and received transcranial Doppler screening each year for the 5-year period 2008–2012. For the period July 2012–June 2013, we calculated the proportion of children with SCD in the registry who received influenza vaccine and children with Hb SS and Hb S-β0 thalassemia who were prescribed hydroxyurea.
This study was approved by the Boston University Medical Campus institutional review board.
Results
For influenza vaccination for the 2012–2013 season, only 49% of children were vaccinated as of November. This proportion increased after outreach
From July 2012 to June 2013, our rates of hydroxyurea use increased from 52% to 73% among eligible patients.
Discussion
In this paper we report on a practical approach for improving the quality of care for persons with SCD that combines the collaboration of a multidisciplinary team, the use of the EHR to create a disease registry, and QI initiatives. We identified where high-quality care is provided and where further attention is needed, and enhanced our case management capabilities with the generation of patient lists identifying those who are in need of care elements. We also used our registry to track care provision, achieving rates of influenza vaccination of 82% and hydroxyurea use to 73% as of June 2013. From these results, we have shown that our EHR can be used for registry management activities and provide real-time clinical data on the care that is provided, and can lead to improved performance on process measures important in the care for children with SCD.
After adjusting to the revised workflow required by the new SCD forms, the pediatric hematology team found them to be useful in tracking important clinical measures. They reported that the most important change was that all routine elements of SCD care, such as dates of last visits to pediatric subspecialists and receipt of recommended routine SCD care, were embedded into their note. This eliminated the need to search previous documents to find dates of the last cardiology visit or influenza immunizations and increased the likelihood that gaps in care would be addressed by the provider during the course of a clinic visit, thereby streamlining clinic workflow.
Healthy People 2020 recommend vaccination rates of 80% and 90% for influenza and PCV13 vaccines, respectively, in the general pediatric population [36]. We have met this goal for the influenza vaccine, but have room to improve for other recommended vaccines for children with SCD. Ultimately, our goal is to provide these vaccines to 100% of children with SCD at our institution. One barrier to achieving high vaccination rates is the lack of provider knowledge on the creation of catch-up vaccine schedules. A study of primary care providers showed that they frequently omitted vaccines when creating catch-up schedules, including the pneumococcal conjugate vaccine for healthy children [37]. Another hurdle is coordination of care between primary and specialty care, as these vaccines could be given in either setting. A recently published study found that only 20% of children with SCD had care coordination between primary and specialty care [38]. Promoting shared responsibility and information on the administration of vaccinations for children with SCD between primary and subspecialty care, and the development of state-wide immunization registries, may help alleviate these challenges.
In this study, our rates of hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia are higher than in other reported studies [12]. We promote hydroxyurea use in this population of children based on the recently published safety data in infants and young children with Hb SS and Hb S-β0 thalassemia [7,32,39] and the significant benefits seen in adults, including improved survival [6,34,35,40]. Future efforts will include tracking outcomes, including the rates of acute chest syndrome and pain episodes, among children who are and are not taking hydroxyurea.
In this study, we found approximately 70% of eligible children were screened with transcranial Doppler each year from 2008–2012, which is higher than the 45% annual screening rate reported in the literature [10]. One reason our transcranial Doppler screening rates may be higher is that a technician is available to perform these tests on certain days that coincide with the pediatric hematology clinic, allowing patients and families to get this test and have a clinic visit on the same day. However, choosing a 12-month period for receipt of transcranial Doppler screening may be too conservative for centers who do not have such ready access to screening; reporting receipt of transcranial Doppler screening within a 15-month time period may be more appropriate and achievable.
Our study has several limitations. First, it was conducted in a single center with well-established electronic data systems, which are not available in many centers. Our hope is that this model can be replicated by others who seek to use EHR to improve the care of persons with SCD. Second, this work was performed in Massachusetts, a state with near-universal health care insurance coverage. As the Affordable Care Act is implemented nationally [41], other states may see improved performance on quality metrics as more people obtain health insurance. Third, although the EHR was designed to improve data capture for clinical care and quality initiatives, advanced clinical decision support systems were not incorporated due to the limitations of the EHR. The use of prompts for needed clinical care may further enhance performance on these measures. Fourth, this study is limited to children with SCD, who are traditionally monitored more closely than their adult counterparts. Efforts are currently underway to replicate these efforts with adults with SCD at our institution. Finally, the quality metrics in this study are process measures in the delivery of high quality SCD care. Future efforts will focus on linking outcomes to these measures, such as hydroxyurea use to reduce the frequency of acute chest syndrome and painful episodes.
Effective use of health information technology has proven challenging [42,43]. Although there are data that suggest that information technology has improved quality of care by increasing adherence to guidelines, enhancing disease surveillance, and decreasing medication errors, most of the high-quality literature to date comes from 4 research institutions [18]. We found that health IT can be effectively harnessed when end-users are engaged in the process of EHR design, there is a strong commitment to improve workflow and support documentation needs of end-users, the design of the EHR supports data collection for quality measures, and most importantly, there is close collaboration among those with overlapping technical, clinical, and health services research expertise.
There have been many calls for the creation of rare disease registries, as 6% to 8% of the population will develop one in their lifetime [44]. In 2010, the NIH’s Office of Rare Diseases Research funded 30 organizations with and without patient registries, and charged them with the creation of a common data collection template for rare diseases to be used internationally [45]. Common data collection elements for SCD, such as those used in our program, could be used in EHRs across US centers in an effort to improve the quality of care for these children. Although this work may be challenging for centers using large enterprise EHR systems, given the costs associated with modifications, once developed the content can often be shared easily with others using the same system. This would provide the opportunity to compare uniform data across institutions and facilitate learning nationally on ways to improve care. In addition, these efforts may serve as the beginnings of a national registry for pediatric SCD.
In conclusion, contemporary SCD care can lead to improved survival and quality of life, but only if the right care is delivered at the right time. In this study, we present our initial findings from the implementation of a population-based information system for children with SCD. Future efforts are needed to define and measure all elements of high quality care, and link improvements in the delivery of high quality care to outcomes for children and adults with SCD longitudinally.
Appendix. Additional Sickle Cell Disease Forms
Acknowledgments: We would like to thank David Botts for his tireless efforts in creating the sickle cell forms within our EHR. We would also like to thank Barry Zuckerman for his support of this project.
Corresponding author: Patricia Kavanagh, MD, Boston University School of Medicine/Boston Medical Center, 88 E Newton St, Vose Hall 3rd Fl, Boston, MA 02118.
Funding/support: This work was supported by the Health Resources and Services Administration Sickle Cell Disease and Newborn Screening Program, grant #U38MC22215. The authors have also actively participated in the Hemoglobinopathy Learning Collaborative, a quality improvement forum coordinated by HRSA and the National Initiative for Children’s Healthcare Quality.
Financial disclosures: None.
From the Department of Pediatrics, Boston University School of Medicine, Boston Medical Center, Boston, MA.
This article is the second in our Hemoglobinopathy Learning Collaborative series. See the related editorial by Oyeku et al in the February 2014 issue of JCOM. (—Ed.)
Abstract
- Objective: To describe the development and use of an electronic health record (EHR)–based sickle cell disease (SCD) registry for children with SCD to enhance case management and quality improvement (QI) efforts at an urban, academic, safety net institution.
- Methods: Using national guidelines and the literature, we created quality metrics for pediatric SCD that focused on vaccination delivery and use of transcranial Doppler screening and hydroxyurea. We revised EHR forms for SCD care and created an EHR-based SCD registry that permitted monthly and annual reporting on quality metrics.
- Results: From 2008 to 2012, the percentage of children with SCD vaccinated for influenza increased from 52% to 65%, and for meningococcus from 53% to 70%. After licensure of PCV13 in 2010, the percentage of children vaccinated rose to 69% in 2012. Results for PPV23 were mixed: 87% to 91% received ≥1 dose, but the rate for receiving the second dose declined from 76% to 64%. Percentage of children screened annually with transcranial Doppler consistently ranged from 62% to 73% during the 5 years. QI initiatives in 2012–2013 led to increased influenza vaccination, from 65% to 83%, and increased hydroxyurea use, from 52% to 73%.
- Conclusion: In this study, a practical, replicable and feasible approach for improving the quality of SCD care combined the collaboration of a multidisciplinary team, an EHR-based disease registry, and QI initiatives. Additional work is needed to define and measure all elements of high-quality care for children with SCD and link process measures to clinical outcomes.
Sickle cell disease (SCD) is the most commonly inherited disorder in the United States, affecting approximately 100,000 individuals and 1 in 400 African American births [1,2]. The use of preventive strategies, such as immunizations [3], transcranial Doppler screening and transfusion protocols [4,5], and hydroxyurea therapy [6,7] has contributed to decreased morbidity and mortality among children with SCD [8,9]. However, a substantial gap exists between the care that children with SCD should receive and the care they actually receive [10–12]. An essential component of any effort that seeks to improve care is the ability to measure care processes and outcomes in a way that can drive quality improvement (QI) initiatives. Registries serve a vital role in quality improvement activities for many pediatric conditions, including inflammatory bowel disease [13] and cystic fibrosis [14]. However, there are no national or nationally representative registries currently available for children with SCD [15]. There is a pressing need for better information systems and tools that can be used in mainstream clinical settings to measure clinical performance with respect to quality indicators [16] if the goals of high quality care and better quality of life are to be achieved for children with SCD.
Electronic health records (EHRs) have been successfully used to improve the quality of care and enhance performance measurement in select institutions [17,18], and adoption of EHRs is growing. The 2009 American Recovery and Reinvestment Act allocated $20.8 billion in incentives to assist providers to adopt and “meaningfully use” EHRs [19,20]. As of 2011, 39% of office-based providers have implemented at least a basic EHR [21], up from 17% in 2008 [22]. The effective use of EHRs depends on collaboration between technical and medical experts so that functionality is achieved and clinical quality is appropriately measured. In addition, few EHRs contain specialized content for the care of persons with SCD.
While independent registries have been shown to be effective in improving care [13,14,23], they involve extra time and effort for data entry, can be difficult and expensive to maintain, and may not be feasible for many systems that care for SCD patients. In this paper, we describe the development and use of our EHR-based SCD registry for children with SCD, including our efforts to engage key technical and clinical experts to develop an EHR that is tailored to the outpatient workflow and data collection of quality measures and implement a fully functional system that collects data on quality measures to support case management and continuous QI.
Methods
This study was conducted at Boston Medical Center, New England’s largest safety net hospital, which cares for 190 children with SCD ages 0 to 21 years. The outpatient EHR (Centricity, GE) has been in use since 2000 and is used for all aspects of outpatient care, including ordering of immunizations and tests, electronic prescription writing, and referrals to specialty care.
Outcome Measures
Vaccines: The Centers for Disease Control and Prevention (CDC) recommends vaccinating children with SCD [26] against influenza annually, given their susceptibility to the influenza virus [24,27]. The CDC also recommends the 23-valent pneumococcal polysaccharide vaccine (PPV23 2-dose series) and 13-valent pneumococcal conjugate vaccine (PCV13, per childhood routine vaccine schedule for young children and 1 catch-up dose for children previously vaccinated with PCV7), and meningococcal vaccine (2-dose series), given patients’ functional asplenic status [25,28].
Transcranial Doppler screening can identify children with hemoglobin (Hb) SS and Hb S-β0 thalassemia at higher risk of stroke, which may be prevented through hypertransfusion programs [4]. Screening is recommended annually for these children ages 2 to 16 years [25].
Hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia is an established practice [29,30]. We consider hydroxyurea therapy for all children 2 years and older with Hb SS and Hb S-β0 thalassemia, given the recently published safety data from the Baby-HUG trial [7] and the benefits of hydroxyurea among children and adults with SCD [6,31–35].
EHR-based Registry
Our EHR-based SCD registry includes 3 key components: (1) forms to support detailed documentation at the point-of-care (ie, clinic visit); (2) a registry management form to allow the QI team to identify patients to be included or excluded from the registry; and (3) a central data warehouse to support quality measurement and improvement.
Documentation in the EHR is performed using a set of customized templates or “forms.” These forms allow documentation of care provision in a structured way. The discrete data elements are stored within the data warehousing system that supports the EHR. The SCD forms used in this project were a revised version of existing forms used by our pediatric hematologists for the past 6 years. The primary goal was to improve efficiency in a patient encounter and enhance data collection efforts. In particular, several changes were made to enhance data collection for quality measures included in the SCD registry. First, we collected genotype in a standardized way to better define subpopulations of SCD patients, as some of the care provided is dictated by genotype. We also expanded data capture for transcranial Doppler screening to include date of last screening to prompt scheduling. For hydroxyurea, the forms now capture if hydroxyurea has been prescribed, and if not, why (eg, declined, not indicated); adherence, current dose, and routine labs for monitoring are also listed to aid in clinical decision-making. Finally, the forms were revised to prominently display the subset of immunizations important to SCD (described above) to assess if the patient is current.
Within the new forms, we collected all data elements important to providing care to children with SCD. Several new items existed in other parts of the EHR and were automatically pulled into the forms, including laboratory results, medications and immunizations. Other new data elements required manual entry by providers based on EHR review, as they had previously not been documented, documented on an ad hoc basis, or found as free text within notes (eg, number of ED visits and hospitalizations in the past year). Initial completion of these forms took approximately 10 to 15 minutes per patient, as many of these data elements were not individually captured prior to this work; documentation for subsequent comprehensive visits required an additional 5 to 10 minutes per chart. Currently, the 3 pediatric hematologists regularly use the SCD forms for routine visits.
The registry management form was also created by the EHR design team. Although this form is separate from the SCD forms, it was readily accessible to the clinical team to quickly check whether patients should be included or excluded from the SCD registry. In this way, inactive patients could be removed and new patients could be included. This form was completed for all active pediatric patients with SCD as of February 2013 using data from a separately maintained clinical database. For patients who were new to the pediatric hematology practice between July 2012 and February 2013 (eg, infants born during this period, patients transferring care), we manually determined a registry start date in order to calculate accurate denominators for each measure. New patients were entered into the SCD registry by members of the care team on an ad hoc basis, and biannual searches of problem lists were planned to ensure the pediatric SCD registry was complete using the SCD-related ICD-9 codes 282.6, 282.41 and 282.4 to encompass all sickle hemoglobinopathies, including sickle cell thalassemia.
For this project, we were fortunate to have a well-established clinical data warehouse into which the medical center’s EHR data is copied nightly. In addition, the medical center already had multiple chronic disease registries and a framework for evaluating and sharing QI data. We were able to add SCD to this existing infrastructure, which was helpful since a secure and HIPAA-compliant location to post these patient-level reports had been previously identified.
We paid for 40 hours of technical staff time using grant funds to create reports using data collected in the EHR for patients who were actively in the SCD registry per the registry management form. Using these data, summary reports for our key SCD metrics were generated on both an annual and monthly basis. We tested and refined our key SCD metrics over a 4-month period to ensure that we had defined the numerators and denominators for each care process accurately. For example, children become eligible for influenza vaccine at 6 months of age, therefore, the eligible denominator would exclude infants < 6 months of age (Table 1). In addition, lists of patient names and phone numbers were automatically generated to identify those in need of care elements, facilitating both case management and continuous improvement for these measures, replacing the need for all external clinical databases.
Data Analysis
For children included in the SCD registry, we calculated the proportion who were appropriately vaccinated and received transcranial Doppler screening each year for the 5-year period 2008–2012. For the period July 2012–June 2013, we calculated the proportion of children with SCD in the registry who received influenza vaccine and children with Hb SS and Hb S-β0 thalassemia who were prescribed hydroxyurea.
This study was approved by the Boston University Medical Campus institutional review board.
Results
For influenza vaccination for the 2012–2013 season, only 49% of children were vaccinated as of November. This proportion increased after outreach
From July 2012 to June 2013, our rates of hydroxyurea use increased from 52% to 73% among eligible patients.
Discussion
In this paper we report on a practical approach for improving the quality of care for persons with SCD that combines the collaboration of a multidisciplinary team, the use of the EHR to create a disease registry, and QI initiatives. We identified where high-quality care is provided and where further attention is needed, and enhanced our case management capabilities with the generation of patient lists identifying those who are in need of care elements. We also used our registry to track care provision, achieving rates of influenza vaccination of 82% and hydroxyurea use to 73% as of June 2013. From these results, we have shown that our EHR can be used for registry management activities and provide real-time clinical data on the care that is provided, and can lead to improved performance on process measures important in the care for children with SCD.
After adjusting to the revised workflow required by the new SCD forms, the pediatric hematology team found them to be useful in tracking important clinical measures. They reported that the most important change was that all routine elements of SCD care, such as dates of last visits to pediatric subspecialists and receipt of recommended routine SCD care, were embedded into their note. This eliminated the need to search previous documents to find dates of the last cardiology visit or influenza immunizations and increased the likelihood that gaps in care would be addressed by the provider during the course of a clinic visit, thereby streamlining clinic workflow.
Healthy People 2020 recommend vaccination rates of 80% and 90% for influenza and PCV13 vaccines, respectively, in the general pediatric population [36]. We have met this goal for the influenza vaccine, but have room to improve for other recommended vaccines for children with SCD. Ultimately, our goal is to provide these vaccines to 100% of children with SCD at our institution. One barrier to achieving high vaccination rates is the lack of provider knowledge on the creation of catch-up vaccine schedules. A study of primary care providers showed that they frequently omitted vaccines when creating catch-up schedules, including the pneumococcal conjugate vaccine for healthy children [37]. Another hurdle is coordination of care between primary and specialty care, as these vaccines could be given in either setting. A recently published study found that only 20% of children with SCD had care coordination between primary and specialty care [38]. Promoting shared responsibility and information on the administration of vaccinations for children with SCD between primary and subspecialty care, and the development of state-wide immunization registries, may help alleviate these challenges.
In this study, our rates of hydroxyurea use among children with Hb SS and Hb S-β0 thalassemia are higher than in other reported studies [12]. We promote hydroxyurea use in this population of children based on the recently published safety data in infants and young children with Hb SS and Hb S-β0 thalassemia [7,32,39] and the significant benefits seen in adults, including improved survival [6,34,35,40]. Future efforts will include tracking outcomes, including the rates of acute chest syndrome and pain episodes, among children who are and are not taking hydroxyurea.
In this study, we found approximately 70% of eligible children were screened with transcranial Doppler each year from 2008–2012, which is higher than the 45% annual screening rate reported in the literature [10]. One reason our transcranial Doppler screening rates may be higher is that a technician is available to perform these tests on certain days that coincide with the pediatric hematology clinic, allowing patients and families to get this test and have a clinic visit on the same day. However, choosing a 12-month period for receipt of transcranial Doppler screening may be too conservative for centers who do not have such ready access to screening; reporting receipt of transcranial Doppler screening within a 15-month time period may be more appropriate and achievable.
Our study has several limitations. First, it was conducted in a single center with well-established electronic data systems, which are not available in many centers. Our hope is that this model can be replicated by others who seek to use EHR to improve the care of persons with SCD. Second, this work was performed in Massachusetts, a state with near-universal health care insurance coverage. As the Affordable Care Act is implemented nationally [41], other states may see improved performance on quality metrics as more people obtain health insurance. Third, although the EHR was designed to improve data capture for clinical care and quality initiatives, advanced clinical decision support systems were not incorporated due to the limitations of the EHR. The use of prompts for needed clinical care may further enhance performance on these measures. Fourth, this study is limited to children with SCD, who are traditionally monitored more closely than their adult counterparts. Efforts are currently underway to replicate these efforts with adults with SCD at our institution. Finally, the quality metrics in this study are process measures in the delivery of high quality SCD care. Future efforts will focus on linking outcomes to these measures, such as hydroxyurea use to reduce the frequency of acute chest syndrome and painful episodes.
Effective use of health information technology has proven challenging [42,43]. Although there are data that suggest that information technology has improved quality of care by increasing adherence to guidelines, enhancing disease surveillance, and decreasing medication errors, most of the high-quality literature to date comes from 4 research institutions [18]. We found that health IT can be effectively harnessed when end-users are engaged in the process of EHR design, there is a strong commitment to improve workflow and support documentation needs of end-users, the design of the EHR supports data collection for quality measures, and most importantly, there is close collaboration among those with overlapping technical, clinical, and health services research expertise.
There have been many calls for the creation of rare disease registries, as 6% to 8% of the population will develop one in their lifetime [44]. In 2010, the NIH’s Office of Rare Diseases Research funded 30 organizations with and without patient registries, and charged them with the creation of a common data collection template for rare diseases to be used internationally [45]. Common data collection elements for SCD, such as those used in our program, could be used in EHRs across US centers in an effort to improve the quality of care for these children. Although this work may be challenging for centers using large enterprise EHR systems, given the costs associated with modifications, once developed the content can often be shared easily with others using the same system. This would provide the opportunity to compare uniform data across institutions and facilitate learning nationally on ways to improve care. In addition, these efforts may serve as the beginnings of a national registry for pediatric SCD.
