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Determinants of Physical Activity in Palliative Cancer Patients: An Application of the Theory of Planned Behavior
Determinants of Physical Activity in Palliative Cancer Patients: An Application of the Theory of Planned Behavior
- Department of Symptom Control and Palliative Care, The Division of Palliative Care Medicine, Department of Oncology, and the Faculty of Physical Education and Recreation, University of Alberta, Cross Cancer Institute, Edmonton, Alberta, Canada
- Received 23 March 2011. Accepted 29 July 2011. Available online 12 October 2011.
- http://dx.doi.org/10.1016/j.suponc.2011.07.005, How to Cite or Link Using DOI
Abstract
Background
Increasing evidence points to the theory of planned behavior as a useful framework to understand physical activity behavior in cancer patients.
Objective
Our primary aim was to examine the demographic, medical, and social–cognitive correlates of physical activity in palliative cancer patients.
Methods
A cross-sectional survey was administered to advanced cancer patients aged 18 years or older with a clinician-estimated life expectancy of less than 12 months and Palliative Performance Scale >30%, from outpatient palliative care, oncology clinics, and palliative home care.
Results
Fifty participants were recruited. Correlates of total physical activity levels were affective attitude (r = 0.36, P = .011), self-efficacy (r = 0.36, P = .010), and intention (r = 0.30, P = .034). Participants who reported 60 minutes or more of total physical activity daily reported significantly higher affective attitude (M = 0.9, 95% confidence interval [CI] 0.26–1.6, P = .008) and self-efficacy (M = 0.8, 95% CI 0.0–1.5, P = .046). Participants <60 years of age (M = 343, 95% CI −7 to 693, P = .054) and who were normal or underweight (M = 333, 95% CI −14 to 680, P = .059) reported higher weekly minutes of total physical activity.
Limitations
Our small sample may not be representative of the total palliative cancer population.
Conclusions
Affective attitude, self-efficacy, and intention were the strongest correlates of total physical activity levels, and younger and normal/underweight participants did more physical activity.
Determinants of Physical Activity in Palliative Cancer Patients: An Application of the Theory of Planned Behavior
- Department of Symptom Control and Palliative Care, The Division of Palliative Care Medicine, Department of Oncology, and the Faculty of Physical Education and Recreation, University of Alberta, Cross Cancer Institute, Edmonton, Alberta, Canada
- Received 23 March 2011. Accepted 29 July 2011. Available online 12 October 2011.
- http://dx.doi.org/10.1016/j.suponc.2011.07.005, How to Cite or Link Using DOI
Abstract
Background
Increasing evidence points to the theory of planned behavior as a useful framework to understand physical activity behavior in cancer patients.
Objective
Our primary aim was to examine the demographic, medical, and social–cognitive correlates of physical activity in palliative cancer patients.
Methods
A cross-sectional survey was administered to advanced cancer patients aged 18 years or older with a clinician-estimated life expectancy of less than 12 months and Palliative Performance Scale >30%, from outpatient palliative care, oncology clinics, and palliative home care.
Results
Fifty participants were recruited. Correlates of total physical activity levels were affective attitude (r = 0.36, P = .011), self-efficacy (r = 0.36, P = .010), and intention (r = 0.30, P = .034). Participants who reported 60 minutes or more of total physical activity daily reported significantly higher affective attitude (M = 0.9, 95% confidence interval [CI] 0.26–1.6, P = .008) and self-efficacy (M = 0.8, 95% CI 0.0–1.5, P = .046). Participants <60 years of age (M = 343, 95% CI −7 to 693, P = .054) and who were normal or underweight (M = 333, 95% CI −14 to 680, P = .059) reported higher weekly minutes of total physical activity.
Limitations
Our small sample may not be representative of the total palliative cancer population.
Conclusions
Affective attitude, self-efficacy, and intention were the strongest correlates of total physical activity levels, and younger and normal/underweight participants did more physical activity.
Determinants of Physical Activity in Palliative Cancer Patients: An Application of the Theory of Planned Behavior
- Department of Symptom Control and Palliative Care, The Division of Palliative Care Medicine, Department of Oncology, and the Faculty of Physical Education and Recreation, University of Alberta, Cross Cancer Institute, Edmonton, Alberta, Canada
- Received 23 March 2011. Accepted 29 July 2011. Available online 12 October 2011.
- http://dx.doi.org/10.1016/j.suponc.2011.07.005, How to Cite or Link Using DOI
Abstract
Background
Increasing evidence points to the theory of planned behavior as a useful framework to understand physical activity behavior in cancer patients.
Objective
Our primary aim was to examine the demographic, medical, and social–cognitive correlates of physical activity in palliative cancer patients.
Methods
A cross-sectional survey was administered to advanced cancer patients aged 18 years or older with a clinician-estimated life expectancy of less than 12 months and Palliative Performance Scale >30%, from outpatient palliative care, oncology clinics, and palliative home care.