In conclusion, contemporary SCD care can lead to improved survival and quality of life, but only if the right care is delivered at the right time. In this study, we present our initial findings from the implementation of a population-based information system for children with SCD. Future efforts are needed to define and measure all elements of high quality care, and link improvements in the delivery of high quality care to outcomes for children and adults with SCD longitudinally.
Appendix. Additional Sickle Cell Disease Forms
Acknowledgments: We would like to thank David Botts for his tireless efforts in creating the sickle cell forms within our EHR. We would also like to thank Barry Zuckerman for his support of this project.
Corresponding author: Patricia Kavanagh, MD, Boston University School of Medicine/Boston Medical Center, 88 E Newton St, Vose Hall 3rd Fl, Boston, MA 02118.
Funding/support: This work was supported by the Health Resources and Services Administration Sickle Cell Disease and Newborn Screening Program, grant #U38MC22215. The authors have also actively participated in the Hemoglobinopathy Learning Collaborative, a quality improvement forum coordinated by HRSA and the National Initiative for Children’s Healthcare Quality.
Financial disclosures: None.
1. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Preventive Med 2010;38(4 Suppl):S512–S521.
2. Steinberg MH. Management of sickle cell disease. N Engl J Med 1999;340:1021–30.
3. Adamkiewicz TV, Silk BJ, Howgate J, et al. Effectiveness of the 7-valent pneumococcal conjugate vaccine in children with sickle cell disease in the first decade of life. Pediatrics 2008;121:562–9.
4. Adams RJ, McKie VC, Hsu L, et al. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial doppler ultrasonography. N Engl J Med 1998;339:5–1.
5. Adams RJ, Brambilla D, Optimizing Primary Stroke Prevention in Sickle Cell Anemia Trial I. Discontinuing prophylactic transfusions used to prevent stroke in sickle cell disease.[see comment]. N Engl J Med 2005;353:2769–78.
6. Charache S, Terrin ML, Moore RD, et al. Effect of hydroxyurea on the frequency of painful crises in sickle cell anemia. N Engl J Med 1995;332:1317–22.
7. Wang WC, Ware RE, Miller ST, et al. Hydroxycarbamide in very young children with sickle-cell anaemia: A multicentre, randomised, controlled trial (baby hug). Lancet 2011;377:1663–72.
8. Quinn CT, Rogers ZR, McCavit TL, Buchanan GR. Improved survival of children and adolescents with sickle cell disease. Blood 2010;115:3447–52.
9. Hamideh D, Alvarez O. Sickle cell disease related mortality in the united states (1999–2009). Pediatr Blood Cancer 2013;60:1482–6.
10. Raphael JL, Shetty PB, Liu H, et al. A critical assessment of transcranial doppler screening rates in a large pediatric sickle cell center: Opportunities to improve healthcare quality. Pediatr Blood Cancer 2008;51:647–51.
11. Sox CM, Cooper WO, Koepsell TD, et al. Provision of pneumococcal prophylaxis for publicly insured children with sickle cell disease. JAMA 2003;290:1057–61.
12. Oyeku SO, Driscoll MC, Cohen HW, et al. Parental and other factors associated with hydroxyurea use for pediatric sickle cell disease. Pediatr Blood Cancer 2013;60:653–58.
13. Crandall WV, Margolis PA, Kappelman MD, et al. Improved outcomes in a quality improvement collaborative for pediatric inflammatory bowel disease. Pediatrics 2012;129:e1030–e1041.
14. Schechter MS, Margolis P. Improving subspecialty healthcare: Lessons from cystic fibrosis. J Pediatr 2005;147:295–301.
15. Smith LA, Oyeku SO, Homer C, Zuckerman B. Sickle cell disease: A question of equity and quality. Pediatrics 2006;117:1763–70.
16. Wang CJ, Kavanagh PL, Little AA, et al. Quality-of-care indicators for children with sickle cell disease. Pediatrics 2011;128:484–93.
17. Jha AK, Perlin JB, Kizer KW, Dudley RA. Effect of the transformation of the veterans affairs health care system on the quality of care. N Engl J Med 2003;348:2218–27.
18. Chaudhry B, Wang J, Wu S, et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006;144:742–52.
19. American recovery and reinvestment act of 2009. Obey D, Frank B, Gordon B, et al., trans. 111th Congress of the United States.
20. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010;363:501–4.
21. Electronic health record adoption by office-based providers. Office of National Coordinator for Health Information Technology. U.S. Department of Health and Human Services. Accessed 15 Jul 2013.
22. DesRoches CM, Campbell EG, Rao SR, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med 2008;359:50–60.
23. Tricco AC, Ivers NM, Grimshaw JM, et al. Effectiveness of quality improvement strategies on the management of diabetes: A systematic review and meta-analysis. Lancet 379:2252–61.
24. Bundy DG, Strouse JJ, Casella JF, Miller MR. Burden of influenza-related hospitalizations among children with sickle cell disease. Pediatrics 2010;125:234–43.
25. National Heart Lung and Blood Institute. The management of sickle cell disease. NIH Pub No. 02-2117. Bethesda, MD: National Institutes of Health; 2002.
26. Centers for Disease Control and Prevention. Immunization schedules. Accessed 5 Jan 2013 at www.cdc.gov/vaccines/schedules/index.html.
27. Strouse JJ, Reller ME, Bundy DG, et al. Severe pandemic h1n1 and seasonal influenza in children and young adults with sickle cell disease. Blood 2010;116:3431–4.
28. Pilishvili T, Zell ER, Farley MM, et al. Risk factors for invasive pneumococcal disease in children in the era of conjugate vaccine use. Pediatrics 2010;126:e9–17.
29. Heeney MM, Ware RE. Hydroxyurea for children with sickle cell disease. Pediatr Clin North Am 008;55:483–501.
30. Ware RE. How I use hydroxyurea to treat young patients with sickle cell anemia. Blood 2010;115:5300–11.
31. Ferster A, Vermylen C, Cornu G, et al. Hydroxyurea for treatment of severe sickle cell anemia: a pediatric clinical trial. Blood 1996;88:1960–4.
32. Strouse JJ, Lanzkron S, Beach MC, et al. Hydroxyurea for sickle cell disease: a systematic review for efficacy and toxicity in children. Pediatrics 2008;122:1332–42.
33. Hankins JS, Ware RE, Rogers ZR, et al. Long-term hydroxyurea therapy for infants with sickle cell anemia: the husoft extension study. Blood 2005;106:2269–75.
34. Steinberg MH, McCarthy WF, Castro O, et al. The risks and benefits of long-term use of hydroxyurea in sickle cell anemia: a 17.5-year follow-up. Am J Hematol 2010;85:403–8.
35. Voskaridou E, Christoulas D, Bilalis A, et al. The effect of prolonged administration of hydroxyurea on morbidity and mortality in adult patients with sickle cell syndromes: results of a 17-year, single-center trial (lashs). Blood 2010;115:2354–63.
36. Healthy people 2020. Immunization and infectious diseases. Accessed 3 Jun 2013 at www.healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx?topicid=23.
37. Cohen NJ, Lauderdale DS, Shete PB, et al. Physician knowledge of catch-up regimens and contraindications for childhood immunizations. Pediatrics 2003;111:925–32.
38. Raphael JL, Rattler TL, Kowalkowski MA, et al. The medical home experience among children with sickle cell disease. Pediatr Blood Cancer 2013;60:275–80.
39. Strouse JJ, Heeney MM. Hydroxyurea for the treatment of sickle cell disease: efficacy, barriers, toxicity, and management in children. Pediatr Blood Cancer 2012;59:365–71.
40. Steinberg MH, Barton F, Castro O, et al. Effect of hydroxyurea on mortality and morbidity in adult sickle cell anemia: risks and benefits up to 9 years of treatment. JAMA 2003;289:1645–51.
41. Patient protection and affordable care act, US Pub. L. No. 111-148, §2702, 124 stat. 119, 318-319. 2010.
42. Harrison M, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care: an interactive sociotechnical analysis. J Am Med Inform Assoc 2007;14:542–9.
43. Haux R. Health information systems – past, present, future. Int J Med Informatics 2006;75:268–81.
44. Schieppati A, Henter J-I, Daina E, Aperia A. Why rare diseases are an important medical and social issue. Lancet 2008;371:2039–41.
45. Office of Rare Diseases Research National Institutes of Health. Rare diseases and related terms. Accessed 28 Jun 2013 at www.rarediseases.info.nih.gov/rarediseaselist.aspx.
1. Hassell KL. Population estimates of sickle cell disease in the U.S. Am J Preventive Med 2010;38(4 Suppl):S512–S521.
2. Steinberg MH. Management of sickle cell disease. N Engl J Med 1999;340:1021–30.
3. Adamkiewicz TV, Silk BJ, Howgate J, et al. Effectiveness of the 7-valent pneumococcal conjugate vaccine in children with sickle cell disease in the first decade of life. Pediatrics 2008;121:562–9.
4. Adams RJ, McKie VC, Hsu L, et al. Prevention of a first stroke by transfusions in children with sickle cell anemia and abnormal results on transcranial doppler ultrasonography. N Engl J Med 1998;339:5–1.
5. Adams RJ, Brambilla D, Optimizing Primary Stroke Prevention in Sickle Cell Anemia Trial I. Discontinuing prophylactic transfusions used to prevent stroke in sickle cell disease.[see comment]. N Engl J Med 2005;353:2769–78.
6. Charache S, Terrin ML, Moore RD, et al. Effect of hydroxyurea on the frequency of painful crises in sickle cell anemia. N Engl J Med 1995;332:1317–22.
7. Wang WC, Ware RE, Miller ST, et al. Hydroxycarbamide in very young children with sickle-cell anaemia: A multicentre, randomised, controlled trial (baby hug). Lancet 2011;377:1663–72.
8. Quinn CT, Rogers ZR, McCavit TL, Buchanan GR. Improved survival of children and adolescents with sickle cell disease. Blood 2010;115:3447–52.
9. Hamideh D, Alvarez O. Sickle cell disease related mortality in the united states (1999–2009). Pediatr Blood Cancer 2013;60:1482–6.
10. Raphael JL, Shetty PB, Liu H, et al. A critical assessment of transcranial doppler screening rates in a large pediatric sickle cell center: Opportunities to improve healthcare quality. Pediatr Blood Cancer 2008;51:647–51.
11. Sox CM, Cooper WO, Koepsell TD, et al. Provision of pneumococcal prophylaxis for publicly insured children with sickle cell disease. JAMA 2003;290:1057–61.
12. Oyeku SO, Driscoll MC, Cohen HW, et al. Parental and other factors associated with hydroxyurea use for pediatric sickle cell disease. Pediatr Blood Cancer 2013;60:653–58.
13. Crandall WV, Margolis PA, Kappelman MD, et al. Improved outcomes in a quality improvement collaborative for pediatric inflammatory bowel disease. Pediatrics 2012;129:e1030–e1041.
14. Schechter MS, Margolis P. Improving subspecialty healthcare: Lessons from cystic fibrosis. J Pediatr 2005;147:295–301.
15. Smith LA, Oyeku SO, Homer C, Zuckerman B. Sickle cell disease: A question of equity and quality. Pediatrics 2006;117:1763–70.
16. Wang CJ, Kavanagh PL, Little AA, et al. Quality-of-care indicators for children with sickle cell disease. Pediatrics 2011;128:484–93.
17. Jha AK, Perlin JB, Kizer KW, Dudley RA. Effect of the transformation of the veterans affairs health care system on the quality of care. N Engl J Med 2003;348:2218–27.
18. Chaudhry B, Wang J, Wu S, et al. Systematic review: Impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 2006;144:742–52.
19. American recovery and reinvestment act of 2009. Obey D, Frank B, Gordon B, et al., trans. 111th Congress of the United States.
20. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med 2010;363:501–4.
21. Electronic health record adoption by office-based providers. Office of National Coordinator for Health Information Technology. U.S. Department of Health and Human Services. Accessed 15 Jul 2013.
22. DesRoches CM, Campbell EG, Rao SR, et al. Electronic health records in ambulatory care — a national survey of physicians. N Engl J Med 2008;359:50–60.
23. Tricco AC, Ivers NM, Grimshaw JM, et al. Effectiveness of quality improvement strategies on the management of diabetes: A systematic review and meta-analysis. Lancet 379:2252–61.
24. Bundy DG, Strouse JJ, Casella JF, Miller MR. Burden of influenza-related hospitalizations among children with sickle cell disease. Pediatrics 2010;125:234–43.
25. National Heart Lung and Blood Institute. The management of sickle cell disease. NIH Pub No. 02-2117. Bethesda, MD: National Institutes of Health; 2002.
26. Centers for Disease Control and Prevention. Immunization schedules. Accessed 5 Jan 2013 at www.cdc.gov/vaccines/schedules/index.html.
27. Strouse JJ, Reller ME, Bundy DG, et al. Severe pandemic h1n1 and seasonal influenza in children and young adults with sickle cell disease. Blood 2010;116:3431–4.
28. Pilishvili T, Zell ER, Farley MM, et al. Risk factors for invasive pneumococcal disease in children in the era of conjugate vaccine use. Pediatrics 2010;126:e9–17.
29. Heeney MM, Ware RE. Hydroxyurea for children with sickle cell disease. Pediatr Clin North Am 008;55:483–501.
30. Ware RE. How I use hydroxyurea to treat young patients with sickle cell anemia. Blood 2010;115:5300–11.
31. Ferster A, Vermylen C, Cornu G, et al. Hydroxyurea for treatment of severe sickle cell anemia: a pediatric clinical trial. Blood 1996;88:1960–4.
32. Strouse JJ, Lanzkron S, Beach MC, et al. Hydroxyurea for sickle cell disease: a systematic review for efficacy and toxicity in children. Pediatrics 2008;122:1332–42.
33. Hankins JS, Ware RE, Rogers ZR, et al. Long-term hydroxyurea therapy for infants with sickle cell anemia: the husoft extension study. Blood 2005;106:2269–75.
34. Steinberg MH, McCarthy WF, Castro O, et al. The risks and benefits of long-term use of hydroxyurea in sickle cell anemia: a 17.5-year follow-up. Am J Hematol 2010;85:403–8.
35. Voskaridou E, Christoulas D, Bilalis A, et al. The effect of prolonged administration of hydroxyurea on morbidity and mortality in adult patients with sickle cell syndromes: results of a 17-year, single-center trial (lashs). Blood 2010;115:2354–63.
36. Healthy people 2020. Immunization and infectious diseases. Accessed 3 Jun 2013 at www.healthypeople.gov/2020/topicsobjectives2020/objectiveslist.aspx?topicid=23.
37. Cohen NJ, Lauderdale DS, Shete PB, et al. Physician knowledge of catch-up regimens and contraindications for childhood immunizations. Pediatrics 2003;111:925–32.
38. Raphael JL, Rattler TL, Kowalkowski MA, et al. The medical home experience among children with sickle cell disease. Pediatr Blood Cancer 2013;60:275–80.
39. Strouse JJ, Heeney MM. Hydroxyurea for the treatment of sickle cell disease: efficacy, barriers, toxicity, and management in children. Pediatr Blood Cancer 2012;59:365–71.
40. Steinberg MH, Barton F, Castro O, et al. Effect of hydroxyurea on mortality and morbidity in adult sickle cell anemia: risks and benefits up to 9 years of treatment. JAMA 2003;289:1645–51.
41. Patient protection and affordable care act, US Pub. L. No. 111-148, §2702, 124 stat. 119, 318-319. 2010.
42. Harrison M, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care: an interactive sociotechnical analysis. J Am Med Inform Assoc 2007;14:542–9.
43. Haux R. Health information systems – past, present, future. Int J Med Informatics 2006;75:268–81.
44. Schieppati A, Henter J-I, Daina E, Aperia A. Why rare diseases are an important medical and social issue. Lancet 2008;371:2039–41.
45. Office of Rare Diseases Research National Institutes of Health. Rare diseases and related terms. Accessed 28 Jun 2013 at www.rarediseases.info.nih.gov/rarediseaselist.aspx.
Evidence-based Management of Newly Diagnosed Chronic Lymphocytic Leukemia
From the Division of Hematology, Ohio State University, Columbus, OH.
Abstract
- Objective: To describe the diagnosis and initial management of chronic lymphocytic leukemia (CLL), including first-line treatment options.
- Methods: Case presentation and review of the literature.
- Results: Most CLL patients demonstrate a chronic, relapsing and remitting course with intervals of months to years between treatments. Recent advances in genetic and molecular markers for risk stratification of CLL significantly impact how clinicians determine prognosis and predict response to treatment for patients with newly diagnosed disease. This information, along with patient factors such as age and health status, should be considered when formulating an initial treatment strategy. Combinations of chemotherapy and immunotherapy offer the longest progression-free survival and overall survival benefit yet reported. For elderly patients or those with significant comorbidities who may not tolerate standard chemoimmunotherapy, less intensive but still effective therapies now exist. Patients with the highest risk disease, such as those with deletions of chromosome 17p, respond poorly to conventional treatment and should be referred to experienced centers where investigational therapies and allogeneic stem cell transplantation are available.
- Conclusion: Both disease characteristics and patient factors should guide the selection among the various effective therapies for CLL. While chemoimmunotherapy is the most effective treatment developed to date, its use may become less prevalent as newer agents are incorporated into initial and relapse treatment algorithms.
Chronic lymphocytic leukemia (CLL) is a chronic malignancy of B-lymphocytes demonstrating a heterogeneous clinical course ranging from indolent to more rapidly progressive. The chief clinical feature is an elevated peripheral blood lymphocyte count, and patients can demonstrate lymphadenopathy, splenomegaly, hepatomegaly, constitutional symptoms, and in late stages bone marrow failure. It is the most common leukemia among adults in the Western world, accounting for between 22% to 30% of new leukemia diagnoses worldwide [1]. Recent incidence rates in the United States are 3.83 cases per 100,000 person-years [2]. The incidence of CLL increases with age, and most new cases are diagnosed in persons 65 years of age or older [1,2]. As reported 5-year survival rates are between 68% and 81% with a median survival of 10 years in some series, the prevalence is significantly higher than the incidence [3]. However, this may even be an underestimate of the population burden of disease, as many cases are not reported to tumor registries [4].
Many patients with CLL are asymptomatic and do not require treatment until years after diagnosis. In these cases a watch and wait approach is taken. The typical natural history of CLL is characterized by periods of effective treatment when required, followed by treatment-free intervals of several years in many cases. However, this can be misleading, as the clinical course for any individual patient is highly variable. Development of cytogenetic and molecular testing has allowed for identification of patients with a higher risk of progression and lower response rates to traditional cytotoxic treatments [5]. For example, depending on chromosomal abnormalities present, median survival can vary from 32 to 133 months [3].
The assessment of underlying disease risk thus provides important information when considering a treatment approach and should be routinely performed for newly diagnosed patients. While the development of highly effective chemoimmunotherapy has allowed most groups of CLL patients to live for many years, some groups do not enjoy the same survival. Recent advances in CLL treatment seek to abrogate such adverse risk factors, thereby improving the survival for all patients with CLL. Given the expected survival of years for most CLL patients, frontline treatment planning must be done in the context of a long-term treatment strategy keeping the risk for late toxicities, such as secondary malignancies, in mind.
Case Study
Initial Presentation
A 50-year-old man is referred for evaluation of cervical lymphadenopathy that had progressed over the prior 6 months. He denies associated symptoms of fatigue, fevers, night sweats, or unintentional weight loss but does report early satiety. On examination there are multiple mobile, enlarged cervical lymph nodes bilaterally. Axillary lymph nodes are likewise enlarged. The liver edge is not palpable, but the spleen is palpable below the belt line. Complete blood count reveals a white blood cell count of 196,000 with 97% lymphocytes. Hemoglobin is 11.0 g/dL and platelet count is 122,000/dL. He recalls being told 3 years previously that his white blood cell count was 48,000 during an emergency department visit for cellulitis.
• How is CLL diagnosed and staged?
CLL is often suspected when patients present with an elevated lymphocyte count. Presenting symptoms of CLL commonly include lymphadenopathy, an enlarged spleen, and constitutional or “B” symptoms such as fatigue, unintentional weight loss, or drenching night sweats. However, only 25% of patients are symptomatic at diagnosis [1]. Many patients with CLL are now diagnosed after a routine blood test, long before the disease is clinically apparent.
The diagnosis of CLL can be made from the peripheral blood and does not require a bone marrow biopsy. According to 2008 guidelines from the International Workshop on Chronic Lymphocytic Leukemia (IWCLL), diagnosis requires at least 5000/uL clonal B-lymphocytes in the peripheral blood. The clonality must be confirmed by immunophenotyping. At time of diagnosis the peripheral blood smear should be examined for the characteristic cells: small mature lymphocytes with a narrow rim of cytoplasm and dense nuclei consisting of clumped chromatin. Larger, atypical cells can be present as long as they do not exceed 55% of the total number of lymphocytes [6].
The immunophenotype of CLL includes aberrant expression of CD5 and a T-cell antigen, along with the characteristic B-cell antigens CD19, CD20, and CD23. The leukemic clone may be either kappa or lambda light chain restricted. Expression of surface immunoglobulin, CD20, and CD79a is typically low compared to that of normal B cells, although there can be some variability in the immunophenotype [6].