Results
Fifty participants were recruited. Correlates of total physical activity levels were affective attitude (r = 0.36, P = .011), self-efficacy (r = 0.36, P = .010), and intention (r = 0.30, P = .034). Participants who reported 60 minutes or more of total physical activity daily reported significantly higher affective attitude (M = 0.9, 95% confidence interval [CI] 0.26–1.6, P = .008) and self-efficacy (M = 0.8, 95% CI 0.0–1.5, P = .046). Participants <60 years of age (M = 343, 95% CI −7 to 693, P = .054) and who were normal or underweight (M = 333, 95% CI −14 to 680, P = .059) reported higher weekly minutes of total physical activity.
Limitations
Our small sample may not be representative of the total palliative cancer population.
Conclusions
Affective attitude, self-efficacy, and intention were the strongest correlates of total physical activity levels, and younger and normal/underweight participants did more physical activity.
Community-Based Surveillance in Clinical Stage I Germ Cell Tumors
Objective: Although depression is prevalent among cancer patients, it remains underdiagnosed and undertreated. Quality of life is an important outcome in cancer patients and can be measured by questionnaires such as the Functional Assessment of Cancer Therapy-General version (FACT-G). The purpose of our study was to establish whether or not a group of items in FACT-G could be used as a screening tool for depression as well as for assessing quality of life.
Methods: A total of 62 chemotherapy patients (median age, 62 years [range, 22-81 years]; 55% women) completed Zung Self-Rating Depression Scale (ZSDS) and FACT-G questionnaires. Patients with ZSDS scores of 40 or more underwent clinical interviews for major depression. Pearson’s correlation was used to examine the relationship between the ZSDS and FACT-G scores. FACT-G score results were then analyzed to evaluate if subsets of the FACT-G can be used as a screening tool for major depression.
Results: In all, 30 of 62 patients (48%) had ZSDS scores 40 and were ruled out for major depression, and 30 of the 32 patients with ZSDS scores 40 participated clinical interviews. Of those who were interviewed, 7 patients (23%) were confirmed to have major depression. Overall, the prevalence of major depression was 7 of 60 patients (12%; 95% CI: 5%-23%). The ZSDS and FACT-G scores had strong correlation (r -0.75). The composite score of six statements in FACT-G were found to have sensitivity of 100% and specificity of 81% in predicting major depression, using a cut-off value of 12 (range, 0-24). The six statements were, I have a lack of energy; I feel sad; I feel nervous; I am able to enjoy life; I am sleeping well; and I am enjoying the things I usually do for fun.
Conclusions: The prevalence of major depression among all participants was 12%. The ZSDS score and FACT-G score had strong correlation; the subsets of FACT-G may be useful as a screening tool for depression.
*For a PDF of the full article, click on the link to the left of this introduction.
Objective: Although depression is prevalent among cancer patients, it remains underdiagnosed and undertreated. Quality of life is an important outcome in cancer patients and can be measured by questionnaires such as the Functional Assessment of Cancer Therapy-General version (FACT-G). The purpose of our study was to establish whether or not a group of items in FACT-G could be used as a screening tool for depression as well as for assessing quality of life.
Methods: A total of 62 chemotherapy patients (median age, 62 years [range, 22-81 years]; 55% women) completed Zung Self-Rating Depression Scale (ZSDS) and FACT-G questionnaires. Patients with ZSDS scores of 40 or more underwent clinical interviews for major depression. Pearson’s correlation was used to examine the relationship between the ZSDS and FACT-G scores. FACT-G score results were then analyzed to evaluate if subsets of the FACT-G can be used as a screening tool for major depression.
Results: In all, 30 of 62 patients (48%) had ZSDS scores 40 and were ruled out for major depression, and 30 of the 32 patients with ZSDS scores 40 participated clinical interviews. Of those who were interviewed, 7 patients (23%) were confirmed to have major depression. Overall, the prevalence of major depression was 7 of 60 patients (12%; 95% CI: 5%-23%). The ZSDS and FACT-G scores had strong correlation (r -0.75). The composite score of six statements in FACT-G were found to have sensitivity of 100% and specificity of 81% in predicting major depression, using a cut-off value of 12 (range, 0-24). The six statements were, I have a lack of energy; I feel sad; I feel nervous; I am able to enjoy life; I am sleeping well; and I am enjoying the things I usually do for fun.
Conclusions: The prevalence of major depression among all participants was 12%. The ZSDS score and FACT-G score had strong correlation; the subsets of FACT-G may be useful as a screening tool for depression.
*For a PDF of the full article, click on the link to the left of this introduction.
Objective: Although depression is prevalent among cancer patients, it remains underdiagnosed and undertreated. Quality of life is an important outcome in cancer patients and can be measured by questionnaires such as the Functional Assessment of Cancer Therapy-General version (FACT-G). The purpose of our study was to establish whether or not a group of items in FACT-G could be used as a screening tool for depression as well as for assessing quality of life.
Methods: A total of 62 chemotherapy patients (median age, 62 years [range, 22-81 years]; 55% women) completed Zung Self-Rating Depression Scale (ZSDS) and FACT-G questionnaires. Patients with ZSDS scores of 40 or more underwent clinical interviews for major depression. Pearson’s correlation was used to examine the relationship between the ZSDS and FACT-G scores. FACT-G score results were then analyzed to evaluate if subsets of the FACT-G can be used as a screening tool for major depression.