Care should be taken to exclude other malignancies with a similar morphology. Leukemic phase mantle cell lymphoma, other low grade lymphomas, and hairy cell leukemia are commonly mistaken for CLL. Immunophenotyping and cytogenetics are usually sufficient to differentiate these. Testing for a balanced translocation involving chromosomes 11 and 14 to exclude mantle cell lymphoma can be helpful, as both CLL and mantle cell lymphoma can appear morphologically similar and share immunophenotypic features (CD5+/CD19+).
Case Continued
The patient’s peripheral blood is drawn for routine immunophenotyping as well as cytogenetic and molecular testing. When he returns to discuss the results 10 days later, he learns that peripheral blood immunophenotyping demonstrates a dim kappa restricted monoclonal population of B-cells that expressed CD19, CD20(dim), CD23, CD38, CD5, and CD43. The lymphocytes are negative for CD10, FMC7, and CD79b, consistent with a CLL immunophenotype. This patient fulfills diagnostic criteria for CLL and has Rai stage II or intermediate-risk disease. Interphase cytogenetic studies of the peripheral blood demonstrate deletions of chromosomes 11q22.3 and 13q14.3. The immunoglobulin heavy chain gene (IGHV) is unmutated.
• How can a CLL patient’s disease risk be characterized?
Historically, staging at diagnosis, pattern of bone marrow infiltration, and response to therapy were used to gauge prognosis. In more recent years, cytogenetic and molecular testing methods have been developed to augment risk stratification. Testing of prognostic significance that influences clinical management includes IGHV mutational status and interphase cytogenetics using FISH [3,12–14]. Expression of ZAP-70 and CD38 are both independent predictors of poorer prognosis in CLL but are not recommended for routine clinical use. Standardized methodology for the measurement of Zap-70 in particular limits the utility of that test in routine clinical practice [15]. Performed at diagnosis, a time when many patients are asymptomatic, cytogenetic testing with FISH and IGHV mutational analysis can predict time to first treatment and increasingly identify high-risk patients for whom investigational early intervention approaches may be considered [16]. While cytogenetic testing has utility at time of diagnosis, it should be considered necessary prior to deciding on the first-line treatment.
Cytogenetics are also important in predicting response to therapy. For instance, patients with deletion(11q) disease have improved survival when treated with regimens containing an alkylating agent [18]. Deletion(17p) patients respond poorly to traditional cytotoxic agents, and treatments with alternate mechanisms of action should be used [5,19]. The gene for tumor suppressor protein TP53 is encoded in this region of chromosome 17, thus treatment with agents that act independent of pathways involving TP53 are preferred [20].
In addition to cytogenetic testing, quantization of somatic mutations in the gene encoding the variable region of the immune globulin heavy chain gene (IGHV) can help define disease-specific risk. When greater than 98% sequence homology is seen, the gene is considered IGHV unmutated. Patients with an unmutated IGHV have worse overall survival. In one study of Rai stage 0 CLL patients, those with an unmutated IGHV had a survival of only 95 months, compared with 293 months in the mutated group [12].
• When should CLL be treated?
CLL is not curable with current standard therapies, and starting treatment at time of diagnosis for early stage, asymptomatic, CLL patients does not improve overall survival and adds treatment-related toxicities [21,22]. Consequently, the decision to treat is based on treating or preventing complications from the disease, and observation is recommended for most asymptomatic, early-stage patients [6]. Because median survival in CLL is often measured in years, deferring treatment can limit both the short- and long-term complications of therapy, especially the significant risk of secondary malignancies associated with some therapies [23]. However, deferring treatment can significantly impact both a patient’s emotional well-being and quality of life, which should be kept in mind when first discussing the rationale for observation with asymptomatic patients [24].
causes.
For patients with anemia, neutropenia, or thrombocytopenia that is autoimmune in nature, treatment should typically begin with corticosteroids, as it would for non-CLL associated cases of autoimmune cytopenias. If steroids are not effective, second-line treatments appropriate for the situation are generally employed, including intravenous immunoglobulin, cyclosporine, azathioprine, and splenectomy. Rituximab has also been shown to be effective in steroid-refractory cases of autoimmune hemolytic anemia associated with CLL [26]. Only if cytopenias are refractory to appropriate second-line therapy should CLL-directed treatments be considered, assuming there are no other indications to treat the underlying CLL [6]. Bone marrow biopsy can be helpful in differentiating autoimmune cytopenias from marrow failure due to CLL infiltration.
• What treatments are most appropriate for young, fit patients?
For younger patients who are in good general health, the standard treatment choice is combination chemoimmunotherapy. While single agent therapies can effectively palliate symptoms in most cases, they do not offer a survival benefit. Treatment with chemoimmunotherapy, consisting of cytotoxic chemotherapy given in combination with an anti-CD20 monoclonal antibody (generally rituximab), results in high response rates and conveys an advantage with respect to both progression-free survival (PFS) and overall survival (OS). Several chemoimmunotherapy regimens are commonly used.
As compared to fludarabine alone, frontline therapy with the combination of rituximab and fludarabine (FR) results in both a higher overall response rate (84% compared with 63% with fludarabine alone) and more complete responses (38% compared with 20% with fludarabine alone). The probability of PFS at 2 years is also better with FR: 67% compared to 45% with single agent fludarabine [28,29]. Neutropenia is more common with the combination regimen but does not appear to increase the rate of infection. Rituximab infusion reactions are commonly observed, so a stepped-up dosing schedule was developed to decrease their incidence and severity.
Fludarabine, cyclophosphamide, and rituximab (FCR) is another highly effective regimen. This combination has similar efficacy to FR with a 90% to 95% overall response rate (ORR) and 44% to 70% complete response (CR) rate [19,30]. Long-term results with this regimen are favorable; 6-year OS of 77% and median time to progression of 80 months have been reported in a follow-up study [31]. However, hematologic toxicity, including severe neutropenia, is common, and many patients are unable to complete all planned therapy [19]. The addition of cyclophosphamide does appear to be especially important for patients with a deletion(11q). Several clinical trials have consistently found that measures of response and survival are improved for deletion(11q) patients receiving an alkylating agent in addition to a nucleoside analogue [18,32,33]. Outcomes in patients with deletion(17p) disease remain poor after FCR; this subset demonstrates the shortest PFS at only 11.5 months [19].
A more recently developed chemoimmunotherapy option for younger, fit patients is bendamustine and rituximab (BR). Bendamustine has structural similarities to both alkylating agents and purine analogues, and is significantly more efficacious than chlorambucil as a single agent [34]. The combination is generally well tolerated, and a phase 2 trial of the combination reported an overall response rate (ORR) of 88.0% [32]. Notably, when the results were examined by genetic risk group, the regimen remained effective for deletion(11q) patients, who achieved overall and CR rates of 90% and 40%, respectively. Unfortunately, only 37.5% of deletion(17p) patients responded, and no patients achieved a CR [32].
The risk for therapy-related neoplasms should be taken into account when selecting initial therapy given the expected long-term survival of most CLL patients. About 8 out of 300 FCR-treated patients developed a therapy-related neoplasm in one study [31]. Treatment with FR, which does not include an alkylating agent, does not appear to have the same risk. In a study reporting long-term follow-up on 104 patients treated with FR, none developed a therapy related neoplasm [35]. Risks associated with bendamustine have not been well characterized but appear to be lower than FC. While inclusion of an alkylating agent is important for deletion(11q) patients, it is not clear if other patients similarly benefit, thus meriting the potentially increased risk for second cancers.
Fortunately, the choice among these similarly effective regimens will soon be based on high-quality, comparative data. FCR and BR have now been directly compared as a first-line treatment in the German CLL Study Group CLL10 trial. At interim analysis, both regimens had the same ORR and 2-year OS. However, CRs were less common in the BR group (38.1% versus 47.4% with FCR) and PFS was likewise inferior. Expectedly, the FCR group experienced more myelotoxicity and infections. The rate of severe neutropenia with FCR was higher at 81.7% compared to only 56.8% with BR [36]. This may be an important consideration when selecting a regimen for individual patients. Baseline renal function may influence choice as well. The active metabolite of fludarabine is eliminated through the kidneys and patients with decreased renal function have been excluded from clinical trials of FCR [19,37]. The phase 2 study of BR included patients with impaired renal function and 35% of participants had a creatinine clearance of less than 70 mL/min. It is notable that increased toxicity was seen in this subset, including higher rates of myelosuppression and infection [32]. As few direct comparisons have been done, the choice between effective first-line chemoimmunotherapy regimens can be difficult. The final results of the CLL 10 trial, as well as the now completed CALGB 10404 trial comparing FCR to FR, will provide new evidence regarding the relative risks and benefits of these regimens, particularly for patients without high-risk chromosomal abnormalities.
• What treatments are most effective for patients with deletion(17p) CLL?
As noted above, deletion(17p) CLL responds poorly to standard treatments. This relative lack of durable response to chemoimmunotherapy appears attributable to loss of function of the tumor suppressor protein TP53 which is encoded in the affected area [20,32,38]. In vivo evidence suggests that fludarabine works through a TP53-dependent mechanism, which likely explains the poor results obtained when deletion(17p) patients are treated with fludarabine-based combinations [38]. Patients harboring deletion(17p) or TP53 mutations should thus be referred for participation in clinical trials or allogeneic stem cell transplantation [17,27].
If initial treatment of a patient with deletion(17p) begins outside of a clinical trial, it should ideally be comprised of agents that have a TP53-independent mechanism of action [20]. Alemtuzumab, a humanized monoclonal antibody against the CD52 antigen expressed on the surface of normal and malignant B- and T-lymphocytes, demonstrated ORR of 33% to 50% in studies of patients with relapsed and refractory CLL [39–42]. A retrospective analysis found that similar outcomes were seen in those who had a TP53 mutation or deletion(17p). A subsequent study of previously untreated CLL patients randomized to treatment with 12 weeks of alemtuzumab or chlorambucil found that alemtuzumab-treated deletion(17p) patients had an ORR of 64% and median PFS of 10.7 months [43]. Alemtuzumab is therefore a rational choice for first-line therapy in this population. Hematologic toxicity is frequent, however, and all patients must receive prophylaxis against and monitoring for reactivation of CMV infection [43]. Infusion reactions are common but may be reduced by subcutaneous administration without apparent loss of efficacy [42,44]. While alemtuzumab is no longer marketed in the United States for the indication of CLL, it is available free of charge from the manufacturer [45].
High-dose methylprednisolone with rituximab (HDMP-R) has also been successfully used as both salvage and first-line therapy in this group. As salvage therapy, responses were seen in greater than 90% of patients, including over 50% of deletion(17p) patients [46-48]. In treatment-naïve CLL, the ORR was 96% [49], although data for patients with deletion 17p is limited in the frontline setting. Myelotoxicity attributable to the regimen is modest, but good antimicrobial prophylaxis is warranted, as well as close monitoring for hyperglycemia in at-risk patients.
• How is treatment modified for older or less fit patients?
For patients older than 70, or those who have significant comorbidities, effective therapies are still available. As most new diagnoses of CLL are made in patients older than 65, age is but one important factor determining an individual patient’s ability to tolerate treatment. The German CLL Study Group has usefully classified elderly patients into 3 treatment groups based on fitness and goals of care. The first group of medically fit patients with a normal life expectancy, sometimes referred to as the “go go” group, generally tolerate standard chemoimmunotherapy. A second group of older patients with significant life-limiting comorbid conditions—the so-called “no go” patients —should be offered best supportive care rather than CLL-directed treatment. A third group of “slow go” patients falls in between these two; these patients have comorbidities with variable life expectancy and will likely tolerate and benefit from CLL-directed therapy [50].
While some older patients can safely receive chemoimmunotherapy at standard doses and schedules, FCR can prove intolerable for even the medically fit elderly. Because inferior outcomes have been reported among patients older than 70 [30,31], a reduced-dose FCR regimen (FCR-lite) has been studied. Doses of fludarabine and cyclophosphamide were reduced by 20% and 40% respectively and dosing frequency of rituximab was increased. The CR rate was favorable at 77%, the rate of severe neutropenia was reduced to only 13%, and most patients completed all planned therapy [51]. Alternatively, the combination of pentostatin, cyclophosphamide, and rituximab (PCR) has also been successfully used in older patients. The overall and CR rates, 91% and 63% respectively, were durable at 26 months of follow-up. Importantly, there was no statistically significant difference in response or toxicity among the 28% of patients older than 70 [52,53].
For less fit patients, chlorambucil remains a reasonable option. Chlorambucil, a well-tolerated oral alkylating agent, has been used as a frontline therapy in CLL for decades. Chlorambucil has demonstrated consistent response rates in at least 4 clinical trials and is an appropriate option for patients who cannot tolerate more intensive therapy [54]. When a multicenter phase III trial compared it directly to fludarabine in patients over 65, the PFS and OS were no different despite favorable response rates in fludarabine-treated patients [55]. The effectiveness of single-agent chlorambucil can be improved, and the tolerability maintained, with the addition of a CD20-directed monoclonal antibody [56]. Obinutuzumab, a glycolengineered type II antibody against CD20, has recently been shown to improve treatment efficacy when used in combination with chlorambucil [57]. The CLL11 trial randomized patients with comorbid conditions to 1 of 3 treatments: single-agent chlorambucil, chlorambucil with rituximab (R-Clb), or chlorambucil with obinutuzumab (G-Clb). Both chemoimmunotherapy combinations outperformed chlorambucil alone, but the inclusion of obinutuzumab was associated with higher CR rates and longer PFS than rituximab, although infusion reactions and neutropenia were more common in the obinutuzumab arm [57]. Based on this result, the US Food and Drug Administration has now approved obinutuzumab for use in combination with chlorambucil as frontline therapy. While regulatory approval is without restriction with respect to patient age or fitness, a chlorambucil backbone remains most appropriate for older patients and/or those with significant comorbidities.
• What therapies are currently under development?
Numerous targeted treatments and novel immunotherapies are under active investigation in CLL. With greater specificity for CLL, these emerging agents offer the possibility of more effective yet less toxic treatments that will undoubtedly change the landscape for future CLL therapy. These agents are currently most studied as salvage therapies, and given their targeted mechanism of action can be highly effective in relapsed and refractory patients who frequently harbor poor risk cytogenetic abnormalities such as deletion(17p). Data for these agents as initial treatment is limited. Ongoing clinical trials employing these newer agents will need to be reported before these drugs can be recommended as frontline therapies.
Frontline experience with the oral immunomodulatory agent lenalidomide is more extensive. Lenalidomide offers convenient daily dosing and a favorable toxicity profile. When given on a continuous dosing schedule to patients who were 65 years old or older, the ORR was 65%, and 88% of patients were still alive at 2 years’ follow-up. The quality of response continued to improve beyond 18 months of treatment. Neutropenia, the most common severe toxicity, complicated about a third of cycles. Tumor flare attributable to immune activation was also seen, but in most cases was low-grade and did not require intervention [58,59]. While life-threatening tumor lysis syndrome and tumor flare have been seen with lenalidomide in CLL, such concerns are largely abrogated by a lower starting dose and careful intrapatient dose titration [60]. Lenalidomide has also been combined with rituximab and yielded promising results. Sixty-nine treatment-naïve patients were treated with escalating doses of lenalidomide along with rituximab infusions starting at the end of cycle 1 in a phase 2 study. They achieved an 88% ORR with 16% CRs. Toxicities were generally manageable, but patients over 65 were less likely to reach higher doses of lenalidomide or complete all planned treatment cycles [61]. Unfortunately, the FDA recently halted accrual to a phase 3 frontline clinical trial comparing lenalidomide to chlorambucil due to excess mortality in the lenalidomide arm among patients over the age of 80 [62]. More detailed outcomes from that study should be forthcoming.
Perhaps the most remarkable recent advance in CLL medicine, however, is the advent of orally bioavailable small molecule inhibitors of the B-cell receptor (BCR) signaling pathway. BCR signaling plays a vitally important role in supporting the growth and survival of malignant B-cells, activating a number of downstream kinases (Syk, Btk, PI3K, among others) which are potential therapeutic targets. Proof of principle for this approach was demonstrated with the Syk inhibitor fostamatinib in a phase 1/2 trial enrolling patients with B-cell non-Hodgkin lymphoma and CLL. CLL/SLL patients had the highest response rates of any subgroup in that study, with 6 out of 11 patients responding [63]. In a subsequent phase 1b study of the Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib, durable partial remissions were reported in more than 70% of multiply relapsed and refractory patients, including genetically high-risk patients [64–66]. Ibrutinib appears safer and better tolerated than traditional chemoimmunotherapy in the relapsed setting; consequently, it is now being studied as a first-line therapy both alone and in combination with other agents [67]. Other BCR signaling agents under study, such as the phosphatidylinositol 3-kinase inhibitor idelalisib, demonstrate similar safety and high response rates across both genetic risk and patient age groups [68].
New targeted drugs are not limited to the BCR signaling pathway. ABT-199 inhibits B-cell leukemia/lymphoma 2 (BCL-2), which is an anti-apoptotic protein in the cell death pathway, and has demonstrated remarkable clinical efficacy in relapsed and refractory CLL patients [69]. As more experience is gained with these targeted agents, it is expected that they will be rapidly incorporated into frontline therapies. However, these agents are just now being studied in comparison to standard initial treatments, such as FCR, and it is not yet clear they will offer an advantage over current chemoimmunotherapy in this setting [70–72]. Since these single agents typically do not induce complete remissions, and require indefinite therapy to maintain response, optimal combination therapies are under intensive investigation.
Case Conclusion
The patient and his physician elect to begin treatment owing to symptomatic cervical lymphadenopathy and massive splenomegaly. Given the presence of a deletion(11q) abnormality, but hoping to limit the risk for both short- and long-term toxicities, this younger, fit patient is treated with 6 cycles of bendamustine and rituximab. At the conclusion of treatment, neither the cervical lymph nodes nor spleen remain palpable. His blood counts have also normalized, with a white blood cell count of 4700 with 8.1% lymphocyotes, hemoglobin of 14.3 gm/dL, and platelets of 151,000/dL.
Summary
CLL follows a chronic course requiring treatment at variable intervals. Both genetic risk features and patient factors should be considered when determining initial therapy. Cytogenetic and molecular testing can characterize the likelihood of treatment success, information useful for treatment planning. Chemoimmunotherapy is highly effective for most patients, including patients with deletion(11q) CLL, where the inclusion of an alkylating agent in frontline therapy alters the natural history of disease. However, patients with deletion(17p) and or TP53-mutated disease respond poorly to standard treatment and should be considered for investigational therapies [73]. Novel approaches to CLL therapy, most notably immunotherapies and BCR-targeted agents, hold the promise to further improve outcomes, particularly for the highest risk patients and those elderly and/or infirm patients who tolerate chemotherapy poorly. Frontline therapy should rapidly evolve as emerging agents enter advanced phase investigation.
Corresponding author: Jeffrey Jones, MD, MPH, Div. of Hematology, Ohio State University, A350B Starling Loving Hall, 320 West 10th Ave., Columbus, OH 43210, jeffrey.jones@osumc.edu.
Financial disclosures: Dr. Jones disclosed that he is on the advisory boards and has received research support from Genentech, Pharmacyclics, and Gilead.
Author contributions: conception and design, KAR, JAJ; analysis and interpretation of data, KAR, JAJ; drafting of article, KAR, JAJ; critical revision of the article, KAR, JAJ.
1. Redaelli A, Laskin BL, Stephens JM, et al. The clinical and epidemiological burden of chronic lymphocytic leukaemia. Eur J Cancer Care (Engl) 2004;13:279–87.
2. Dores GM, Anderson WF, Curtis RE, et al. Chronic lymphocytic leukaemia and small lymphocytic lymphoma: overview of the descriptive epidemiology. Br J Haematol 2007;139:809–19.
3. Döhner H, Stilgenbauer S, Benner A, et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med 2000;343:1910–6.
4. Zent CS, Kyasa MJ, Evans R, Schichman SA. Chronic lymphocytic leukemia incidence is substantially higher than estimated from tumor registry data. Cancer 2001;92:1325–30.
5. Byrd JC, Gribben JG, Peterson BL, et al. Select high-risk genetic features predict earlier progression following chemoimmunotherapy with fludarabine and rituximab in chronic lymphocytic leukemia: justification for risk-adapted therapy. J Clin Oncol 2006;24:437–43.
6. Hallek M, Cheson BD, Catovsky D, et al. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood 2008;111:5446–56.
7. Rawstron AC, Bennett FL, O'Connor SJ, et al. Monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia. N Engl J Med 2008;359:575–83.
8. Rai KR, Sawitsky A, Cronkite EP, et al. Clinical staging of chronic lymphocytic leukemia. Blood 1975;46:219–34.
9. Binet JL, Auquier A, Dighiero G, et al. A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer 1981;48:198–206.
10. Binet JL, Lepoprier M, Dighiero G, et al. A clinical staging system for chronic lymphocytic leukemia: prognostic significance. Cancer 1977:40:855–64.
11. Eichhorst BF, Fischer K, Fink AM, et al. Limited clinical relevance of imaging techniques in the follow-up of patients with advanced chronic lymphocytic leukemia: results of a meta-analysis. Blood 2011;117:1817–21.
12. Hamblin TJ, Davis Z, Gardiner A, et al. Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999;94:1848–54.
13. Crespo M, Bosch F, Villamor N, et al. ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia. N Engl J Med 2003;348:
1764–75.
14. Hamblin TJ, Orchard JA, Ibbotson RE, et al. CD38 expression and immunoglobulin variable region mutations are independent prognostic variables in chronic lymphocytic leukemia, but CD38 expression may vary during the course of the disease. Blood 2002;99:1023–9.
15. Rassenti LZ, Kipps TJ. Clinical utility of assessing ZAP-70 and CD38 in chronic lymphocytic leukemia. Cytometry B Clin Cytom 2006;70:209–13.
16. Wierda WG, O'Brien S, Wang X, et al. Multivariable model for time to first treatment in patients with chronic lymphocytic leukemia. J Clin Oncol 2011;29:4088–95.
17. Schetelig J, van Biezen A, Brand R, et al. Allogeneic hematopoietic stem-cell transplantation for chronic lymphocytic leukemia with 17p deletion: a retrospective European Group for Blood and Marrow Transplantation analysis. J Clin Oncol 2008;26:5094–100.
18. Ding W, Ferrajoli A. Evidence-based mini-review: the role of alkylating agents in the initial treatment of chronic lymphocytic leukemia patients with the 11q deletion. Hematology Am Soc Hematol Educ Program 2010;2010:90–2.
19. Hallek M, Fischer K, Fingerle-Rowson G, et al. Addition of rituximab to fludarabine and cyclophosphamide in patients with chronic lymphocytic leukaemia: a randomised, open-label, phase 3 trial. Lancet 2010;376:1164–74.
20. Badoux XC, Keating MJ, Wierda WG.What is the best frontline therapy for patients with CLL and 17p deletion? Curr Hematol Malig Rep 2011;6:36–46.
21. Dighiero G, Maloum K, Desablens B, et al. Chlorambucil in indolent chronic lymphocytic leukemia. French Cooperative Group on Chronic Lymphocytic Leukemia. N Engl J Med 1998;338:1506–14.
22. Chemotherapeutic options in chronic lymphocytic leukemia: a meta-analysis of the randomized trials. CLL Trialists' Collaborative Group. J Natl Cancer Inst 1999;91:861–8.
23. Morton LM, Curtis RE, Linet MS, et al. Second malignancy risks after non-Hodgkin's lymphoma and chronic lymphocytic leukemia: differences by lymphoma subtype. J Clin Oncol 2010;28:4935–44.
24. Shanafelt TD, Bowen D, Venkat C, et al. Quality of life in chronic lymphocytic leukemia: an international survey of 1482 patients. Br J Haematol 2007;139:255–64.
25. Baer MR, Stein RS, Dessypris EN. Chronic lymphocytic leukemia with hyperleukocytosis. The hyperviscosity syndrome. Cancer 1985;56:2865–9.
26. Gupta N, Kavuru S, Patel D, et al. Rituximab-based chemotherapy for steroid-refractory autoimmune hemolytic anemia of chronic lymphocytic leukemia. Leukemia 2002;16:2092–5.
27. National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology: non-hodgkin's lymphomas. Version 2.2013. Available at http://www.nccn.org/professionals/physician_gls/pdf/nhl.pdf.
28. Byrd JC, Rai K, Peterson BL, et al. Addition of rituximab to fludarabine may prolong progression-free survival and overall survival in patients with previously untreated chronic lymphocytic leukemia: an updated retrospective comparative analysis of CALGB 9712 and CALGB 9011. Blood 2005;105:49–53.
29. Byrd JC, Peterson BL, Morrison VA, et al. Randomized phase 2 study of fludarabine with concurrent versus sequential treatment with rituximab in symptomatic, untreated patients with B-cell chronic lymphocytic leukemia: results from Cancer and Leukemia Group B 9712 (CALGB 9712). Blood 2003;101:6–14.
30. Keating MJ, O'Brien S, Albitar M, et al. Early results of a chemoimmunotherapy regimen of fludarabine, cyclophosphamide, and rituximab as initial therapy for chronic lymphocytic leukemia. J Clin Oncol 2005;23:4079–88.
31. Tam CS, O'Brien S, Wierda W, et al. Long-term results of the fludarabine, cyclophosphamide, and rituximab regimen as initial therapy of chronic lymphocytic leukemia. Blood 2008;112:975–80.
32. Fischer K, Cramer P, Busch R, et al. Bendamustine in combination with rituximab for previously untreated patients with chronic lymphocytic leukemia: a multicenter phase II trial of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2012;30:3209–16.
33. Catovsky D, Richards S, Matutes E, et al. Assessment of fludarabine plus cyclophosphamide for patients with chronic lymphocytic leukaemia (the LRF CLL4 Trial): a randomised controlled trial. Lancet 2007;370:230–9.
34. Knauf WU, Lissichkov T, Aldaoud A, et al. Phase III randomized study of bendamustine compared with chlorambucil in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:4378–84.
35. Woyach JA, Ruppert AS, Heerema NA, et al. Chemoimmunotherapy with fludarabine and rituximab produces extended overall survival and progression-free survival in chronic lymphocytic leukemia: long-term follow-up of CALGB study 9712. J Clin Oncol 2011;29:1349–55.
36. Fink AM, et al., Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximabversus bendamustine and rituximabin previously untreated and physically fit patientswith advanced chronic lymphocytic leukemia: results of a planned interim analysis of the CLL10 Trial, an international, randomized study of the German CLL Study Group (GCLLSG). Blood 2013;122:526.
37. Gandhi V, Plunkett W. Cellular and clinical pharmacology of fludarabine. Clin Pharmacokinet 2002;41:93–103.
38. Rosenwald A, Chuang EY, Davis RE, et al. Fludarabine treatment of patients with chronic lymphocytic leukemia induces a p53-dependent gene expression response. Blood 2004;104:1428–34.
39. Keating MJ, Flinn I, Jain V, et al. Therapeutic role of alemtuzumab (Campath-1H) in patients who have failed fludarabine: results of a large international study. Blood 2002;99:3554–61.
40. Lozanski G, Heerema NA, Flinn IW, et al. Alemtuzumab is an effective therapy for chronic lymphocytic leukemia with p53 mutations and deletions. Blood 2004;103:3278–81.
41. Osuji NC, Del Giudice I, Matutes E, et al, The efficacy of alemtuzumab for refractory chronic lymphocytic leukemia in relation to cytogenetic abnormalities of p53. Haematologica 2005;90:1435–6.
42. Stilgenbauer S, Zenz T, Winkler D, et al. Subcutaneous alemtuzumab in fludarabine-refractory chronic lymphocytic leukemia: clinical results and prognostic marker analyses from the CLL2H study of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2009;27:3994–4001.
43. Hillmen P, Skotnicki AB, Robak T, et al. Alemtuzumab compared with chlorambucil as first-line therapy for chronic lymphocytic leukemia. J Clin Oncol 2007;25:5616–23.
44. Lundin J, Kimby E, Björkholm M, et al. Phase II trial of subcutaneous anti-CD52 monoclonal antibody alemtuzumab (Campath-1H) as first-line treatment for patients with B-cell chronic lymphocytic leukemia (B-CLL). Blood 2002;100:768–73.
45. Genzyme. US Campath Distribution Program. Cambridge, MA: Genzyme. Available at http://www.campath.com/.
46. Thornton PD, Matutes E, Bosanquet AG, et al. High dose methylprednisolone can induce remissions in CLL patients with p53 abnormalities. Ann Hematol 2003;82:759–65.
47. Bowen DA, Call TG, Jenkins GD, et al. Methylprednisolone-rituximab is an effective salvage therapy for patients with relapsed chronic lymphocytic leukemia including those with unfavorable cytogenetic features. Leuk Lymphoma 2007;48:2412–7.
48. Castro JE, Sandoval-Sus JD, Bole J, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of fludarabine refractory high-risk chronic lymphocytic leukemia. Leukemia 2008;22:2048–53.
49. Castro JE, James DF, Sandoval-Sus JD, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of chronic lymphocytic leukemia. Leukemia 2009;23:1779–89.
50. Eichhorst B, Goede V, Hallek M. Treatment of elderly patients with chronic lymphocytic leukemia. Leuk Lymphoma 2009;50:171–8.
51. Foon KA, Boyiadzis M, Land SR, et al. Chemoimmunotherapy with low-dose fludarabine and cyclophosphamide and high dose rituximab in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:498–503.
52. Kay NE, Geyer SM, Call TG, et al. Combination chemoimmunotherapy with pentostatin, cyclophosphamide, and rituximab shows significant clinical activity with low accompanying toxicity in previously untreated B chronic lymphocytic leukemia. Blood 2007;109:405–11.
53. Shanafelt TD, Lin T, Geyer SM, et al. Pentostatin, cyclophosphamide, and rituximab regimen in older patients with chronic lymphocytic leukemia. Cancer 2007;109:2291–8.
54. Catovsky D, Else M, Richards S. Chlorambucil--still not bad: a reappraisal. Clin Lymphoma Myeloma Leuk 2011;11 Suppl 1:S2–6.
55. Eichhorst BF, Busch R, Stilgenbauer S, et al. First-line therapy with fludarabine compared with chlorambucil does not result in a major benefit for elderly patients with advanced chronic lymphocytic leukemia. Blood 2009;114:3382–91.
56. Laurenti L, Vannata B, Innocenti I, et al. Chlorambucil plus rituximab as front-line therapy in elderly/unfit patients affected by b-cell chronic lymphocytic leukemia: results of a single-centre experience. Mediterr J Hematol Infect Dis 2013;5:e2013031.
57. Goede V, Fischer K, Busch R, et al. Obinutuzumab plus chlorambucil in patients with CLL and coexisting conditions. N Engl J Med 2014 Jan 8. [Epub ahead of print].
58. Badoux XC, Keating MJ, Wen S, et al. Lenalidomide as initial therapy of elderly patients with chronic lymphocytic leukemia. Blood 2011;118:3489–98.
59. Strati P, Keating MJ, Wierda WG, et al. Lenalidomide induces long-lasting responses in elderly patients with chronic lymphocytic leukemia. Blood 2013;122:734–7.
60. Moutouh-de Parseval LA, Weiss L, DeLap RJ, et al. Tumor lysis syndrome/tumor flare reaction in lenalidomide-treated chronic lymphocytic leukemia. J Clin Oncol 2007;25:5047.
61. James DF, Brown JR, Werner L, et al. Lenalidomide and rituximab for the initial treatment of patients with chronic lymphocytic leukemia (CLL): a multicenter study of the CLL Research Consortium. ASH Annual Meeting Abstracts 2011;118:291.
62. US Food and Drug Administration. FDA halts clinical trial of drug Revlimid (lenalidomide) for chronic lymphocytic leukemia due to safety concerns. Available at http://www.fda.gov/Drugs/DrugSafety/ucm361444.htm.
63. Friedberg JW, Sharman J, Sweetenham J, et al. Inhibition of Syk with fostamatinib disodium has significant clinical activity in non-Hodgkin lymphoma and chronic lymphocytic leukemia. Blood 2010;115:2578–85.
64. Byrd JC, Furman RR, Coutre SE, et al. Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 2013;369:32–42.
65. Farooqui M, Aue G, Valdez J, et al. Single agent ibrutinib (PCI-32765) achieves equally good and durable responses in chronic lymphocytic leukemia (CLL) patients with and without deletion 17p. Blood 2013;122:673.
66. Byrd JC, Furman RR, Coutre S, et al. The Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib (PCI-32765) monotherapy demonstrates long-term safety and durability of response in chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) patients in an open-label extension study. Blood 2013;122:4163.
67. Brown JR, Barrientos JC, Barr PM, et al. Ibrutinib in combination with bendamustine and rituximab is active and tolerable in patients with relapsed/refractory CLL/SLL: final results of a phase 1b study. ASH Annual Meeting Abstracts 2013.
68. O'Brien SM, Lamanna N, Kipps TJ, et al. A phase II study of the selective phosphatidylinositol 3-kinase delta (PI3K{delta}) inhibitor idelalisib (GS-1101) in combination with rituximab (R) in treatment-naive patients (pts) ≥ 65 years with chronic lymphocytic leukemia (CLL) or small lymphocytic lymphoma (SLL). J Clin Oncol 2013;31(15 Suppl); Abstract 7005.
69. Seymour JF, Davids MS, Pagel JM, et al. Bcl-2 Inhibitor ABT-199 (GDC-0199) monotherapy shows anti-tumor activity including complete remissions in high-risk relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL). Blood 2013;122:872.
70. Rituxumab and bendamustine hydrochloride, rituxumab and ibrutunib, or ibrutinib alone in treating older patients with previously untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT01886872?term=ibrutinib+cll&rank=8.
71. A multicenter, open-label, phase 3 study of the bruton's tyrosine kinase inhibitor pci-32765 versus chlorambucil in patients 65 years of older with treatment-naive chronic lymphocytic leukemia or small lymphocytic lymphoma (RESONATE-2) Available at http://clinicaltrials.gov/ct2/show/NCT01722487?term=ibrutinib+cll&rank=12.
72. Ibrutinib and rituximab compared with fludarabine phosphate, cyclophosphamide, and rituxumab in treating patients with untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT02048813?term=ibrutinib+cll&rank=2.
73. Strati P, Keating MJ, O'Brien SM, et al. Outcomes of first-line treatment for chronic lymphocytic leukemia (CLL) with 17p deletion. J Clin Oncol 2013;31(15 suppl): Abstract 7102.
From the Division of Hematology, Ohio State University, Columbus, OH.
Abstract
- Objective: To describe the diagnosis and initial management of chronic lymphocytic leukemia (CLL), including first-line treatment options.
- Methods: Case presentation and review of the literature.
- Results: Most CLL patients demonstrate a chronic, relapsing and remitting course with intervals of months to years between treatments. Recent advances in genetic and molecular markers for risk stratification of CLL significantly impact how clinicians determine prognosis and predict response to treatment for patients with newly diagnosed disease. This information, along with patient factors such as age and health status, should be considered when formulating an initial treatment strategy. Combinations of chemotherapy and immunotherapy offer the longest progression-free survival and overall survival benefit yet reported. For elderly patients or those with significant comorbidities who may not tolerate standard chemoimmunotherapy, less intensive but still effective therapies now exist. Patients with the highest risk disease, such as those with deletions of chromosome 17p, respond poorly to conventional treatment and should be referred to experienced centers where investigational therapies and allogeneic stem cell transplantation are available.
- Conclusion: Both disease characteristics and patient factors should guide the selection among the various effective therapies for CLL. While chemoimmunotherapy is the most effective treatment developed to date, its use may become less prevalent as newer agents are incorporated into initial and relapse treatment algorithms.
Chronic lymphocytic leukemia (CLL) is a chronic malignancy of B-lymphocytes demonstrating a heterogeneous clinical course ranging from indolent to more rapidly progressive. The chief clinical feature is an elevated peripheral blood lymphocyte count, and patients can demonstrate lymphadenopathy, splenomegaly, hepatomegaly, constitutional symptoms, and in late stages bone marrow failure. It is the most common leukemia among adults in the Western world, accounting for between 22% to 30% of new leukemia diagnoses worldwide [1]. Recent incidence rates in the United States are 3.83 cases per 100,000 person-years [2]. The incidence of CLL increases with age, and most new cases are diagnosed in persons 65 years of age or older [1,2]. As reported 5-year survival rates are between 68% and 81% with a median survival of 10 years in some series, the prevalence is significantly higher than the incidence [3]. However, this may even be an underestimate of the population burden of disease, as many cases are not reported to tumor registries [4].
Many patients with CLL are asymptomatic and do not require treatment until years after diagnosis. In these cases a watch and wait approach is taken. The typical natural history of CLL is characterized by periods of effective treatment when required, followed by treatment-free intervals of several years in many cases. However, this can be misleading, as the clinical course for any individual patient is highly variable. Development of cytogenetic and molecular testing has allowed for identification of patients with a higher risk of progression and lower response rates to traditional cytotoxic treatments [5]. For example, depending on chromosomal abnormalities present, median survival can vary from 32 to 133 months [3].
The assessment of underlying disease risk thus provides important information when considering a treatment approach and should be routinely performed for newly diagnosed patients. While the development of highly effective chemoimmunotherapy has allowed most groups of CLL patients to live for many years, some groups do not enjoy the same survival. Recent advances in CLL treatment seek to abrogate such adverse risk factors, thereby improving the survival for all patients with CLL. Given the expected survival of years for most CLL patients, frontline treatment planning must be done in the context of a long-term treatment strategy keeping the risk for late toxicities, such as secondary malignancies, in mind.
Case Study
Initial Presentation
A 50-year-old man is referred for evaluation of cervical lymphadenopathy that had progressed over the prior 6 months. He denies associated symptoms of fatigue, fevers, night sweats, or unintentional weight loss but does report early satiety. On examination there are multiple mobile, enlarged cervical lymph nodes bilaterally. Axillary lymph nodes are likewise enlarged. The liver edge is not palpable, but the spleen is palpable below the belt line. Complete blood count reveals a white blood cell count of 196,000 with 97% lymphocytes. Hemoglobin is 11.0 g/dL and platelet count is 122,000/dL. He recalls being told 3 years previously that his white blood cell count was 48,000 during an emergency department visit for cellulitis.
• How is CLL diagnosed and staged?
CLL is often suspected when patients present with an elevated lymphocyte count. Presenting symptoms of CLL commonly include lymphadenopathy, an enlarged spleen, and constitutional or “B” symptoms such as fatigue, unintentional weight loss, or drenching night sweats. However, only 25% of patients are symptomatic at diagnosis [1]. Many patients with CLL are now diagnosed after a routine blood test, long before the disease is clinically apparent.
The diagnosis of CLL can be made from the peripheral blood and does not require a bone marrow biopsy. According to 2008 guidelines from the International Workshop on Chronic Lymphocytic Leukemia (IWCLL), diagnosis requires at least 5000/uL clonal B-lymphocytes in the peripheral blood. The clonality must be confirmed by immunophenotyping. At time of diagnosis the peripheral blood smear should be examined for the characteristic cells: small mature lymphocytes with a narrow rim of cytoplasm and dense nuclei consisting of clumped chromatin. Larger, atypical cells can be present as long as they do not exceed 55% of the total number of lymphocytes [6].
The immunophenotype of CLL includes aberrant expression of CD5 and a T-cell antigen, along with the characteristic B-cell antigens CD19, CD20, and CD23. The leukemic clone may be either kappa or lambda light chain restricted. Expression of surface immunoglobulin, CD20, and CD79a is typically low compared to that of normal B cells, although there can be some variability in the immunophenotype [6].
Care should be taken to exclude other malignancies with a similar morphology. Leukemic phase mantle cell lymphoma, other low grade lymphomas, and hairy cell leukemia are commonly mistaken for CLL. Immunophenotyping and cytogenetics are usually sufficient to differentiate these. Testing for a balanced translocation involving chromosomes 11 and 14 to exclude mantle cell lymphoma can be helpful, as both CLL and mantle cell lymphoma can appear morphologically similar and share immunophenotypic features (CD5+/CD19+).
Case Continued
The patient’s peripheral blood is drawn for routine immunophenotyping as well as cytogenetic and molecular testing. When he returns to discuss the results 10 days later, he learns that peripheral blood immunophenotyping demonstrates a dim kappa restricted monoclonal population of B-cells that expressed CD19, CD20(dim), CD23, CD38, CD5, and CD43. The lymphocytes are negative for CD10, FMC7, and CD79b, consistent with a CLL immunophenotype. This patient fulfills diagnostic criteria for CLL and has Rai stage II or intermediate-risk disease. Interphase cytogenetic studies of the peripheral blood demonstrate deletions of chromosomes 11q22.3 and 13q14.3. The immunoglobulin heavy chain gene (IGHV) is unmutated.
• How can a CLL patient’s disease risk be characterized?
Historically, staging at diagnosis, pattern of bone marrow infiltration, and response to therapy were used to gauge prognosis. In more recent years, cytogenetic and molecular testing methods have been developed to augment risk stratification. Testing of prognostic significance that influences clinical management includes IGHV mutational status and interphase cytogenetics using FISH [3,12–14]. Expression of ZAP-70 and CD38 are both independent predictors of poorer prognosis in CLL but are not recommended for routine clinical use. Standardized methodology for the measurement of Zap-70 in particular limits the utility of that test in routine clinical practice [15]. Performed at diagnosis, a time when many patients are asymptomatic, cytogenetic testing with FISH and IGHV mutational analysis can predict time to first treatment and increasingly identify high-risk patients for whom investigational early intervention approaches may be considered [16]. While cytogenetic testing has utility at time of diagnosis, it should be considered necessary prior to deciding on the first-line treatment.