Results: In all, 30 of 62 patients (48%) had ZSDS scores 40 and were ruled out for major depression, and 30 of the 32 patients with ZSDS scores 40 participated clinical interviews. Of those who were interviewed, 7 patients (23%) were confirmed to have major depression. Overall, the prevalence of major depression was 7 of 60 patients (12%; 95% CI: 5%-23%). The ZSDS and FACT-G scores had strong correlation (r -0.75). The composite score of six statements in FACT-G were found to have sensitivity of 100% and specificity of 81% in predicting major depression, using a cut-off value of 12 (range, 0-24). The six statements were, I have a lack of energy; I feel sad; I feel nervous; I am able to enjoy life; I am sleeping well; and I am enjoying the things I usually do for fun.
Conclusions: The prevalence of major depression among all participants was 12%. The ZSDS score and FACT-G score had strong correlation; the subsets of FACT-G may be useful as a screening tool for depression.
*For a PDF of the full article, click on the link to the left of this introduction.
Retrospective Study of Patients with Metastatic Triple-Negative Breast Cancer: Survival, Health Care Utilization, and Cost
Background: Triple-negative breast cancer (TNBC) is a subset of breast cancer. Health care cost and utilization data for TNBC are lacking.
Objective: We examined differences between metastatic TNBC and metastatic non-TNBC in survival and health care costs and utilization.
Methods: This retrospective analysis of metastatic TNBC (134 patients) and metastatic non-TNBC (445 patients) used a proprietary oncology registry, the Impact Intelligence Oncology Management registry database, linked with health insurance claims and social security mortality data.
Results: We found metastatic patients whose breast cancer is triple negative to be younger (56.49 vs 59.24 years), to be more likely to have recurrent disease (64.93 vs 45.39%), and to have greater mortality vs metastatic non-TNBC patients (67.16 vs 50.79%) (all P less than .05). Recurrent patients with metastatic TNBC have the highest risk of death (HR, 1.9; P less than .001), whereas survival was greatest for de novo metastatic non-TNBC. Patients with metastatic TNBC had more all-cause annual hospitalizations, more hospitalized days, and higher total costs vs metastatic non-TNBC. Annual payer’s total costs, annual payer’s inpatient costs, cancer-related hospitalizations, and cancer-related inpatient costs also were greater among patients with metastatic TNBC.
Limitations: While the study spans slightly more than 2 years, 5-10 years would have been preferable to achieve a full clinical profile of indexed patients. The database also omitted factors that potentially confound the results, such as race and socioeconomic status.
Conclusions: Metastatic TNBC is associated with significant burden of disease and higher health care utilization vs metastatic non-TNBC, which may be due in part to the aggressive clinical course of the disease...
* For a PDF of the full article, click in the link to the left of this introduction.
Background: Triple-negative breast cancer (TNBC) is a subset of breast cancer. Health care cost and utilization data for TNBC are lacking.
Objective: We examined differences between metastatic TNBC and metastatic non-TNBC in survival and health care costs and utilization.
Methods: This retrospective analysis of metastatic TNBC (134 patients) and metastatic non-TNBC (445 patients) used a proprietary oncology registry, the Impact Intelligence Oncology Management registry database, linked with health insurance claims and social security mortality data.
Results: We found metastatic patients whose breast cancer is triple negative to be younger (56.49 vs 59.24 years), to be more likely to have recurrent disease (64.93 vs 45.39%), and to have greater mortality vs metastatic non-TNBC patients (67.16 vs 50.79%) (all P less than .05). Recurrent patients with metastatic TNBC have the highest risk of death (HR, 1.9; P less than .001), whereas survival was greatest for de novo metastatic non-TNBC. Patients with metastatic TNBC had more all-cause annual hospitalizations, more hospitalized days, and higher total costs vs metastatic non-TNBC. Annual payer’s total costs, annual payer’s inpatient costs, cancer-related hospitalizations, and cancer-related inpatient costs also were greater among patients with metastatic TNBC.
Limitations: While the study spans slightly more than 2 years, 5-10 years would have been preferable to achieve a full clinical profile of indexed patients. The database also omitted factors that potentially confound the results, such as race and socioeconomic status.
Conclusions: Metastatic TNBC is associated with significant burden of disease and higher health care utilization vs metastatic non-TNBC, which may be due in part to the aggressive clinical course of the disease...
* For a PDF of the full article, click in the link to the left of this introduction.
Background: Triple-negative breast cancer (TNBC) is a subset of breast cancer. Health care cost and utilization data for TNBC are lacking.
Objective: We examined differences between metastatic TNBC and metastatic non-TNBC in survival and health care costs and utilization.
Methods: This retrospective analysis of metastatic TNBC (134 patients) and metastatic non-TNBC (445 patients) used a proprietary oncology registry, the Impact Intelligence Oncology Management registry database, linked with health insurance claims and social security mortality data.