Cytogenetics are also important in predicting response to therapy. For instance, patients with deletion(11q) disease have improved survival when treated with regimens containing an alkylating agent [18]. Deletion(17p) patients respond poorly to traditional cytotoxic agents, and treatments with alternate mechanisms of action should be used [5,19]. The gene for tumor suppressor protein TP53 is encoded in this region of chromosome 17, thus treatment with agents that act independent of pathways involving TP53 are preferred [20].
In addition to cytogenetic testing, quantization of somatic mutations in the gene encoding the variable region of the immune globulin heavy chain gene (IGHV) can help define disease-specific risk. When greater than 98% sequence homology is seen, the gene is considered IGHV unmutated. Patients with an unmutated IGHV have worse overall survival. In one study of Rai stage 0 CLL patients, those with an unmutated IGHV had a survival of only 95 months, compared with 293 months in the mutated group [12].
• When should CLL be treated?
CLL is not curable with current standard therapies, and starting treatment at time of diagnosis for early stage, asymptomatic, CLL patients does not improve overall survival and adds treatment-related toxicities [21,22]. Consequently, the decision to treat is based on treating or preventing complications from the disease, and observation is recommended for most asymptomatic, early-stage patients [6]. Because median survival in CLL is often measured in years, deferring treatment can limit both the short- and long-term complications of therapy, especially the significant risk of secondary malignancies associated with some therapies [23]. However, deferring treatment can significantly impact both a patient’s emotional well-being and quality of life, which should be kept in mind when first discussing the rationale for observation with asymptomatic patients [24].
causes.
For patients with anemia, neutropenia, or thrombocytopenia that is autoimmune in nature, treatment should typically begin with corticosteroids, as it would for non-CLL associated cases of autoimmune cytopenias. If steroids are not effective, second-line treatments appropriate for the situation are generally employed, including intravenous immunoglobulin, cyclosporine, azathioprine, and splenectomy. Rituximab has also been shown to be effective in steroid-refractory cases of autoimmune hemolytic anemia associated with CLL [26]. Only if cytopenias are refractory to appropriate second-line therapy should CLL-directed treatments be considered, assuming there are no other indications to treat the underlying CLL [6]. Bone marrow biopsy can be helpful in differentiating autoimmune cytopenias from marrow failure due to CLL infiltration.
• What treatments are most appropriate for young, fit patients?
For younger patients who are in good general health, the standard treatment choice is combination chemoimmunotherapy. While single agent therapies can effectively palliate symptoms in most cases, they do not offer a survival benefit. Treatment with chemoimmunotherapy, consisting of cytotoxic chemotherapy given in combination with an anti-CD20 monoclonal antibody (generally rituximab), results in high response rates and conveys an advantage with respect to both progression-free survival (PFS) and overall survival (OS). Several chemoimmunotherapy regimens are commonly used.
As compared to fludarabine alone, frontline therapy with the combination of rituximab and fludarabine (FR) results in both a higher overall response rate (84% compared with 63% with fludarabine alone) and more complete responses (38% compared with 20% with fludarabine alone). The probability of PFS at 2 years is also better with FR: 67% compared to 45% with single agent fludarabine [28,29]. Neutropenia is more common with the combination regimen but does not appear to increase the rate of infection. Rituximab infusion reactions are commonly observed, so a stepped-up dosing schedule was developed to decrease their incidence and severity.
Fludarabine, cyclophosphamide, and rituximab (FCR) is another highly effective regimen. This combination has similar efficacy to FR with a 90% to 95% overall response rate (ORR) and 44% to 70% complete response (CR) rate [19,30]. Long-term results with this regimen are favorable; 6-year OS of 77% and median time to progression of 80 months have been reported in a follow-up study [31]. However, hematologic toxicity, including severe neutropenia, is common, and many patients are unable to complete all planned therapy [19]. The addition of cyclophosphamide does appear to be especially important for patients with a deletion(11q). Several clinical trials have consistently found that measures of response and survival are improved for deletion(11q) patients receiving an alkylating agent in addition to a nucleoside analogue [18,32,33]. Outcomes in patients with deletion(17p) disease remain poor after FCR; this subset demonstrates the shortest PFS at only 11.5 months [19].
A more recently developed chemoimmunotherapy option for younger, fit patients is bendamustine and rituximab (BR). Bendamustine has structural similarities to both alkylating agents and purine analogues, and is significantly more efficacious than chlorambucil as a single agent [34]. The combination is generally well tolerated, and a phase 2 trial of the combination reported an overall response rate (ORR) of 88.0% [32]. Notably, when the results were examined by genetic risk group, the regimen remained effective for deletion(11q) patients, who achieved overall and CR rates of 90% and 40%, respectively. Unfortunately, only 37.5% of deletion(17p) patients responded, and no patients achieved a CR [32].
The risk for therapy-related neoplasms should be taken into account when selecting initial therapy given the expected long-term survival of most CLL patients. About 8 out of 300 FCR-treated patients developed a therapy-related neoplasm in one study [31]. Treatment with FR, which does not include an alkylating agent, does not appear to have the same risk. In a study reporting long-term follow-up on 104 patients treated with FR, none developed a therapy related neoplasm [35]. Risks associated with bendamustine have not been well characterized but appear to be lower than FC. While inclusion of an alkylating agent is important for deletion(11q) patients, it is not clear if other patients similarly benefit, thus meriting the potentially increased risk for second cancers.
Fortunately, the choice among these similarly effective regimens will soon be based on high-quality, comparative data. FCR and BR have now been directly compared as a first-line treatment in the German CLL Study Group CLL10 trial. At interim analysis, both regimens had the same ORR and 2-year OS. However, CRs were less common in the BR group (38.1% versus 47.4% with FCR) and PFS was likewise inferior. Expectedly, the FCR group experienced more myelotoxicity and infections. The rate of severe neutropenia with FCR was higher at 81.7% compared to only 56.8% with BR [36]. This may be an important consideration when selecting a regimen for individual patients. Baseline renal function may influence choice as well. The active metabolite of fludarabine is eliminated through the kidneys and patients with decreased renal function have been excluded from clinical trials of FCR [19,37]. The phase 2 study of BR included patients with impaired renal function and 35% of participants had a creatinine clearance of less than 70 mL/min. It is notable that increased toxicity was seen in this subset, including higher rates of myelosuppression and infection [32]. As few direct comparisons have been done, the choice between effective first-line chemoimmunotherapy regimens can be difficult. The final results of the CLL 10 trial, as well as the now completed CALGB 10404 trial comparing FCR to FR, will provide new evidence regarding the relative risks and benefits of these regimens, particularly for patients without high-risk chromosomal abnormalities.
• What treatments are most effective for patients with deletion(17p) CLL?
As noted above, deletion(17p) CLL responds poorly to standard treatments. This relative lack of durable response to chemoimmunotherapy appears attributable to loss of function of the tumor suppressor protein TP53 which is encoded in the affected area [20,32,38]. In vivo evidence suggests that fludarabine works through a TP53-dependent mechanism, which likely explains the poor results obtained when deletion(17p) patients are treated with fludarabine-based combinations [38]. Patients harboring deletion(17p) or TP53 mutations should thus be referred for participation in clinical trials or allogeneic stem cell transplantation [17,27].
If initial treatment of a patient with deletion(17p) begins outside of a clinical trial, it should ideally be comprised of agents that have a TP53-independent mechanism of action [20]. Alemtuzumab, a humanized monoclonal antibody against the CD52 antigen expressed on the surface of normal and malignant B- and T-lymphocytes, demonstrated ORR of 33% to 50% in studies of patients with relapsed and refractory CLL [39–42]. A retrospective analysis found that similar outcomes were seen in those who had a TP53 mutation or deletion(17p). A subsequent study of previously untreated CLL patients randomized to treatment with 12 weeks of alemtuzumab or chlorambucil found that alemtuzumab-treated deletion(17p) patients had an ORR of 64% and median PFS of 10.7 months [43]. Alemtuzumab is therefore a rational choice for first-line therapy in this population. Hematologic toxicity is frequent, however, and all patients must receive prophylaxis against and monitoring for reactivation of CMV infection [43]. Infusion reactions are common but may be reduced by subcutaneous administration without apparent loss of efficacy [42,44]. While alemtuzumab is no longer marketed in the United States for the indication of CLL, it is available free of charge from the manufacturer [45].
High-dose methylprednisolone with rituximab (HDMP-R) has also been successfully used as both salvage and first-line therapy in this group. As salvage therapy, responses were seen in greater than 90% of patients, including over 50% of deletion(17p) patients [46-48]. In treatment-naïve CLL, the ORR was 96% [49], although data for patients with deletion 17p is limited in the frontline setting. Myelotoxicity attributable to the regimen is modest, but good antimicrobial prophylaxis is warranted, as well as close monitoring for hyperglycemia in at-risk patients.
• How is treatment modified for older or less fit patients?
For patients older than 70, or those who have significant comorbidities, effective therapies are still available. As most new diagnoses of CLL are made in patients older than 65, age is but one important factor determining an individual patient’s ability to tolerate treatment. The German CLL Study Group has usefully classified elderly patients into 3 treatment groups based on fitness and goals of care. The first group of medically fit patients with a normal life expectancy, sometimes referred to as the “go go” group, generally tolerate standard chemoimmunotherapy. A second group of older patients with significant life-limiting comorbid conditions—the so-called “no go” patients —should be offered best supportive care rather than CLL-directed treatment. A third group of “slow go” patients falls in between these two; these patients have comorbidities with variable life expectancy and will likely tolerate and benefit from CLL-directed therapy [50].
While some older patients can safely receive chemoimmunotherapy at standard doses and schedules, FCR can prove intolerable for even the medically fit elderly. Because inferior outcomes have been reported among patients older than 70 [30,31], a reduced-dose FCR regimen (FCR-lite) has been studied. Doses of fludarabine and cyclophosphamide were reduced by 20% and 40% respectively and dosing frequency of rituximab was increased. The CR rate was favorable at 77%, the rate of severe neutropenia was reduced to only 13%, and most patients completed all planned therapy [51]. Alternatively, the combination of pentostatin, cyclophosphamide, and rituximab (PCR) has also been successfully used in older patients. The overall and CR rates, 91% and 63% respectively, were durable at 26 months of follow-up. Importantly, there was no statistically significant difference in response or toxicity among the 28% of patients older than 70 [52,53].
For less fit patients, chlorambucil remains a reasonable option. Chlorambucil, a well-tolerated oral alkylating agent, has been used as a frontline therapy in CLL for decades. Chlorambucil has demonstrated consistent response rates in at least 4 clinical trials and is an appropriate option for patients who cannot tolerate more intensive therapy [54]. When a multicenter phase III trial compared it directly to fludarabine in patients over 65, the PFS and OS were no different despite favorable response rates in fludarabine-treated patients [55]. The effectiveness of single-agent chlorambucil can be improved, and the tolerability maintained, with the addition of a CD20-directed monoclonal antibody [56]. Obinutuzumab, a glycolengineered type II antibody against CD20, has recently been shown to improve treatment efficacy when used in combination with chlorambucil [57]. The CLL11 trial randomized patients with comorbid conditions to 1 of 3 treatments: single-agent chlorambucil, chlorambucil with rituximab (R-Clb), or chlorambucil with obinutuzumab (G-Clb). Both chemoimmunotherapy combinations outperformed chlorambucil alone, but the inclusion of obinutuzumab was associated with higher CR rates and longer PFS than rituximab, although infusion reactions and neutropenia were more common in the obinutuzumab arm [57]. Based on this result, the US Food and Drug Administration has now approved obinutuzumab for use in combination with chlorambucil as frontline therapy. While regulatory approval is without restriction with respect to patient age or fitness, a chlorambucil backbone remains most appropriate for older patients and/or those with significant comorbidities.
• What therapies are currently under development?
Numerous targeted treatments and novel immunotherapies are under active investigation in CLL. With greater specificity for CLL, these emerging agents offer the possibility of more effective yet less toxic treatments that will undoubtedly change the landscape for future CLL therapy. These agents are currently most studied as salvage therapies, and given their targeted mechanism of action can be highly effective in relapsed and refractory patients who frequently harbor poor risk cytogenetic abnormalities such as deletion(17p). Data for these agents as initial treatment is limited. Ongoing clinical trials employing these newer agents will need to be reported before these drugs can be recommended as frontline therapies.
Frontline experience with the oral immunomodulatory agent lenalidomide is more extensive. Lenalidomide offers convenient daily dosing and a favorable toxicity profile. When given on a continuous dosing schedule to patients who were 65 years old or older, the ORR was 65%, and 88% of patients were still alive at 2 years’ follow-up. The quality of response continued to improve beyond 18 months of treatment. Neutropenia, the most common severe toxicity, complicated about a third of cycles. Tumor flare attributable to immune activation was also seen, but in most cases was low-grade and did not require intervention [58,59]. While life-threatening tumor lysis syndrome and tumor flare have been seen with lenalidomide in CLL, such concerns are largely abrogated by a lower starting dose and careful intrapatient dose titration [60]. Lenalidomide has also been combined with rituximab and yielded promising results. Sixty-nine treatment-naïve patients were treated with escalating doses of lenalidomide along with rituximab infusions starting at the end of cycle 1 in a phase 2 study. They achieved an 88% ORR with 16% CRs. Toxicities were generally manageable, but patients over 65 were less likely to reach higher doses of lenalidomide or complete all planned treatment cycles [61]. Unfortunately, the FDA recently halted accrual to a phase 3 frontline clinical trial comparing lenalidomide to chlorambucil due to excess mortality in the lenalidomide arm among patients over the age of 80 [62]. More detailed outcomes from that study should be forthcoming.
Perhaps the most remarkable recent advance in CLL medicine, however, is the advent of orally bioavailable small molecule inhibitors of the B-cell receptor (BCR) signaling pathway. BCR signaling plays a vitally important role in supporting the growth and survival of malignant B-cells, activating a number of downstream kinases (Syk, Btk, PI3K, among others) which are potential therapeutic targets. Proof of principle for this approach was demonstrated with the Syk inhibitor fostamatinib in a phase 1/2 trial enrolling patients with B-cell non-Hodgkin lymphoma and CLL. CLL/SLL patients had the highest response rates of any subgroup in that study, with 6 out of 11 patients responding [63]. In a subsequent phase 1b study of the Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib, durable partial remissions were reported in more than 70% of multiply relapsed and refractory patients, including genetically high-risk patients [64–66]. Ibrutinib appears safer and better tolerated than traditional chemoimmunotherapy in the relapsed setting; consequently, it is now being studied as a first-line therapy both alone and in combination with other agents [67]. Other BCR signaling agents under study, such as the phosphatidylinositol 3-kinase inhibitor idelalisib, demonstrate similar safety and high response rates across both genetic risk and patient age groups [68].
New targeted drugs are not limited to the BCR signaling pathway. ABT-199 inhibits B-cell leukemia/lymphoma 2 (BCL-2), which is an anti-apoptotic protein in the cell death pathway, and has demonstrated remarkable clinical efficacy in relapsed and refractory CLL patients [69]. As more experience is gained with these targeted agents, it is expected that they will be rapidly incorporated into frontline therapies. However, these agents are just now being studied in comparison to standard initial treatments, such as FCR, and it is not yet clear they will offer an advantage over current chemoimmunotherapy in this setting [70–72]. Since these single agents typically do not induce complete remissions, and require indefinite therapy to maintain response, optimal combination therapies are under intensive investigation.
Case Conclusion
The patient and his physician elect to begin treatment owing to symptomatic cervical lymphadenopathy and massive splenomegaly. Given the presence of a deletion(11q) abnormality, but hoping to limit the risk for both short- and long-term toxicities, this younger, fit patient is treated with 6 cycles of bendamustine and rituximab. At the conclusion of treatment, neither the cervical lymph nodes nor spleen remain palpable. His blood counts have also normalized, with a white blood cell count of 4700 with 8.1% lymphocyotes, hemoglobin of 14.3 gm/dL, and platelets of 151,000/dL.
Summary
CLL follows a chronic course requiring treatment at variable intervals. Both genetic risk features and patient factors should be considered when determining initial therapy. Cytogenetic and molecular testing can characterize the likelihood of treatment success, information useful for treatment planning. Chemoimmunotherapy is highly effective for most patients, including patients with deletion(11q) CLL, where the inclusion of an alkylating agent in frontline therapy alters the natural history of disease. However, patients with deletion(17p) and or TP53-mutated disease respond poorly to standard treatment and should be considered for investigational therapies [73]. Novel approaches to CLL therapy, most notably immunotherapies and BCR-targeted agents, hold the promise to further improve outcomes, particularly for the highest risk patients and those elderly and/or infirm patients who tolerate chemotherapy poorly. Frontline therapy should rapidly evolve as emerging agents enter advanced phase investigation.
Corresponding author: Jeffrey Jones, MD, MPH, Div. of Hematology, Ohio State University, A350B Starling Loving Hall, 320 West 10th Ave., Columbus, OH 43210, jeffrey.jones@osumc.edu.
Financial disclosures: Dr. Jones disclosed that he is on the advisory boards and has received research support from Genentech, Pharmacyclics, and Gilead.
Author contributions: conception and design, KAR, JAJ; analysis and interpretation of data, KAR, JAJ; drafting of article, KAR, JAJ; critical revision of the article, KAR, JAJ.
From the Division of Hematology, Ohio State University, Columbus, OH.
Abstract
- Objective: To describe the diagnosis and initial management of chronic lymphocytic leukemia (CLL), including first-line treatment options.
- Methods: Case presentation and review of the literature.
- Results: Most CLL patients demonstrate a chronic, relapsing and remitting course with intervals of months to years between treatments. Recent advances in genetic and molecular markers for risk stratification of CLL significantly impact how clinicians determine prognosis and predict response to treatment for patients with newly diagnosed disease. This information, along with patient factors such as age and health status, should be considered when formulating an initial treatment strategy. Combinations of chemotherapy and immunotherapy offer the longest progression-free survival and overall survival benefit yet reported. For elderly patients or those with significant comorbidities who may not tolerate standard chemoimmunotherapy, less intensive but still effective therapies now exist. Patients with the highest risk disease, such as those with deletions of chromosome 17p, respond poorly to conventional treatment and should be referred to experienced centers where investigational therapies and allogeneic stem cell transplantation are available.
- Conclusion: Both disease characteristics and patient factors should guide the selection among the various effective therapies for CLL. While chemoimmunotherapy is the most effective treatment developed to date, its use may become less prevalent as newer agents are incorporated into initial and relapse treatment algorithms.
Chronic lymphocytic leukemia (CLL) is a chronic malignancy of B-lymphocytes demonstrating a heterogeneous clinical course ranging from indolent to more rapidly progressive. The chief clinical feature is an elevated peripheral blood lymphocyte count, and patients can demonstrate lymphadenopathy, splenomegaly, hepatomegaly, constitutional symptoms, and in late stages bone marrow failure. It is the most common leukemia among adults in the Western world, accounting for between 22% to 30% of new leukemia diagnoses worldwide [1]. Recent incidence rates in the United States are 3.83 cases per 100,000 person-years [2]. The incidence of CLL increases with age, and most new cases are diagnosed in persons 65 years of age or older [1,2]. As reported 5-year survival rates are between 68% and 81% with a median survival of 10 years in some series, the prevalence is significantly higher than the incidence [3]. However, this may even be an underestimate of the population burden of disease, as many cases are not reported to tumor registries [4].
Many patients with CLL are asymptomatic and do not require treatment until years after diagnosis. In these cases a watch and wait approach is taken. The typical natural history of CLL is characterized by periods of effective treatment when required, followed by treatment-free intervals of several years in many cases. However, this can be misleading, as the clinical course for any individual patient is highly variable. Development of cytogenetic and molecular testing has allowed for identification of patients with a higher risk of progression and lower response rates to traditional cytotoxic treatments [5]. For example, depending on chromosomal abnormalities present, median survival can vary from 32 to 133 months [3].
The assessment of underlying disease risk thus provides important information when considering a treatment approach and should be routinely performed for newly diagnosed patients. While the development of highly effective chemoimmunotherapy has allowed most groups of CLL patients to live for many years, some groups do not enjoy the same survival. Recent advances in CLL treatment seek to abrogate such adverse risk factors, thereby improving the survival for all patients with CLL. Given the expected survival of years for most CLL patients, frontline treatment planning must be done in the context of a long-term treatment strategy keeping the risk for late toxicities, such as secondary malignancies, in mind.
Case Study
Initial Presentation
A 50-year-old man is referred for evaluation of cervical lymphadenopathy that had progressed over the prior 6 months. He denies associated symptoms of fatigue, fevers, night sweats, or unintentional weight loss but does report early satiety. On examination there are multiple mobile, enlarged cervical lymph nodes bilaterally. Axillary lymph nodes are likewise enlarged. The liver edge is not palpable, but the spleen is palpable below the belt line. Complete blood count reveals a white blood cell count of 196,000 with 97% lymphocytes. Hemoglobin is 11.0 g/dL and platelet count is 122,000/dL. He recalls being told 3 years previously that his white blood cell count was 48,000 during an emergency department visit for cellulitis.
• How is CLL diagnosed and staged?
CLL is often suspected when patients present with an elevated lymphocyte count. Presenting symptoms of CLL commonly include lymphadenopathy, an enlarged spleen, and constitutional or “B” symptoms such as fatigue, unintentional weight loss, or drenching night sweats. However, only 25% of patients are symptomatic at diagnosis [1]. Many patients with CLL are now diagnosed after a routine blood test, long before the disease is clinically apparent.
The diagnosis of CLL can be made from the peripheral blood and does not require a bone marrow biopsy. According to 2008 guidelines from the International Workshop on Chronic Lymphocytic Leukemia (IWCLL), diagnosis requires at least 5000/uL clonal B-lymphocytes in the peripheral blood. The clonality must be confirmed by immunophenotyping. At time of diagnosis the peripheral blood smear should be examined for the characteristic cells: small mature lymphocytes with a narrow rim of cytoplasm and dense nuclei consisting of clumped chromatin. Larger, atypical cells can be present as long as they do not exceed 55% of the total number of lymphocytes [6].
The immunophenotype of CLL includes aberrant expression of CD5 and a T-cell antigen, along with the characteristic B-cell antigens CD19, CD20, and CD23. The leukemic clone may be either kappa or lambda light chain restricted. Expression of surface immunoglobulin, CD20, and CD79a is typically low compared to that of normal B cells, although there can be some variability in the immunophenotype [6].
Care should be taken to exclude other malignancies with a similar morphology. Leukemic phase mantle cell lymphoma, other low grade lymphomas, and hairy cell leukemia are commonly mistaken for CLL. Immunophenotyping and cytogenetics are usually sufficient to differentiate these. Testing for a balanced translocation involving chromosomes 11 and 14 to exclude mantle cell lymphoma can be helpful, as both CLL and mantle cell lymphoma can appear morphologically similar and share immunophenotypic features (CD5+/CD19+).
Case Continued
The patient’s peripheral blood is drawn for routine immunophenotyping as well as cytogenetic and molecular testing. When he returns to discuss the results 10 days later, he learns that peripheral blood immunophenotyping demonstrates a dim kappa restricted monoclonal population of B-cells that expressed CD19, CD20(dim), CD23, CD38, CD5, and CD43. The lymphocytes are negative for CD10, FMC7, and CD79b, consistent with a CLL immunophenotype. This patient fulfills diagnostic criteria for CLL and has Rai stage II or intermediate-risk disease. Interphase cytogenetic studies of the peripheral blood demonstrate deletions of chromosomes 11q22.3 and 13q14.3. The immunoglobulin heavy chain gene (IGHV) is unmutated.
• How can a CLL patient’s disease risk be characterized?
Historically, staging at diagnosis, pattern of bone marrow infiltration, and response to therapy were used to gauge prognosis. In more recent years, cytogenetic and molecular testing methods have been developed to augment risk stratification. Testing of prognostic significance that influences clinical management includes IGHV mutational status and interphase cytogenetics using FISH [3,12–14]. Expression of ZAP-70 and CD38 are both independent predictors of poorer prognosis in CLL but are not recommended for routine clinical use. Standardized methodology for the measurement of Zap-70 in particular limits the utility of that test in routine clinical practice [15]. Performed at diagnosis, a time when many patients are asymptomatic, cytogenetic testing with FISH and IGHV mutational analysis can predict time to first treatment and increasingly identify high-risk patients for whom investigational early intervention approaches may be considered [16]. While cytogenetic testing has utility at time of diagnosis, it should be considered necessary prior to deciding on the first-line treatment.
Cytogenetics are also important in predicting response to therapy. For instance, patients with deletion(11q) disease have improved survival when treated with regimens containing an alkylating agent [18]. Deletion(17p) patients respond poorly to traditional cytotoxic agents, and treatments with alternate mechanisms of action should be used [5,19]. The gene for tumor suppressor protein TP53 is encoded in this region of chromosome 17, thus treatment with agents that act independent of pathways involving TP53 are preferred [20].
In addition to cytogenetic testing, quantization of somatic mutations in the gene encoding the variable region of the immune globulin heavy chain gene (IGHV) can help define disease-specific risk. When greater than 98% sequence homology is seen, the gene is considered IGHV unmutated. Patients with an unmutated IGHV have worse overall survival. In one study of Rai stage 0 CLL patients, those with an unmutated IGHV had a survival of only 95 months, compared with 293 months in the mutated group [12].
• When should CLL be treated?
CLL is not curable with current standard therapies, and starting treatment at time of diagnosis for early stage, asymptomatic, CLL patients does not improve overall survival and adds treatment-related toxicities [21,22]. Consequently, the decision to treat is based on treating or preventing complications from the disease, and observation is recommended for most asymptomatic, early-stage patients [6]. Because median survival in CLL is often measured in years, deferring treatment can limit both the short- and long-term complications of therapy, especially the significant risk of secondary malignancies associated with some therapies [23]. However, deferring treatment can significantly impact both a patient’s emotional well-being and quality of life, which should be kept in mind when first discussing the rationale for observation with asymptomatic patients [24].
causes.
For patients with anemia, neutropenia, or thrombocytopenia that is autoimmune in nature, treatment should typically begin with corticosteroids, as it would for non-CLL associated cases of autoimmune cytopenias. If steroids are not effective, second-line treatments appropriate for the situation are generally employed, including intravenous immunoglobulin, cyclosporine, azathioprine, and splenectomy. Rituximab has also been shown to be effective in steroid-refractory cases of autoimmune hemolytic anemia associated with CLL [26]. Only if cytopenias are refractory to appropriate second-line therapy should CLL-directed treatments be considered, assuming there are no other indications to treat the underlying CLL [6]. Bone marrow biopsy can be helpful in differentiating autoimmune cytopenias from marrow failure due to CLL infiltration.
• What treatments are most appropriate for young, fit patients?
For younger patients who are in good general health, the standard treatment choice is combination chemoimmunotherapy. While single agent therapies can effectively palliate symptoms in most cases, they do not offer a survival benefit. Treatment with chemoimmunotherapy, consisting of cytotoxic chemotherapy given in combination with an anti-CD20 monoclonal antibody (generally rituximab), results in high response rates and conveys an advantage with respect to both progression-free survival (PFS) and overall survival (OS). Several chemoimmunotherapy regimens are commonly used.
As compared to fludarabine alone, frontline therapy with the combination of rituximab and fludarabine (FR) results in both a higher overall response rate (84% compared with 63% with fludarabine alone) and more complete responses (38% compared with 20% with fludarabine alone). The probability of PFS at 2 years is also better with FR: 67% compared to 45% with single agent fludarabine [28,29]. Neutropenia is more common with the combination regimen but does not appear to increase the rate of infection. Rituximab infusion reactions are commonly observed, so a stepped-up dosing schedule was developed to decrease their incidence and severity.
Fludarabine, cyclophosphamide, and rituximab (FCR) is another highly effective regimen. This combination has similar efficacy to FR with a 90% to 95% overall response rate (ORR) and 44% to 70% complete response (CR) rate [19,30]. Long-term results with this regimen are favorable; 6-year OS of 77% and median time to progression of 80 months have been reported in a follow-up study [31]. However, hematologic toxicity, including severe neutropenia, is common, and many patients are unable to complete all planned therapy [19]. The addition of cyclophosphamide does appear to be especially important for patients with a deletion(11q). Several clinical trials have consistently found that measures of response and survival are improved for deletion(11q) patients receiving an alkylating agent in addition to a nucleoside analogue [18,32,33]. Outcomes in patients with deletion(17p) disease remain poor after FCR; this subset demonstrates the shortest PFS at only 11.5 months [19].
A more recently developed chemoimmunotherapy option for younger, fit patients is bendamustine and rituximab (BR). Bendamustine has structural similarities to both alkylating agents and purine analogues, and is significantly more efficacious than chlorambucil as a single agent [34]. The combination is generally well tolerated, and a phase 2 trial of the combination reported an overall response rate (ORR) of 88.0% [32]. Notably, when the results were examined by genetic risk group, the regimen remained effective for deletion(11q) patients, who achieved overall and CR rates of 90% and 40%, respectively. Unfortunately, only 37.5% of deletion(17p) patients responded, and no patients achieved a CR [32].
The risk for therapy-related neoplasms should be taken into account when selecting initial therapy given the expected long-term survival of most CLL patients. About 8 out of 300 FCR-treated patients developed a therapy-related neoplasm in one study [31]. Treatment with FR, which does not include an alkylating agent, does not appear to have the same risk. In a study reporting long-term follow-up on 104 patients treated with FR, none developed a therapy related neoplasm [35]. Risks associated with bendamustine have not been well characterized but appear to be lower than FC. While inclusion of an alkylating agent is important for deletion(11q) patients, it is not clear if other patients similarly benefit, thus meriting the potentially increased risk for second cancers.
Fortunately, the choice among these similarly effective regimens will soon be based on high-quality, comparative data. FCR and BR have now been directly compared as a first-line treatment in the German CLL Study Group CLL10 trial. At interim analysis, both regimens had the same ORR and 2-year OS. However, CRs were less common in the BR group (38.1% versus 47.4% with FCR) and PFS was likewise inferior. Expectedly, the FCR group experienced more myelotoxicity and infections. The rate of severe neutropenia with FCR was higher at 81.7% compared to only 56.8% with BR [36]. This may be an important consideration when selecting a regimen for individual patients. Baseline renal function may influence choice as well. The active metabolite of fludarabine is eliminated through the kidneys and patients with decreased renal function have been excluded from clinical trials of FCR [19,37]. The phase 2 study of BR included patients with impaired renal function and 35% of participants had a creatinine clearance of less than 70 mL/min. It is notable that increased toxicity was seen in this subset, including higher rates of myelosuppression and infection [32]. As few direct comparisons have been done, the choice between effective first-line chemoimmunotherapy regimens can be difficult. The final results of the CLL 10 trial, as well as the now completed CALGB 10404 trial comparing FCR to FR, will provide new evidence regarding the relative risks and benefits of these regimens, particularly for patients without high-risk chromosomal abnormalities.
• What treatments are most effective for patients with deletion(17p) CLL?
As noted above, deletion(17p) CLL responds poorly to standard treatments. This relative lack of durable response to chemoimmunotherapy appears attributable to loss of function of the tumor suppressor protein TP53 which is encoded in the affected area [20,32,38]. In vivo evidence suggests that fludarabine works through a TP53-dependent mechanism, which likely explains the poor results obtained when deletion(17p) patients are treated with fludarabine-based combinations [38]. Patients harboring deletion(17p) or TP53 mutations should thus be referred for participation in clinical trials or allogeneic stem cell transplantation [17,27].
If initial treatment of a patient with deletion(17p) begins outside of a clinical trial, it should ideally be comprised of agents that have a TP53-independent mechanism of action [20]. Alemtuzumab, a humanized monoclonal antibody against the CD52 antigen expressed on the surface of normal and malignant B- and T-lymphocytes, demonstrated ORR of 33% to 50% in studies of patients with relapsed and refractory CLL [39–42]. A retrospective analysis found that similar outcomes were seen in those who had a TP53 mutation or deletion(17p). A subsequent study of previously untreated CLL patients randomized to treatment with 12 weeks of alemtuzumab or chlorambucil found that alemtuzumab-treated deletion(17p) patients had an ORR of 64% and median PFS of 10.7 months [43]. Alemtuzumab is therefore a rational choice for first-line therapy in this population. Hematologic toxicity is frequent, however, and all patients must receive prophylaxis against and monitoring for reactivation of CMV infection [43]. Infusion reactions are common but may be reduced by subcutaneous administration without apparent loss of efficacy [42,44]. While alemtuzumab is no longer marketed in the United States for the indication of CLL, it is available free of charge from the manufacturer [45].
High-dose methylprednisolone with rituximab (HDMP-R) has also been successfully used as both salvage and first-line therapy in this group. As salvage therapy, responses were seen in greater than 90% of patients, including over 50% of deletion(17p) patients [46-48]. In treatment-naïve CLL, the ORR was 96% [49], although data for patients with deletion 17p is limited in the frontline setting. Myelotoxicity attributable to the regimen is modest, but good antimicrobial prophylaxis is warranted, as well as close monitoring for hyperglycemia in at-risk patients.
• How is treatment modified for older or less fit patients?
For patients older than 70, or those who have significant comorbidities, effective therapies are still available. As most new diagnoses of CLL are made in patients older than 65, age is but one important factor determining an individual patient’s ability to tolerate treatment. The German CLL Study Group has usefully classified elderly patients into 3 treatment groups based on fitness and goals of care. The first group of medically fit patients with a normal life expectancy, sometimes referred to as the “go go” group, generally tolerate standard chemoimmunotherapy. A second group of older patients with significant life-limiting comorbid conditions—the so-called “no go” patients —should be offered best supportive care rather than CLL-directed treatment. A third group of “slow go” patients falls in between these two; these patients have comorbidities with variable life expectancy and will likely tolerate and benefit from CLL-directed therapy [50].
While some older patients can safely receive chemoimmunotherapy at standard doses and schedules, FCR can prove intolerable for even the medically fit elderly. Because inferior outcomes have been reported among patients older than 70 [30,31], a reduced-dose FCR regimen (FCR-lite) has been studied. Doses of fludarabine and cyclophosphamide were reduced by 20% and 40% respectively and dosing frequency of rituximab was increased. The CR rate was favorable at 77%, the rate of severe neutropenia was reduced to only 13%, and most patients completed all planned therapy [51]. Alternatively, the combination of pentostatin, cyclophosphamide, and rituximab (PCR) has also been successfully used in older patients. The overall and CR rates, 91% and 63% respectively, were durable at 26 months of follow-up. Importantly, there was no statistically significant difference in response or toxicity among the 28% of patients older than 70 [52,53].
For less fit patients, chlorambucil remains a reasonable option. Chlorambucil, a well-tolerated oral alkylating agent, has been used as a frontline therapy in CLL for decades. Chlorambucil has demonstrated consistent response rates in at least 4 clinical trials and is an appropriate option for patients who cannot tolerate more intensive therapy [54]. When a multicenter phase III trial compared it directly to fludarabine in patients over 65, the PFS and OS were no different despite favorable response rates in fludarabine-treated patients [55]. The effectiveness of single-agent chlorambucil can be improved, and the tolerability maintained, with the addition of a CD20-directed monoclonal antibody [56]. Obinutuzumab, a glycolengineered type II antibody against CD20, has recently been shown to improve treatment efficacy when used in combination with chlorambucil [57]. The CLL11 trial randomized patients with comorbid conditions to 1 of 3 treatments: single-agent chlorambucil, chlorambucil with rituximab (R-Clb), or chlorambucil with obinutuzumab (G-Clb). Both chemoimmunotherapy combinations outperformed chlorambucil alone, but the inclusion of obinutuzumab was associated with higher CR rates and longer PFS than rituximab, although infusion reactions and neutropenia were more common in the obinutuzumab arm [57]. Based on this result, the US Food and Drug Administration has now approved obinutuzumab for use in combination with chlorambucil as frontline therapy. While regulatory approval is without restriction with respect to patient age or fitness, a chlorambucil backbone remains most appropriate for older patients and/or those with significant comorbidities.
• What therapies are currently under development?
Numerous targeted treatments and novel immunotherapies are under active investigation in CLL. With greater specificity for CLL, these emerging agents offer the possibility of more effective yet less toxic treatments that will undoubtedly change the landscape for future CLL therapy. These agents are currently most studied as salvage therapies, and given their targeted mechanism of action can be highly effective in relapsed and refractory patients who frequently harbor poor risk cytogenetic abnormalities such as deletion(17p). Data for these agents as initial treatment is limited. Ongoing clinical trials employing these newer agents will need to be reported before these drugs can be recommended as frontline therapies.
Frontline experience with the oral immunomodulatory agent lenalidomide is more extensive. Lenalidomide offers convenient daily dosing and a favorable toxicity profile. When given on a continuous dosing schedule to patients who were 65 years old or older, the ORR was 65%, and 88% of patients were still alive at 2 years’ follow-up. The quality of response continued to improve beyond 18 months of treatment. Neutropenia, the most common severe toxicity, complicated about a third of cycles. Tumor flare attributable to immune activation was also seen, but in most cases was low-grade and did not require intervention [58,59]. While life-threatening tumor lysis syndrome and tumor flare have been seen with lenalidomide in CLL, such concerns are largely abrogated by a lower starting dose and careful intrapatient dose titration [60]. Lenalidomide has also been combined with rituximab and yielded promising results. Sixty-nine treatment-naïve patients were treated with escalating doses of lenalidomide along with rituximab infusions starting at the end of cycle 1 in a phase 2 study. They achieved an 88% ORR with 16% CRs. Toxicities were generally manageable, but patients over 65 were less likely to reach higher doses of lenalidomide or complete all planned treatment cycles [61]. Unfortunately, the FDA recently halted accrual to a phase 3 frontline clinical trial comparing lenalidomide to chlorambucil due to excess mortality in the lenalidomide arm among patients over the age of 80 [62]. More detailed outcomes from that study should be forthcoming.
Perhaps the most remarkable recent advance in CLL medicine, however, is the advent of orally bioavailable small molecule inhibitors of the B-cell receptor (BCR) signaling pathway. BCR signaling plays a vitally important role in supporting the growth and survival of malignant B-cells, activating a number of downstream kinases (Syk, Btk, PI3K, among others) which are potential therapeutic targets. Proof of principle for this approach was demonstrated with the Syk inhibitor fostamatinib in a phase 1/2 trial enrolling patients with B-cell non-Hodgkin lymphoma and CLL. CLL/SLL patients had the highest response rates of any subgroup in that study, with 6 out of 11 patients responding [63]. In a subsequent phase 1b study of the Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib, durable partial remissions were reported in more than 70% of multiply relapsed and refractory patients, including genetically high-risk patients [64–66]. Ibrutinib appears safer and better tolerated than traditional chemoimmunotherapy in the relapsed setting; consequently, it is now being studied as a first-line therapy both alone and in combination with other agents [67]. Other BCR signaling agents under study, such as the phosphatidylinositol 3-kinase inhibitor idelalisib, demonstrate similar safety and high response rates across both genetic risk and patient age groups [68].
New targeted drugs are not limited to the BCR signaling pathway. ABT-199 inhibits B-cell leukemia/lymphoma 2 (BCL-2), which is an anti-apoptotic protein in the cell death pathway, and has demonstrated remarkable clinical efficacy in relapsed and refractory CLL patients [69]. As more experience is gained with these targeted agents, it is expected that they will be rapidly incorporated into frontline therapies. However, these agents are just now being studied in comparison to standard initial treatments, such as FCR, and it is not yet clear they will offer an advantage over current chemoimmunotherapy in this setting [70–72]. Since these single agents typically do not induce complete remissions, and require indefinite therapy to maintain response, optimal combination therapies are under intensive investigation.
Case Conclusion
The patient and his physician elect to begin treatment owing to symptomatic cervical lymphadenopathy and massive splenomegaly. Given the presence of a deletion(11q) abnormality, but hoping to limit the risk for both short- and long-term toxicities, this younger, fit patient is treated with 6 cycles of bendamustine and rituximab. At the conclusion of treatment, neither the cervical lymph nodes nor spleen remain palpable. His blood counts have also normalized, with a white blood cell count of 4700 with 8.1% lymphocyotes, hemoglobin of 14.3 gm/dL, and platelets of 151,000/dL.
Summary
CLL follows a chronic course requiring treatment at variable intervals. Both genetic risk features and patient factors should be considered when determining initial therapy. Cytogenetic and molecular testing can characterize the likelihood of treatment success, information useful for treatment planning. Chemoimmunotherapy is highly effective for most patients, including patients with deletion(11q) CLL, where the inclusion of an alkylating agent in frontline therapy alters the natural history of disease. However, patients with deletion(17p) and or TP53-mutated disease respond poorly to standard treatment and should be considered for investigational therapies [73]. Novel approaches to CLL therapy, most notably immunotherapies and BCR-targeted agents, hold the promise to further improve outcomes, particularly for the highest risk patients and those elderly and/or infirm patients who tolerate chemotherapy poorly. Frontline therapy should rapidly evolve as emerging agents enter advanced phase investigation.
Corresponding author: Jeffrey Jones, MD, MPH, Div. of Hematology, Ohio State University, A350B Starling Loving Hall, 320 West 10th Ave., Columbus, OH 43210, jeffrey.jones@osumc.edu.
Financial disclosures: Dr. Jones disclosed that he is on the advisory boards and has received research support from Genentech, Pharmacyclics, and Gilead.
Author contributions: conception and design, KAR, JAJ; analysis and interpretation of data, KAR, JAJ; drafting of article, KAR, JAJ; critical revision of the article, KAR, JAJ.
1. Redaelli A, Laskin BL, Stephens JM, et al. The clinical and epidemiological burden of chronic lymphocytic leukaemia. Eur J Cancer Care (Engl) 2004;13:279–87.