Results: We found metastatic patients whose breast cancer is triple negative to be younger (56.49 vs 59.24 years), to be more likely to have recurrent disease (64.93 vs 45.39%), and to have greater mortality vs metastatic non-TNBC patients (67.16 vs 50.79%) (all P less than .05). Recurrent patients with metastatic TNBC have the highest risk of death (HR, 1.9; P less than .001), whereas survival was greatest for de novo metastatic non-TNBC. Patients with metastatic TNBC had more all-cause annual hospitalizations, more hospitalized days, and higher total costs vs metastatic non-TNBC. Annual payer’s total costs, annual payer’s inpatient costs, cancer-related hospitalizations, and cancer-related inpatient costs also were greater among patients with metastatic TNBC.
Limitations: While the study spans slightly more than 2 years, 5-10 years would have been preferable to achieve a full clinical profile of indexed patients. The database also omitted factors that potentially confound the results, such as race and socioeconomic status.
Conclusions: Metastatic TNBC is associated with significant burden of disease and higher health care utilization vs metastatic non-TNBC, which may be due in part to the aggressive clinical course of the disease...
* For a PDF of the full article, click in the link to the left of this introduction.
Documenting the Symptom Experience of Cancer Patients
Volume 9, Issue 6, November-December 2011, Pages 216-223
| doi:10.1016/j.suponc.2011.06.003 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Teresa L. Deshields PhD 
Received 11 January 2011; Accepted 9 June 2011. Available online 3 November 2011.
Abstract
Background
Cancer patients experience symptoms associated with their disease, treatment, and comorbidities. Symptom experience is complicated, reflecting symptom prevalence, frequency, and severity. Symptom burden is associated with treatment tolerance as well as patients' quality of life (QOL).
Objectives
The purpose of this study was to document the symptom experience and QOL of patients with commonly diagnosed cancers. The relationship between symptoms and QOL was also explored.
Methods
A convenience sample of patients with the five most common cancers at a comprehensive cancer center completed surveys assessing symptom experience (Memorial Symptom Assessment Survey) and QOL (Functional Assessment of Cancer Therapy). Patients completed surveys at baseline and at 3, 6, 9, and 12 months thereafter. This article describes the study's baseline findings.
Results
Surveys were completed by 558 cancer patients with breast, colorectal, gynecologic, lung, or prostate cancer. Patients reported an average of 9.1 symptoms, with symptom experience varying by cancer type. The mean overall QOL for the total sample was 85.1, with results differing by cancer type. Prostate cancer patients reported the lowest symptom burden and the highest QOL.
Limitations
The sample was limited in terms of racial diversity. Because of the method of recruitment, baseline data were collected 6–8 months after diagnosis, meaning that participants were at various stages of treatment.
Conclusions
The symptom experience of cancer patients varies widely depending on cancer type. Nevertheless, most patients report symptoms, regardless of whether or not they are currently receiving treatment. Patients' QOL is inversely related to their symptom burden.
Volume 9, Issue 6, November-December 2011, Pages 216-223
Volume 9, Issue 6, November-December 2011, Pages 216-223
| doi:10.1016/j.suponc.2011.06.003 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Teresa L. Deshields PhD
Received 11 January 2011; Accepted 9 June 2011. Available online 3 November 2011.
Abstract
Background
Cancer patients experience symptoms associated with their disease, treatment, and comorbidities. Symptom experience is complicated, reflecting symptom prevalence, frequency, and severity. Symptom burden is associated with treatment tolerance as well as patients' quality of life (QOL).
Objectives
The purpose of this study was to document the symptom experience and QOL of patients with commonly diagnosed cancers. The relationship between symptoms and QOL was also explored.
Methods
A convenience sample of patients with the five most common cancers at a comprehensive cancer center completed surveys assessing symptom experience (Memorial Symptom Assessment Survey) and QOL (Functional Assessment of Cancer Therapy). Patients completed surveys at baseline and at 3, 6, 9, and 12 months thereafter. This article describes the study's baseline findings.
Results
Surveys were completed by 558 cancer patients with breast, colorectal, gynecologic, lung, or prostate cancer. Patients reported an average of 9.1 symptoms, with symptom experience varying by cancer type. The mean overall QOL for the total sample was 85.1, with results differing by cancer type. Prostate cancer patients reported the lowest symptom burden and the highest QOL.
Limitations
The sample was limited in terms of racial diversity. Because of the method of recruitment, baseline data were collected 6–8 months after diagnosis, meaning that participants were at various stages of treatment.
Conclusions
The symptom experience of cancer patients varies widely depending on cancer type. Nevertheless, most patients report symptoms, regardless of whether or not they are currently receiving treatment. Patients' QOL is inversely related to their symptom burden.
Volume 9, Issue 6, November-December 2011, Pages 216-223
Volume 9, Issue 6, November-December 2011, Pages 216-223
| doi:10.1016/j.suponc.2011.06.003 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Teresa L. Deshields PhD
Received 11 January 2011; Accepted 9 June 2011. Available online 3 November 2011.