2. Dores GM, Anderson WF, Curtis RE, et al. Chronic lymphocytic leukaemia and small lymphocytic lymphoma: overview of the descriptive epidemiology. Br J Haematol 2007;139:809–19.
3. Döhner H, Stilgenbauer S, Benner A, et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med 2000;343:1910–6.
4. Zent CS, Kyasa MJ, Evans R, Schichman SA. Chronic lymphocytic leukemia incidence is substantially higher than estimated from tumor registry data. Cancer 2001;92:1325–30.
5. Byrd JC, Gribben JG, Peterson BL, et al. Select high-risk genetic features predict earlier progression following chemoimmunotherapy with fludarabine and rituximab in chronic lymphocytic leukemia: justification for risk-adapted therapy. J Clin Oncol 2006;24:437–43.
6. Hallek M, Cheson BD, Catovsky D, et al. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood 2008;111:5446–56.
7. Rawstron AC, Bennett FL, O'Connor SJ, et al. Monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia. N Engl J Med 2008;359:575–83.
8. Rai KR, Sawitsky A, Cronkite EP, et al. Clinical staging of chronic lymphocytic leukemia. Blood 1975;46:219–34.
9. Binet JL, Auquier A, Dighiero G, et al. A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer 1981;48:198–206.
10. Binet JL, Lepoprier M, Dighiero G, et al. A clinical staging system for chronic lymphocytic leukemia: prognostic significance. Cancer 1977:40:855–64.
11. Eichhorst BF, Fischer K, Fink AM, et al. Limited clinical relevance of imaging techniques in the follow-up of patients with advanced chronic lymphocytic leukemia: results of a meta-analysis. Blood 2011;117:1817–21.
12. Hamblin TJ, Davis Z, Gardiner A, et al. Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999;94:1848–54.
13. Crespo M, Bosch F, Villamor N, et al. ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia. N Engl J Med 2003;348:
1764–75.
14. Hamblin TJ, Orchard JA, Ibbotson RE, et al. CD38 expression and immunoglobulin variable region mutations are independent prognostic variables in chronic lymphocytic leukemia, but CD38 expression may vary during the course of the disease. Blood 2002;99:1023–9.
15. Rassenti LZ, Kipps TJ. Clinical utility of assessing ZAP-70 and CD38 in chronic lymphocytic leukemia. Cytometry B Clin Cytom 2006;70:209–13.
16. Wierda WG, O'Brien S, Wang X, et al. Multivariable model for time to first treatment in patients with chronic lymphocytic leukemia. J Clin Oncol 2011;29:4088–95.
17. Schetelig J, van Biezen A, Brand R, et al. Allogeneic hematopoietic stem-cell transplantation for chronic lymphocytic leukemia with 17p deletion: a retrospective European Group for Blood and Marrow Transplantation analysis. J Clin Oncol 2008;26:5094–100.
18. Ding W, Ferrajoli A. Evidence-based mini-review: the role of alkylating agents in the initial treatment of chronic lymphocytic leukemia patients with the 11q deletion. Hematology Am Soc Hematol Educ Program 2010;2010:90–2.
19. Hallek M, Fischer K, Fingerle-Rowson G, et al. Addition of rituximab to fludarabine and cyclophosphamide in patients with chronic lymphocytic leukaemia: a randomised, open-label, phase 3 trial. Lancet 2010;376:1164–74.
20. Badoux XC, Keating MJ, Wierda WG.What is the best frontline therapy for patients with CLL and 17p deletion? Curr Hematol Malig Rep 2011;6:36–46.
21. Dighiero G, Maloum K, Desablens B, et al. Chlorambucil in indolent chronic lymphocytic leukemia. French Cooperative Group on Chronic Lymphocytic Leukemia. N Engl J Med 1998;338:1506–14.
22. Chemotherapeutic options in chronic lymphocytic leukemia: a meta-analysis of the randomized trials. CLL Trialists' Collaborative Group. J Natl Cancer Inst 1999;91:861–8.
23. Morton LM, Curtis RE, Linet MS, et al. Second malignancy risks after non-Hodgkin's lymphoma and chronic lymphocytic leukemia: differences by lymphoma subtype. J Clin Oncol 2010;28:4935–44.
24. Shanafelt TD, Bowen D, Venkat C, et al. Quality of life in chronic lymphocytic leukemia: an international survey of 1482 patients. Br J Haematol 2007;139:255–64.
25. Baer MR, Stein RS, Dessypris EN. Chronic lymphocytic leukemia with hyperleukocytosis. The hyperviscosity syndrome. Cancer 1985;56:2865–9.
26. Gupta N, Kavuru S, Patel D, et al. Rituximab-based chemotherapy for steroid-refractory autoimmune hemolytic anemia of chronic lymphocytic leukemia. Leukemia 2002;16:2092–5.
27. National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology: non-hodgkin's lymphomas. Version 2.2013. Available at http://www.nccn.org/professionals/physician_gls/pdf/nhl.pdf.
28. Byrd JC, Rai K, Peterson BL, et al. Addition of rituximab to fludarabine may prolong progression-free survival and overall survival in patients with previously untreated chronic lymphocytic leukemia: an updated retrospective comparative analysis of CALGB 9712 and CALGB 9011. Blood 2005;105:49–53.
29. Byrd JC, Peterson BL, Morrison VA, et al. Randomized phase 2 study of fludarabine with concurrent versus sequential treatment with rituximab in symptomatic, untreated patients with B-cell chronic lymphocytic leukemia: results from Cancer and Leukemia Group B 9712 (CALGB 9712). Blood 2003;101:6–14.
30. Keating MJ, O'Brien S, Albitar M, et al. Early results of a chemoimmunotherapy regimen of fludarabine, cyclophosphamide, and rituximab as initial therapy for chronic lymphocytic leukemia. J Clin Oncol 2005;23:4079–88.
31. Tam CS, O'Brien S, Wierda W, et al. Long-term results of the fludarabine, cyclophosphamide, and rituximab regimen as initial therapy of chronic lymphocytic leukemia. Blood 2008;112:975–80.
32. Fischer K, Cramer P, Busch R, et al. Bendamustine in combination with rituximab for previously untreated patients with chronic lymphocytic leukemia: a multicenter phase II trial of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2012;30:3209–16.
33. Catovsky D, Richards S, Matutes E, et al. Assessment of fludarabine plus cyclophosphamide for patients with chronic lymphocytic leukaemia (the LRF CLL4 Trial): a randomised controlled trial. Lancet 2007;370:230–9.
34. Knauf WU, Lissichkov T, Aldaoud A, et al. Phase III randomized study of bendamustine compared with chlorambucil in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:4378–84.
35. Woyach JA, Ruppert AS, Heerema NA, et al. Chemoimmunotherapy with fludarabine and rituximab produces extended overall survival and progression-free survival in chronic lymphocytic leukemia: long-term follow-up of CALGB study 9712. J Clin Oncol 2011;29:1349–55.
36. Fink AM, et al., Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximabversus bendamustine and rituximabin previously untreated and physically fit patientswith advanced chronic lymphocytic leukemia: results of a planned interim analysis of the CLL10 Trial, an international, randomized study of the German CLL Study Group (GCLLSG). Blood 2013;122:526.
37. Gandhi V, Plunkett W. Cellular and clinical pharmacology of fludarabine. Clin Pharmacokinet 2002;41:93–103.
38. Rosenwald A, Chuang EY, Davis RE, et al. Fludarabine treatment of patients with chronic lymphocytic leukemia induces a p53-dependent gene expression response. Blood 2004;104:1428–34.
39. Keating MJ, Flinn I, Jain V, et al. Therapeutic role of alemtuzumab (Campath-1H) in patients who have failed fludarabine: results of a large international study. Blood 2002;99:3554–61.
40. Lozanski G, Heerema NA, Flinn IW, et al. Alemtuzumab is an effective therapy for chronic lymphocytic leukemia with p53 mutations and deletions. Blood 2004;103:3278–81.
41. Osuji NC, Del Giudice I, Matutes E, et al, The efficacy of alemtuzumab for refractory chronic lymphocytic leukemia in relation to cytogenetic abnormalities of p53. Haematologica 2005;90:1435–6.
42. Stilgenbauer S, Zenz T, Winkler D, et al. Subcutaneous alemtuzumab in fludarabine-refractory chronic lymphocytic leukemia: clinical results and prognostic marker analyses from the CLL2H study of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2009;27:3994–4001.
43. Hillmen P, Skotnicki AB, Robak T, et al. Alemtuzumab compared with chlorambucil as first-line therapy for chronic lymphocytic leukemia. J Clin Oncol 2007;25:5616–23.
44. Lundin J, Kimby E, Björkholm M, et al. Phase II trial of subcutaneous anti-CD52 monoclonal antibody alemtuzumab (Campath-1H) as first-line treatment for patients with B-cell chronic lymphocytic leukemia (B-CLL). Blood 2002;100:768–73.
45. Genzyme. US Campath Distribution Program. Cambridge, MA: Genzyme. Available at http://www.campath.com/.
46. Thornton PD, Matutes E, Bosanquet AG, et al. High dose methylprednisolone can induce remissions in CLL patients with p53 abnormalities. Ann Hematol 2003;82:759–65.
47. Bowen DA, Call TG, Jenkins GD, et al. Methylprednisolone-rituximab is an effective salvage therapy for patients with relapsed chronic lymphocytic leukemia including those with unfavorable cytogenetic features. Leuk Lymphoma 2007;48:2412–7.
48. Castro JE, Sandoval-Sus JD, Bole J, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of fludarabine refractory high-risk chronic lymphocytic leukemia. Leukemia 2008;22:2048–53.
49. Castro JE, James DF, Sandoval-Sus JD, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of chronic lymphocytic leukemia. Leukemia 2009;23:1779–89.
50. Eichhorst B, Goede V, Hallek M. Treatment of elderly patients with chronic lymphocytic leukemia. Leuk Lymphoma 2009;50:171–8.
51. Foon KA, Boyiadzis M, Land SR, et al. Chemoimmunotherapy with low-dose fludarabine and cyclophosphamide and high dose rituximab in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:498–503.
52. Kay NE, Geyer SM, Call TG, et al. Combination chemoimmunotherapy with pentostatin, cyclophosphamide, and rituximab shows significant clinical activity with low accompanying toxicity in previously untreated B chronic lymphocytic leukemia. Blood 2007;109:405–11.
53. Shanafelt TD, Lin T, Geyer SM, et al. Pentostatin, cyclophosphamide, and rituximab regimen in older patients with chronic lymphocytic leukemia. Cancer 2007;109:2291–8.
54. Catovsky D, Else M, Richards S. Chlorambucil--still not bad: a reappraisal. Clin Lymphoma Myeloma Leuk 2011;11 Suppl 1:S2–6.
55. Eichhorst BF, Busch R, Stilgenbauer S, et al. First-line therapy with fludarabine compared with chlorambucil does not result in a major benefit for elderly patients with advanced chronic lymphocytic leukemia. Blood 2009;114:3382–91.
56. Laurenti L, Vannata B, Innocenti I, et al. Chlorambucil plus rituximab as front-line therapy in elderly/unfit patients affected by b-cell chronic lymphocytic leukemia: results of a single-centre experience. Mediterr J Hematol Infect Dis 2013;5:e2013031.
57. Goede V, Fischer K, Busch R, et al. Obinutuzumab plus chlorambucil in patients with CLL and coexisting conditions. N Engl J Med 2014 Jan 8. [Epub ahead of print].
58. Badoux XC, Keating MJ, Wen S, et al. Lenalidomide as initial therapy of elderly patients with chronic lymphocytic leukemia. Blood 2011;118:3489–98.
59. Strati P, Keating MJ, Wierda WG, et al. Lenalidomide induces long-lasting responses in elderly patients with chronic lymphocytic leukemia. Blood 2013;122:734–7.
60. Moutouh-de Parseval LA, Weiss L, DeLap RJ, et al. Tumor lysis syndrome/tumor flare reaction in lenalidomide-treated chronic lymphocytic leukemia. J Clin Oncol 2007;25:5047.
61. James DF, Brown JR, Werner L, et al. Lenalidomide and rituximab for the initial treatment of patients with chronic lymphocytic leukemia (CLL): a multicenter study of the CLL Research Consortium. ASH Annual Meeting Abstracts 2011;118:291.
62. US Food and Drug Administration. FDA halts clinical trial of drug Revlimid (lenalidomide) for chronic lymphocytic leukemia due to safety concerns. Available at http://www.fda.gov/Drugs/DrugSafety/ucm361444.htm.
63. Friedberg JW, Sharman J, Sweetenham J, et al. Inhibition of Syk with fostamatinib disodium has significant clinical activity in non-Hodgkin lymphoma and chronic lymphocytic leukemia. Blood 2010;115:2578–85.
64. Byrd JC, Furman RR, Coutre SE, et al. Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 2013;369:32–42.
65. Farooqui M, Aue G, Valdez J, et al. Single agent ibrutinib (PCI-32765) achieves equally good and durable responses in chronic lymphocytic leukemia (CLL) patients with and without deletion 17p. Blood 2013;122:673.
66. Byrd JC, Furman RR, Coutre S, et al. The Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib (PCI-32765) monotherapy demonstrates long-term safety and durability of response in chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) patients in an open-label extension study. Blood 2013;122:4163.
67. Brown JR, Barrientos JC, Barr PM, et al. Ibrutinib in combination with bendamustine and rituximab is active and tolerable in patients with relapsed/refractory CLL/SLL: final results of a phase 1b study. ASH Annual Meeting Abstracts 2013.
68. O'Brien SM, Lamanna N, Kipps TJ, et al. A phase II study of the selective phosphatidylinositol 3-kinase delta (PI3K{delta}) inhibitor idelalisib (GS-1101) in combination with rituximab (R) in treatment-naive patients (pts) ≥ 65 years with chronic lymphocytic leukemia (CLL) or small lymphocytic lymphoma (SLL). J Clin Oncol 2013;31(15 Suppl); Abstract 7005.
69. Seymour JF, Davids MS, Pagel JM, et al. Bcl-2 Inhibitor ABT-199 (GDC-0199) monotherapy shows anti-tumor activity including complete remissions in high-risk relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL). Blood 2013;122:872.
70. Rituxumab and bendamustine hydrochloride, rituxumab and ibrutunib, or ibrutinib alone in treating older patients with previously untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT01886872?term=ibrutinib+cll&rank=8.
71. A multicenter, open-label, phase 3 study of the bruton's tyrosine kinase inhibitor pci-32765 versus chlorambucil in patients 65 years of older with treatment-naive chronic lymphocytic leukemia or small lymphocytic lymphoma (RESONATE-2) Available at http://clinicaltrials.gov/ct2/show/NCT01722487?term=ibrutinib+cll&rank=12.
72. Ibrutinib and rituximab compared with fludarabine phosphate, cyclophosphamide, and rituxumab in treating patients with untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT02048813?term=ibrutinib+cll&rank=2.
73. Strati P, Keating MJ, O'Brien SM, et al. Outcomes of first-line treatment for chronic lymphocytic leukemia (CLL) with 17p deletion. J Clin Oncol 2013;31(15 suppl): Abstract 7102.
1. Redaelli A, Laskin BL, Stephens JM, et al. The clinical and epidemiological burden of chronic lymphocytic leukaemia. Eur J Cancer Care (Engl) 2004;13:279–87.
2. Dores GM, Anderson WF, Curtis RE, et al. Chronic lymphocytic leukaemia and small lymphocytic lymphoma: overview of the descriptive epidemiology. Br J Haematol 2007;139:809–19.
3. Döhner H, Stilgenbauer S, Benner A, et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med 2000;343:1910–6.
4. Zent CS, Kyasa MJ, Evans R, Schichman SA. Chronic lymphocytic leukemia incidence is substantially higher than estimated from tumor registry data. Cancer 2001;92:1325–30.
5. Byrd JC, Gribben JG, Peterson BL, et al. Select high-risk genetic features predict earlier progression following chemoimmunotherapy with fludarabine and rituximab in chronic lymphocytic leukemia: justification for risk-adapted therapy. J Clin Oncol 2006;24:437–43.
6. Hallek M, Cheson BD, Catovsky D, et al. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood 2008;111:5446–56.
7. Rawstron AC, Bennett FL, O'Connor SJ, et al. Monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia. N Engl J Med 2008;359:575–83.
8. Rai KR, Sawitsky A, Cronkite EP, et al. Clinical staging of chronic lymphocytic leukemia. Blood 1975;46:219–34.
9. Binet JL, Auquier A, Dighiero G, et al. A new prognostic classification of chronic lymphocytic leukemia derived from a multivariate survival analysis. Cancer 1981;48:198–206.
10. Binet JL, Lepoprier M, Dighiero G, et al. A clinical staging system for chronic lymphocytic leukemia: prognostic significance. Cancer 1977:40:855–64.
11. Eichhorst BF, Fischer K, Fink AM, et al. Limited clinical relevance of imaging techniques in the follow-up of patients with advanced chronic lymphocytic leukemia: results of a meta-analysis. Blood 2011;117:1817–21.
12. Hamblin TJ, Davis Z, Gardiner A, et al. Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999;94:1848–54.
13. Crespo M, Bosch F, Villamor N, et al. ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia. N Engl J Med 2003;348:
1764–75.
14. Hamblin TJ, Orchard JA, Ibbotson RE, et al. CD38 expression and immunoglobulin variable region mutations are independent prognostic variables in chronic lymphocytic leukemia, but CD38 expression may vary during the course of the disease. Blood 2002;99:1023–9.
15. Rassenti LZ, Kipps TJ. Clinical utility of assessing ZAP-70 and CD38 in chronic lymphocytic leukemia. Cytometry B Clin Cytom 2006;70:209–13.
16. Wierda WG, O'Brien S, Wang X, et al. Multivariable model for time to first treatment in patients with chronic lymphocytic leukemia. J Clin Oncol 2011;29:4088–95.
17. Schetelig J, van Biezen A, Brand R, et al. Allogeneic hematopoietic stem-cell transplantation for chronic lymphocytic leukemia with 17p deletion: a retrospective European Group for Blood and Marrow Transplantation analysis. J Clin Oncol 2008;26:5094–100.
18. Ding W, Ferrajoli A. Evidence-based mini-review: the role of alkylating agents in the initial treatment of chronic lymphocytic leukemia patients with the 11q deletion. Hematology Am Soc Hematol Educ Program 2010;2010:90–2.
19. Hallek M, Fischer K, Fingerle-Rowson G, et al. Addition of rituximab to fludarabine and cyclophosphamide in patients with chronic lymphocytic leukaemia: a randomised, open-label, phase 3 trial. Lancet 2010;376:1164–74.
20. Badoux XC, Keating MJ, Wierda WG.What is the best frontline therapy for patients with CLL and 17p deletion? Curr Hematol Malig Rep 2011;6:36–46.
21. Dighiero G, Maloum K, Desablens B, et al. Chlorambucil in indolent chronic lymphocytic leukemia. French Cooperative Group on Chronic Lymphocytic Leukemia. N Engl J Med 1998;338:1506–14.
22. Chemotherapeutic options in chronic lymphocytic leukemia: a meta-analysis of the randomized trials. CLL Trialists' Collaborative Group. J Natl Cancer Inst 1999;91:861–8.
23. Morton LM, Curtis RE, Linet MS, et al. Second malignancy risks after non-Hodgkin's lymphoma and chronic lymphocytic leukemia: differences by lymphoma subtype. J Clin Oncol 2010;28:4935–44.
24. Shanafelt TD, Bowen D, Venkat C, et al. Quality of life in chronic lymphocytic leukemia: an international survey of 1482 patients. Br J Haematol 2007;139:255–64.
25. Baer MR, Stein RS, Dessypris EN. Chronic lymphocytic leukemia with hyperleukocytosis. The hyperviscosity syndrome. Cancer 1985;56:2865–9.
26. Gupta N, Kavuru S, Patel D, et al. Rituximab-based chemotherapy for steroid-refractory autoimmune hemolytic anemia of chronic lymphocytic leukemia. Leukemia 2002;16:2092–5.
27. National Comprehensive Cancer Network. NCCN clinical practice guidelines in oncology: non-hodgkin's lymphomas. Version 2.2013. Available at http://www.nccn.org/professionals/physician_gls/pdf/nhl.pdf.
28. Byrd JC, Rai K, Peterson BL, et al. Addition of rituximab to fludarabine may prolong progression-free survival and overall survival in patients with previously untreated chronic lymphocytic leukemia: an updated retrospective comparative analysis of CALGB 9712 and CALGB 9011. Blood 2005;105:49–53.
29. Byrd JC, Peterson BL, Morrison VA, et al. Randomized phase 2 study of fludarabine with concurrent versus sequential treatment with rituximab in symptomatic, untreated patients with B-cell chronic lymphocytic leukemia: results from Cancer and Leukemia Group B 9712 (CALGB 9712). Blood 2003;101:6–14.
30. Keating MJ, O'Brien S, Albitar M, et al. Early results of a chemoimmunotherapy regimen of fludarabine, cyclophosphamide, and rituximab as initial therapy for chronic lymphocytic leukemia. J Clin Oncol 2005;23:4079–88.