Abstract
Background
Cancer patients experience symptoms associated with their disease, treatment, and comorbidities. Symptom experience is complicated, reflecting symptom prevalence, frequency, and severity. Symptom burden is associated with treatment tolerance as well as patients' quality of life (QOL).
Objectives
The purpose of this study was to document the symptom experience and QOL of patients with commonly diagnosed cancers. The relationship between symptoms and QOL was also explored.
Methods
A convenience sample of patients with the five most common cancers at a comprehensive cancer center completed surveys assessing symptom experience (Memorial Symptom Assessment Survey) and QOL (Functional Assessment of Cancer Therapy). Patients completed surveys at baseline and at 3, 6, 9, and 12 months thereafter. This article describes the study's baseline findings.
Results
Surveys were completed by 558 cancer patients with breast, colorectal, gynecologic, lung, or prostate cancer. Patients reported an average of 9.1 symptoms, with symptom experience varying by cancer type. The mean overall QOL for the total sample was 85.1, with results differing by cancer type. Prostate cancer patients reported the lowest symptom burden and the highest QOL.
Limitations
The sample was limited in terms of racial diversity. Because of the method of recruitment, baseline data were collected 6–8 months after diagnosis, meaning that participants were at various stages of treatment.
Conclusions
The symptom experience of cancer patients varies widely depending on cancer type. Nevertheless, most patients report symptoms, regardless of whether or not they are currently receiving treatment. Patients' QOL is inversely related to their symptom burden.
Volume 9, Issue 6, November-December 2011, Pages 216-223
Efficacy and Safety of Fentanyl Pectin Nasal Spray Compared with Immediate-Release Morphine Sulfate Tablets in the Treatment of Breakthrough Cancer Pain: A Multicenter, Randomized, Controlled, Double-Blind, Double-Dummy Multiple-Crossover Study
Volume 9, Issue 6, November-December 2011, Pages 224-231
| doi:10.1016/j.suponc.2011.07.004 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Marie Fallon MB, ChB, MD, FRCP
Received 10 February 2011; Accepted 18 July 2011. Available online 3 November 2011.
Background
Immediate-release morphine sulfate (IRMS) remains the standard treatment for breakthrough cancer pain (BTCP), but its onset of effect does not match the rapid onset and short duration of most BTCP episodes.
Objective
This study will evaluate the efficacy/tolerability of fentanyl pectin nasal spray (FPNS) compared with IRMS for BTCP.
Methods
Patients (n = 110) experiencing one to four BTCP episodes/day while taking ≥60 mg/day oral morphine (or equivalent) for background cancer pain entered a double-blind, double-dummy (DB/DD), multiple-crossover study. Patients completing a titration phase (n = 84) continued to a DB/DD phase: 10 episodes of BTCP were randomly treated with FPNS and oral capsule placebo (five episodes) or IRMS and nasal spray placebo (5 episodes). The primary end point was pain intensity (P < .05 FPNS vs. IRMS) difference from baseline at 15 minutes (PID15). Secondary end points were onset of pain intensity (PI) decrease (≥1-point) and time to clinically meaningful pain relief (CMPR, ≥2-point PI decrease). Safety and tolerability were evaluated by adverse events (AEs) and nasal assessments. By-patient and by-episode analyses were completed.
Results
Compared with IRMS, FPNS significantly improved mean PID15 scores. 57.5% of FPNS-treated episodes significantly demonstrated onset of PI improvement by 5 minutes and 95.7% by 30 minutes. CMPR (≥2-point PI decrease) was seen in 52.4% of episodes by 10 minutes. Only 4.7% of patients withdrew from titration (2.4% in DB/DD phase) because of AEs; no significant nasal effects were reported.
Conclusion
FPNS was efficacious and well tolerated in the treatment of BTCP and provided faster onset of analgesia and attainment of CMPR than IRMS.
The authors acknowledge i3Research, which conducted the study; the technical and editorial support provided by Anita Chadha-Patel at ApotheCom; and the Fentanyl Nasal Spray Study 044 Investigators. This study was sponsored by Archimedes Development, Ltd.
Conflicts of interest Disclosure: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr. Davies has served as a consultant for Archimedes and received support from Archimedes to travel to meetings to present trial data. No other conflicts of interest were reported.
 |  |
Volume 9, Issue 6, November-December 2011, Pages 224-231
| doi:10.1016/j.suponc.2011.07.004 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Marie Fallon MB, ChB, MD, FRCP
Received 10 February 2011; Accepted 18 July 2011. Available online 3 November 2011.
Background
Immediate-release morphine sulfate (IRMS) remains the standard treatment for breakthrough cancer pain (BTCP), but its onset of effect does not match the rapid onset and short duration of most BTCP episodes.
Objective
This study will evaluate the efficacy/tolerability of fentanyl pectin nasal spray (FPNS) compared with IRMS for BTCP.
Methods
Patients (n = 110) experiencing one to four BTCP episodes/day while taking ≥60 mg/day oral morphine (or equivalent) for background cancer pain entered a double-blind, double-dummy (DB/DD), multiple-crossover study. Patients completing a titration phase (n = 84) continued to a DB/DD phase: 10 episodes of BTCP were randomly treated with FPNS and oral capsule placebo (five episodes) or IRMS and nasal spray placebo (5 episodes). The primary end point was pain intensity (P < .05 FPNS vs. IRMS) difference from baseline at 15 minutes (PID15). Secondary end points were onset of pain intensity (PI) decrease (≥1-point) and time to clinically meaningful pain relief (CMPR, ≥2-point PI decrease). Safety and tolerability were evaluated by adverse events (AEs) and nasal assessments. By-patient and by-episode analyses were completed.
Results
Compared with IRMS, FPNS significantly improved mean PID15 scores. 57.5% of FPNS-treated episodes significantly demonstrated onset of PI improvement by 5 minutes and 95.7% by 30 minutes. CMPR (≥2-point PI decrease) was seen in 52.4% of episodes by 10 minutes. Only 4.7% of patients withdrew from titration (2.4% in DB/DD phase) because of AEs; no significant nasal effects were reported.
Conclusion
FPNS was efficacious and well tolerated in the treatment of BTCP and provided faster onset of analgesia and attainment of CMPR than IRMS.
The authors acknowledge i3Research, which conducted the study; the technical and editorial support provided by Anita Chadha-Patel at ApotheCom; and the Fentanyl Nasal Spray Study 044 Investigators. This study was sponsored by Archimedes Development, Ltd.
Conflicts of interest Disclosure: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr. Davies has served as a consultant for Archimedes and received support from Archimedes to travel to meetings to present trial data. No other conflicts of interest were reported.
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Volume 9, Issue 6, November-December 2011, Pages 224-231
| doi:10.1016/j.suponc.2011.07.004 | How to Cite or Link Using DOI |
| Permissions & Reprints |
Original research
Marie Fallon MB, ChB, MD, FRCP
Received 10 February 2011; Accepted 18 July 2011. Available online 3 November 2011.
Background
Immediate-release morphine sulfate (IRMS) remains the standard treatment for breakthrough cancer pain (BTCP), but its onset of effect does not match the rapid onset and short duration of most BTCP episodes.
Objective
This study will evaluate the efficacy/tolerability of fentanyl pectin nasal spray (FPNS) compared with IRMS for BTCP.
Methods
Patients (n = 110) experiencing one to four BTCP episodes/day while taking ≥60 mg/day oral morphine (or equivalent) for background cancer pain entered a double-blind, double-dummy (DB/DD), multiple-crossover study. Patients completing a titration phase (n = 84) continued to a DB/DD phase: 10 episodes of BTCP were randomly treated with FPNS and oral capsule placebo (five episodes) or IRMS and nasal spray placebo (5 episodes). The primary end point was pain intensity (P < .05 FPNS vs. IRMS) difference from baseline at 15 minutes (PID15). Secondary end points were onset of pain intensity (PI) decrease (≥1-point) and time to clinically meaningful pain relief (CMPR, ≥2-point PI decrease). Safety and tolerability were evaluated by adverse events (AEs) and nasal assessments. By-patient and by-episode analyses were completed.
Results
Compared with IRMS, FPNS significantly improved mean PID15 scores. 57.5% of FPNS-treated episodes significantly demonstrated onset of PI improvement by 5 minutes and 95.7% by 30 minutes. CMPR (≥2-point PI decrease) was seen in 52.4% of episodes by 10 minutes. Only 4.7% of patients withdrew from titration (2.4% in DB/DD phase) because of AEs; no significant nasal effects were reported.
Conclusion
FPNS was efficacious and well tolerated in the treatment of BTCP and provided faster onset of analgesia and attainment of CMPR than IRMS.
The authors acknowledge i3Research, which conducted the study; the technical and editorial support provided by Anita Chadha-Patel at ApotheCom; and the Fentanyl Nasal Spray Study 044 Investigators. This study was sponsored by Archimedes Development, Ltd.
Conflicts of interest Disclosure: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr. Davies has served as a consultant for Archimedes and received support from Archimedes to travel to meetings to present trial data. No other conflicts of interest were reported.
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The impact of bone metastases and skeletal-related events on healthcare costs in prostate cancer patients receiving hormonal therapy
Bone is the most common site of metastases in men with advanced prostate cancer, one of the most prevalent cancers in the United States and the second leading cause of cancer death after lung cancer.1–3 The median survival from diagnosis of bone metastases is 30–40 months.2 During this time, skeletal-related events (SREs), including pathologic fractures, surgery or radiation to the bone, spinal cord compression, or hypercalcemia of malignancy, can occur. SREs are associated with considerable morbidity, impaired health-related quality of life, reduced survival, and increased costs.4–10
Although studies have examined the impact of SREs on costs in patients with advanced cancers and bone metastases,5–9,11 the effects of bone metastases without SREs on healthcare costs in prostate cancer patients have not been studied. The magnitude of these costs may be important in economic evaluations of treatments to prevent or delay bone metastases in prostate cancer patients. The objective of this study was to estimate the effects on healthcare costs of bone metastases in the presence and absence of SREs in men with prostate cancer who were receiving hormonal therapy.