31. Tam CS, O'Brien S, Wierda W, et al. Long-term results of the fludarabine, cyclophosphamide, and rituximab regimen as initial therapy of chronic lymphocytic leukemia. Blood 2008;112:975–80.
32. Fischer K, Cramer P, Busch R, et al. Bendamustine in combination with rituximab for previously untreated patients with chronic lymphocytic leukemia: a multicenter phase II trial of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2012;30:3209–16.
33. Catovsky D, Richards S, Matutes E, et al. Assessment of fludarabine plus cyclophosphamide for patients with chronic lymphocytic leukaemia (the LRF CLL4 Trial): a randomised controlled trial. Lancet 2007;370:230–9.
34. Knauf WU, Lissichkov T, Aldaoud A, et al. Phase III randomized study of bendamustine compared with chlorambucil in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:4378–84.
35. Woyach JA, Ruppert AS, Heerema NA, et al. Chemoimmunotherapy with fludarabine and rituximab produces extended overall survival and progression-free survival in chronic lymphocytic leukemia: long-term follow-up of CALGB study 9712. J Clin Oncol 2011;29:1349–55.
36. Fink AM, et al., Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximabversus bendamustine and rituximabin previously untreated and physically fit patientswith advanced chronic lymphocytic leukemia: results of a planned interim analysis of the CLL10 Trial, an international, randomized study of the German CLL Study Group (GCLLSG). Blood 2013;122:526.
37. Gandhi V, Plunkett W. Cellular and clinical pharmacology of fludarabine. Clin Pharmacokinet 2002;41:93–103.
38. Rosenwald A, Chuang EY, Davis RE, et al. Fludarabine treatment of patients with chronic lymphocytic leukemia induces a p53-dependent gene expression response. Blood 2004;104:1428–34.
39. Keating MJ, Flinn I, Jain V, et al. Therapeutic role of alemtuzumab (Campath-1H) in patients who have failed fludarabine: results of a large international study. Blood 2002;99:3554–61.
40. Lozanski G, Heerema NA, Flinn IW, et al. Alemtuzumab is an effective therapy for chronic lymphocytic leukemia with p53 mutations and deletions. Blood 2004;103:3278–81.
41. Osuji NC, Del Giudice I, Matutes E, et al, The efficacy of alemtuzumab for refractory chronic lymphocytic leukemia in relation to cytogenetic abnormalities of p53. Haematologica 2005;90:1435–6.
42. Stilgenbauer S, Zenz T, Winkler D, et al. Subcutaneous alemtuzumab in fludarabine-refractory chronic lymphocytic leukemia: clinical results and prognostic marker analyses from the CLL2H study of the German Chronic Lymphocytic Leukemia Study Group. J Clin Oncol 2009;27:3994–4001.
43. Hillmen P, Skotnicki AB, Robak T, et al. Alemtuzumab compared with chlorambucil as first-line therapy for chronic lymphocytic leukemia. J Clin Oncol 2007;25:5616–23.
44. Lundin J, Kimby E, Björkholm M, et al. Phase II trial of subcutaneous anti-CD52 monoclonal antibody alemtuzumab (Campath-1H) as first-line treatment for patients with B-cell chronic lymphocytic leukemia (B-CLL). Blood 2002;100:768–73.
45. Genzyme. US Campath Distribution Program. Cambridge, MA: Genzyme. Available at http://www.campath.com/.
46. Thornton PD, Matutes E, Bosanquet AG, et al. High dose methylprednisolone can induce remissions in CLL patients with p53 abnormalities. Ann Hematol 2003;82:759–65.
47. Bowen DA, Call TG, Jenkins GD, et al. Methylprednisolone-rituximab is an effective salvage therapy for patients with relapsed chronic lymphocytic leukemia including those with unfavorable cytogenetic features. Leuk Lymphoma 2007;48:2412–7.
48. Castro JE, Sandoval-Sus JD, Bole J, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of fludarabine refractory high-risk chronic lymphocytic leukemia. Leukemia 2008;22:2048–53.
49. Castro JE, James DF, Sandoval-Sus JD, et al. Rituximab in combination with high-dose methylprednisolone for the treatment of chronic lymphocytic leukemia. Leukemia 2009;23:1779–89.
50. Eichhorst B, Goede V, Hallek M. Treatment of elderly patients with chronic lymphocytic leukemia. Leuk Lymphoma 2009;50:171–8.
51. Foon KA, Boyiadzis M, Land SR, et al. Chemoimmunotherapy with low-dose fludarabine and cyclophosphamide and high dose rituximab in previously untreated patients with chronic lymphocytic leukemia. J Clin Oncol 2009;27:498–503.
52. Kay NE, Geyer SM, Call TG, et al. Combination chemoimmunotherapy with pentostatin, cyclophosphamide, and rituximab shows significant clinical activity with low accompanying toxicity in previously untreated B chronic lymphocytic leukemia. Blood 2007;109:405–11.
53. Shanafelt TD, Lin T, Geyer SM, et al. Pentostatin, cyclophosphamide, and rituximab regimen in older patients with chronic lymphocytic leukemia. Cancer 2007;109:2291–8.
54. Catovsky D, Else M, Richards S. Chlorambucil--still not bad: a reappraisal. Clin Lymphoma Myeloma Leuk 2011;11 Suppl 1:S2–6.
55. Eichhorst BF, Busch R, Stilgenbauer S, et al. First-line therapy with fludarabine compared with chlorambucil does not result in a major benefit for elderly patients with advanced chronic lymphocytic leukemia. Blood 2009;114:3382–91.
56. Laurenti L, Vannata B, Innocenti I, et al. Chlorambucil plus rituximab as front-line therapy in elderly/unfit patients affected by b-cell chronic lymphocytic leukemia: results of a single-centre experience. Mediterr J Hematol Infect Dis 2013;5:e2013031.
57. Goede V, Fischer K, Busch R, et al. Obinutuzumab plus chlorambucil in patients with CLL and coexisting conditions. N Engl J Med 2014 Jan 8. [Epub ahead of print].
58. Badoux XC, Keating MJ, Wen S, et al. Lenalidomide as initial therapy of elderly patients with chronic lymphocytic leukemia. Blood 2011;118:3489–98.
59. Strati P, Keating MJ, Wierda WG, et al. Lenalidomide induces long-lasting responses in elderly patients with chronic lymphocytic leukemia. Blood 2013;122:734–7.
60. Moutouh-de Parseval LA, Weiss L, DeLap RJ, et al. Tumor lysis syndrome/tumor flare reaction in lenalidomide-treated chronic lymphocytic leukemia. J Clin Oncol 2007;25:5047.
61. James DF, Brown JR, Werner L, et al. Lenalidomide and rituximab for the initial treatment of patients with chronic lymphocytic leukemia (CLL): a multicenter study of the CLL Research Consortium. ASH Annual Meeting Abstracts 2011;118:291.
62. US Food and Drug Administration. FDA halts clinical trial of drug Revlimid (lenalidomide) for chronic lymphocytic leukemia due to safety concerns. Available at http://www.fda.gov/Drugs/DrugSafety/ucm361444.htm.
63. Friedberg JW, Sharman J, Sweetenham J, et al. Inhibition of Syk with fostamatinib disodium has significant clinical activity in non-Hodgkin lymphoma and chronic lymphocytic leukemia. Blood 2010;115:2578–85.
64. Byrd JC, Furman RR, Coutre SE, et al. Targeting BTK with ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med 2013;369:32–42.
65. Farooqui M, Aue G, Valdez J, et al. Single agent ibrutinib (PCI-32765) achieves equally good and durable responses in chronic lymphocytic leukemia (CLL) patients with and without deletion 17p. Blood 2013;122:673.
66. Byrd JC, Furman RR, Coutre S, et al. The Bruton’s tyrosine kinase (BTK) inhibitor ibrutinib (PCI-32765) monotherapy demonstrates long-term safety and durability of response in chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) patients in an open-label extension study. Blood 2013;122:4163.
67. Brown JR, Barrientos JC, Barr PM, et al. Ibrutinib in combination with bendamustine and rituximab is active and tolerable in patients with relapsed/refractory CLL/SLL: final results of a phase 1b study. ASH Annual Meeting Abstracts 2013.
68. O'Brien SM, Lamanna N, Kipps TJ, et al. A phase II study of the selective phosphatidylinositol 3-kinase delta (PI3K{delta}) inhibitor idelalisib (GS-1101) in combination with rituximab (R) in treatment-naive patients (pts) ≥ 65 years with chronic lymphocytic leukemia (CLL) or small lymphocytic lymphoma (SLL). J Clin Oncol 2013;31(15 Suppl); Abstract 7005.
69. Seymour JF, Davids MS, Pagel JM, et al. Bcl-2 Inhibitor ABT-199 (GDC-0199) monotherapy shows anti-tumor activity including complete remissions in high-risk relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL). Blood 2013;122:872.
70. Rituxumab and bendamustine hydrochloride, rituxumab and ibrutunib, or ibrutinib alone in treating older patients with previously untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT01886872?term=ibrutinib+cll&rank=8.
71. A multicenter, open-label, phase 3 study of the bruton's tyrosine kinase inhibitor pci-32765 versus chlorambucil in patients 65 years of older with treatment-naive chronic lymphocytic leukemia or small lymphocytic lymphoma (RESONATE-2) Available at http://clinicaltrials.gov/ct2/show/NCT01722487?term=ibrutinib+cll&rank=12.
72. Ibrutinib and rituximab compared with fludarabine phosphate, cyclophosphamide, and rituxumab in treating patients with untreated chronic lymphocytic leukemia. Available at http://clinicaltrials.gov/ct2/show/NCT02048813?term=ibrutinib+cll&rank=2.
73. Strati P, Keating MJ, O'Brien SM, et al. Outcomes of first-line treatment for chronic lymphocytic leukemia (CLL) with 17p deletion. J Clin Oncol 2013;31(15 suppl): Abstract 7102.
Mutation testing aids CML treatment decisions
Patients with Ph+ CML-CP (Philadelphia chromosome–positive chronic myeloid leukemia, chronic phase) who fail to achieve and maintain treatment response at key milestones should be considered for mutation screening, based on data from the DASISION trial.
Patients with mutations had poor outcomes and high rates of treatment discontinuation in an extended 4-year minimum follow-up of patients in the trial; 14 of 17 dasatinib-treated patients and 14 of 18 imatinib-treated patients with mutations discontinued treatment. The primary reason for treatment discontinuation was protocol-defined disease progression (dasatinib, n = 11; imatinib, n = 8); patients with mutations accounted for 61% of discontinuations on dasatinib (n = 11/18) and 42% on imatinib (n = 8/19).
“With the introduction of generic imatinib into the market in 2016, choosing the most appropriate second-line tyrosine-kinase inhibitor for patients, based on factors such as mutation status, will become increasingly important,” Dr. Tim Hughes of the South Australian Health and Medical Research Institute in Adelaide and his colleagues wrote. Having the option to choose the most suitable second-line therapy may ensure improved outcomes and decreased health care costs.
In the DASISION (Dasatinib vs. Imatinib Study in Treatment-Naive CML-CP) trial, all participants had newly diagnosed Ph+ CML-CP; they were treated with dasatinib (n = 259) or imatinib (n = 260) and followed for a minimum of 3 years (Leukemia. 2015 Sep;29[9]:1832-8). Dr. Hughes and his colleagues conducted a retrospective study of the patients who were potentially at a higher risk for developing mutations. This included patients on treatment who had at least one clinically relevant event – no confirmed complete cytogenetic response (cCCyR) within 12 months, no major molecular response (MMR) within 12 months; a fivefold increase in BCR-ABL1 transcript levels with loss of MMR; loss of CCyR – and/or who discontinued treatment for any reason.
Screening identified only a small number of patients with mutations (dasatinib, n = 17; imatinib, n = 18). Those on dasatinib had a narrower spectrum of mutations (4 sites for dasatinib vs. 12 sites for imatinib), fewer phosphate-binding loop mutations (1 mutation for dasatinib vs, 9 mutations for imatinib), and fewer multiple mutations (1 patient on dasatinib vs. 6 patients on imatinib).
However, patients on dasatinib had a greater occurrence of T315I mutations (11 patients on dasatinib vs. 0 patients on imatinib). The researchers hypothesized that this finding resulted from differences in competitive advantage between mutant clones. For example, P-loop mutations Y253F, E255K were found to have higher transformation potency and proliferation rates, compared with T315I, even in the absence of BCR-ABL1 inhibitors. If one assumes that imatinib has lower activity than dasatinib against these mutations, then mutant clones with select P-loop mutations might expand more rapidly than clones with the T315I mutation when exposed to imatinib.
Consistent with this idea, T315I is less common than all P-loop mutations in CML-CP patients with imatinib resistance. In addition, dasatinib suppresses P-loop mutations to a greater extent than does T315I; therefore, T315I may be able to develop during dasatinib treatment with relatively little competition from rapidly proliferating clones.
“Dasatinib, nilotinib, bosutinib, and ponatinib have enabled many patients, including those with mutations, to overcome imatinib resistance; however, each lack[s] efficacy against a small number of different leukemic clones, and all except ponatinib lack efficacy against T315I,” the researchers wrote.
The study was sponsored by Bristol-Myers Squibb. Dr. Hughes reported receiving honoraria and research funding from ARIAD, the maker of ponatinib; Bristol-Myers Squibb, the maker of dasatinib; and Novartis, the maker of imatinib.
Patients with Ph+ CML-CP (Philadelphia chromosome–positive chronic myeloid leukemia, chronic phase) who fail to achieve and maintain treatment response at key milestones should be considered for mutation screening, based on data from the DASISION trial.
Patients with mutations had poor outcomes and high rates of treatment discontinuation in an extended 4-year minimum follow-up of patients in the trial; 14 of 17 dasatinib-treated patients and 14 of 18 imatinib-treated patients with mutations discontinued treatment. The primary reason for treatment discontinuation was protocol-defined disease progression (dasatinib, n = 11; imatinib, n = 8); patients with mutations accounted for 61% of discontinuations on dasatinib (n = 11/18) and 42% on imatinib (n = 8/19).
“With the introduction of generic imatinib into the market in 2016, choosing the most appropriate second-line tyrosine-kinase inhibitor for patients, based on factors such as mutation status, will become increasingly important,” Dr. Tim Hughes of the South Australian Health and Medical Research Institute in Adelaide and his colleagues wrote. Having the option to choose the most suitable second-line therapy may ensure improved outcomes and decreased health care costs.
In the DASISION (Dasatinib vs. Imatinib Study in Treatment-Naive CML-CP) trial, all participants had newly diagnosed Ph+ CML-CP; they were treated with dasatinib (n = 259) or imatinib (n = 260) and followed for a minimum of 3 years (Leukemia. 2015 Sep;29[9]:1832-8). Dr. Hughes and his colleagues conducted a retrospective study of the patients who were potentially at a higher risk for developing mutations. This included patients on treatment who had at least one clinically relevant event – no confirmed complete cytogenetic response (cCCyR) within 12 months, no major molecular response (MMR) within 12 months; a fivefold increase in BCR-ABL1 transcript levels with loss of MMR; loss of CCyR – and/or who discontinued treatment for any reason.
Screening identified only a small number of patients with mutations (dasatinib, n = 17; imatinib, n = 18). Those on dasatinib had a narrower spectrum of mutations (4 sites for dasatinib vs. 12 sites for imatinib), fewer phosphate-binding loop mutations (1 mutation for dasatinib vs, 9 mutations for imatinib), and fewer multiple mutations (1 patient on dasatinib vs. 6 patients on imatinib).
However, patients on dasatinib had a greater occurrence of T315I mutations (11 patients on dasatinib vs. 0 patients on imatinib). The researchers hypothesized that this finding resulted from differences in competitive advantage between mutant clones. For example, P-loop mutations Y253F, E255K were found to have higher transformation potency and proliferation rates, compared with T315I, even in the absence of BCR-ABL1 inhibitors. If one assumes that imatinib has lower activity than dasatinib against these mutations, then mutant clones with select P-loop mutations might expand more rapidly than clones with the T315I mutation when exposed to imatinib.
Consistent with this idea, T315I is less common than all P-loop mutations in CML-CP patients with imatinib resistance. In addition, dasatinib suppresses P-loop mutations to a greater extent than does T315I; therefore, T315I may be able to develop during dasatinib treatment with relatively little competition from rapidly proliferating clones.
“Dasatinib, nilotinib, bosutinib, and ponatinib have enabled many patients, including those with mutations, to overcome imatinib resistance; however, each lack[s] efficacy against a small number of different leukemic clones, and all except ponatinib lack efficacy against T315I,” the researchers wrote.
The study was sponsored by Bristol-Myers Squibb. Dr. Hughes reported receiving honoraria and research funding from ARIAD, the maker of ponatinib; Bristol-Myers Squibb, the maker of dasatinib; and Novartis, the maker of imatinib.
Patients with Ph+ CML-CP (Philadelphia chromosome–positive chronic myeloid leukemia, chronic phase) who fail to achieve and maintain treatment response at key milestones should be considered for mutation screening, based on data from the DASISION trial.
Patients with mutations had poor outcomes and high rates of treatment discontinuation in an extended 4-year minimum follow-up of patients in the trial; 14 of 17 dasatinib-treated patients and 14 of 18 imatinib-treated patients with mutations discontinued treatment. The primary reason for treatment discontinuation was protocol-defined disease progression (dasatinib, n = 11; imatinib, n = 8); patients with mutations accounted for 61% of discontinuations on dasatinib (n = 11/18) and 42% on imatinib (n = 8/19).
“With the introduction of generic imatinib into the market in 2016, choosing the most appropriate second-line tyrosine-kinase inhibitor for patients, based on factors such as mutation status, will become increasingly important,” Dr. Tim Hughes of the South Australian Health and Medical Research Institute in Adelaide and his colleagues wrote. Having the option to choose the most suitable second-line therapy may ensure improved outcomes and decreased health care costs.
In the DASISION (Dasatinib vs. Imatinib Study in Treatment-Naive CML-CP) trial, all participants had newly diagnosed Ph+ CML-CP; they were treated with dasatinib (n = 259) or imatinib (n = 260) and followed for a minimum of 3 years (Leukemia. 2015 Sep;29[9]:1832-8). Dr. Hughes and his colleagues conducted a retrospective study of the patients who were potentially at a higher risk for developing mutations. This included patients on treatment who had at least one clinically relevant event – no confirmed complete cytogenetic response (cCCyR) within 12 months, no major molecular response (MMR) within 12 months; a fivefold increase in BCR-ABL1 transcript levels with loss of MMR; loss of CCyR – and/or who discontinued treatment for any reason.
Screening identified only a small number of patients with mutations (dasatinib, n = 17; imatinib, n = 18). Those on dasatinib had a narrower spectrum of mutations (4 sites for dasatinib vs. 12 sites for imatinib), fewer phosphate-binding loop mutations (1 mutation for dasatinib vs, 9 mutations for imatinib), and fewer multiple mutations (1 patient on dasatinib vs. 6 patients on imatinib).
However, patients on dasatinib had a greater occurrence of T315I mutations (11 patients on dasatinib vs. 0 patients on imatinib). The researchers hypothesized that this finding resulted from differences in competitive advantage between mutant clones. For example, P-loop mutations Y253F, E255K were found to have higher transformation potency and proliferation rates, compared with T315I, even in the absence of BCR-ABL1 inhibitors. If one assumes that imatinib has lower activity than dasatinib against these mutations, then mutant clones with select P-loop mutations might expand more rapidly than clones with the T315I mutation when exposed to imatinib.
Consistent with this idea, T315I is less common than all P-loop mutations in CML-CP patients with imatinib resistance. In addition, dasatinib suppresses P-loop mutations to a greater extent than does T315I; therefore, T315I may be able to develop during dasatinib treatment with relatively little competition from rapidly proliferating clones.
“Dasatinib, nilotinib, bosutinib, and ponatinib have enabled many patients, including those with mutations, to overcome imatinib resistance; however, each lack[s] efficacy against a small number of different leukemic clones, and all except ponatinib lack efficacy against T315I,” the researchers wrote.
The study was sponsored by Bristol-Myers Squibb. Dr. Hughes reported receiving honoraria and research funding from ARIAD, the maker of ponatinib; Bristol-Myers Squibb, the maker of dasatinib; and Novartis, the maker of imatinib.
FROM LEUKEMIA
Key clinical point:Mutation testing may aid treatment selection in patients with chronic myeloid leukemia (CML) when selecting an alternative therapy because of treatment failure.
Major finding: Patients with mutations accounted for 61% of discontinuations on dasatinib (n = 11/18) and 42% on imatinib (n = 8/19).
Data source: A retrospective analysis of the DASISION trial results of 259 patients treated with dasatinib and 260 treated with imatinib.
Disclosures: The study was sponsored by Bristol-Myers Squibb. Dr. Hughes reported receiving honoraria and research funding from ARIAD, the maker of ponatinib; Bristol-Myers Squibb, the maker of dasatinib; and Novartis, the maker of imatinib.