* For a PDF of the full article, click in the link to the left of this introduction.
Bone is the most common site of metastases in men with advanced prostate cancer, one of the most prevalent cancers in the United States and the second leading cause of cancer death after lung cancer.1–3 The median survival from diagnosis of bone metastases is 30–40 months.2 During this time, skeletal-related events (SREs), including pathologic fractures, surgery or radiation to the bone, spinal cord compression, or hypercalcemia of malignancy, can occur. SREs are associated with considerable morbidity, impaired health-related quality of life, reduced survival, and increased costs.4–10
Although studies have examined the impact of SREs on costs in patients with advanced cancers and bone metastases,5–9,11 the effects of bone metastases without SREs on healthcare costs in prostate cancer patients have not been studied. The magnitude of these costs may be important in economic evaluations of treatments to prevent or delay bone metastases in prostate cancer patients. The objective of this study was to estimate the effects on healthcare costs of bone metastases in the presence and absence of SREs in men with prostate cancer who were receiving hormonal therapy.
* For a PDF of the full article, click in the link to the left of this introduction.
Bone is the most common site of metastases in men with advanced prostate cancer, one of the most prevalent cancers in the United States and the second leading cause of cancer death after lung cancer.1–3 The median survival from diagnosis of bone metastases is 30–40 months.2 During this time, skeletal-related events (SREs), including pathologic fractures, surgery or radiation to the bone, spinal cord compression, or hypercalcemia of malignancy, can occur. SREs are associated with considerable morbidity, impaired health-related quality of life, reduced survival, and increased costs.4–10
Although studies have examined the impact of SREs on costs in patients with advanced cancers and bone metastases,5–9,11 the effects of bone metastases without SREs on healthcare costs in prostate cancer patients have not been studied. The magnitude of these costs may be important in economic evaluations of treatments to prevent or delay bone metastases in prostate cancer patients. The objective of this study was to estimate the effects on healthcare costs of bone metastases in the presence and absence of SREs in men with prostate cancer who were receiving hormonal therapy.
* For a PDF of the full article, click in the link to the left of this introduction.
Olanzapine Versus Aprepitant for the Prevention of Chemotherapy-Induced Nausea and Vomiting: A Randomized Phase III Trial
Volume 9, Issue 5, September-October 2011, Pages 188-195
| doi:10.1016/j.suponc.2011.05.002 |
| Permissions & Reprints |
Original Research
Received 8 April 2011; Accepted 19 May 2011. Available online 24 September 2011.
Abstract
Background
The purpose of the study was to compare the effectiveness of olanzapine (OLN) and aprepitant (APR) for the prevention of chemotherapy-induced nausea and vomiting (CINV) in patients receiving highly emetogenic chemotherapy.
Methods
A phase III trial was performed in chemotherapy-naive patients receiving cisplatin ≥70 mg/m2 or cyclophosphamide ≥500 mg/m2 and doxorubicin ≥50 mg/m2, comparing OLN to APR in combination with palonosetron (PAL) and dexamethasone (DEX). The OLN, PAL, DEX (OPD) regimen was 10 mg of oral OLN, 0.25 mg of IV PAL, and 20 mg of IV DEX prechemotherapy, day 1, and 10 mg/day of oral OLN alone on days 2–4 postchemotherapy. The APR, PAL, DEX (APD) regimen was 125 mg of oral APR, 0.25 mg of IV PAL, and 12 mg of IV DEX, day 1, and 80 mg of oral APR, days 2 and 3, and 4 mg of DEX BID, days 2–4. Two hundred fifty-one patients consented to the protocol and were randomized. Two hundred forty-one patients were evaluable.
Results
Complete response (CR) (no emesis, no rescue) was 97% for the acute period (24 hours postchemotherapy), 77% for the delayed period (days 2–5 postchemotherapy), and 77% for the overall period (0–120 hours) for 121 patients receiving the OPD regimen. CR was 87% for the acute period, 73% for the delayed period, and 73% for the overall period in 120 patients receiving the APD regimen. Patients without nausea (0, scale 0–10, MD Anderson Symptom Inventory) were OPD: 87% acute, 69% delayed, and 69% overall; APD: 87% acute, 38% delayed, and 38% overall. There were no grade 3 or 4 toxicities. CR and control of nausea in subsequent chemotherapy cycles were equal to or greater than cycle 1 for both regimens. OPD was comparable to APD in the control of CINV. Nausea was better controlled with OPD.
Discussion
In this study, OLN combined with a single dose of DEX and a single dose of PAL was very effective at controlling acute and delayed CINV in patients receiving highly emetogenic chemotherapy. CR rates were not significantly different from a similar group of patients receiving highly emetogenic chemotherapy and an antiemetic regimen consisting of APR, PAL, and DEX.
Volume 9, Issue 5, September-October 2011, Pages 188-195
Volume 9, Issue 5, September-October 2011, Pages 188-195
| doi:10.1016/j.suponc.2011.05.002 |
| Permissions & Reprints |
Original Research
Received 8 April 2011; Accepted 19 May 2011. Available online 24 September 2011.
Abstract
Background
The purpose of the study was to compare the effectiveness of olanzapine (OLN) and aprepitant (APR) for the prevention of chemotherapy-induced nausea and vomiting (CINV) in patients receiving highly emetogenic chemotherapy.
Methods
A phase III trial was performed in chemotherapy-naive patients receiving cisplatin ≥70 mg/m2 or cyclophosphamide ≥500 mg/m2 and doxorubicin ≥50 mg/m2, comparing OLN to APR in combination with palonosetron (PAL) and dexamethasone (DEX). The OLN, PAL, DEX (OPD) regimen was 10 mg of oral OLN, 0.25 mg of IV PAL, and 20 mg of IV DEX prechemotherapy, day 1, and 10 mg/day of oral OLN alone on days 2–4 postchemotherapy. The APR, PAL, DEX (APD) regimen was 125 mg of oral APR, 0.25 mg of IV PAL, and 12 mg of IV DEX, day 1, and 80 mg of oral APR, days 2 and 3, and 4 mg of DEX BID, days 2–4. Two hundred fifty-one patients consented to the protocol and were randomized. Two hundred forty-one patients were evaluable.
Results
Complete response (CR) (no emesis, no rescue) was 97% for the acute period (24 hours postchemotherapy), 77% for the delayed period (days 2–5 postchemotherapy), and 77% for the overall period (0–120 hours) for 121 patients receiving the OPD regimen. CR was 87% for the acute period, 73% for the delayed period, and 73% for the overall period in 120 patients receiving the APD regimen. Patients without nausea (0, scale 0–10, MD Anderson Symptom Inventory) were OPD: 87% acute, 69% delayed, and 69% overall; APD: 87% acute, 38% delayed, and 38% overall. There were no grade 3 or 4 toxicities. CR and control of nausea in subsequent chemotherapy cycles were equal to or greater than cycle 1 for both regimens. OPD was comparable to APD in the control of CINV. Nausea was better controlled with OPD.
Discussion
In this study, OLN combined with a single dose of DEX and a single dose of PAL was very effective at controlling acute and delayed CINV in patients receiving highly emetogenic chemotherapy. CR rates were not significantly different from a similar group of patients receiving highly emetogenic chemotherapy and an antiemetic regimen consisting of APR, PAL, and DEX.
Volume 9, Issue 5, September-October 2011, Pages 188-195
Volume 9, Issue 5, September-October 2011, Pages 188-195
| doi:10.1016/j.suponc.2011.05.002 |
| Permissions & Reprints |
Original Research
Received 8 April 2011; Accepted 19 May 2011. Available online 24 September 2011.
Abstract
Background
The purpose of the study was to compare the effectiveness of olanzapine (OLN) and aprepitant (APR) for the prevention of chemotherapy-induced nausea and vomiting (CINV) in patients receiving highly emetogenic chemotherapy.
Methods
A phase III trial was performed in chemotherapy-naive patients receiving cisplatin ≥70 mg/m2 or cyclophosphamide ≥500 mg/m2 and doxorubicin ≥50 mg/m2, comparing OLN to APR in combination with palonosetron (PAL) and dexamethasone (DEX). The OLN, PAL, DEX (OPD) regimen was 10 mg of oral OLN, 0.25 mg of IV PAL, and 20 mg of IV DEX prechemotherapy, day 1, and 10 mg/day of oral OLN alone on days 2–4 postchemotherapy. The APR, PAL, DEX (APD) regimen was 125 mg of oral APR, 0.25 mg of IV PAL, and 12 mg of IV DEX, day 1, and 80 mg of oral APR, days 2 and 3, and 4 mg of DEX BID, days 2–4. Two hundred fifty-one patients consented to the protocol and were randomized. Two hundred forty-one patients were evaluable.
Results
Complete response (CR) (no emesis, no rescue) was 97% for the acute period (24 hours postchemotherapy), 77% for the delayed period (days 2–5 postchemotherapy), and 77% for the overall period (0–120 hours) for 121 patients receiving the OPD regimen. CR was 87% for the acute period, 73% for the delayed period, and 73% for the overall period in 120 patients receiving the APD regimen. Patients without nausea (0, scale 0–10, MD Anderson Symptom Inventory) were OPD: 87% acute, 69% delayed, and 69% overall; APD: 87% acute, 38% delayed, and 38% overall. There were no grade 3 or 4 toxicities. CR and control of nausea in subsequent chemotherapy cycles were equal to or greater than cycle 1 for both regimens. OPD was comparable to APD in the control of CINV. Nausea was better controlled with OPD.
Discussion
In this study, OLN combined with a single dose of DEX and a single dose of PAL was very effective at controlling acute and delayed CINV in patients receiving highly emetogenic chemotherapy. CR rates were not significantly different from a similar group of patients receiving highly emetogenic chemotherapy and an antiemetic regimen consisting of APR, PAL, and DEX.
Volume 9, Issue 5, September-October 2011, Pages 188-195
The wearable external cardiac defibrillator for cancer patients at risk for sudden cardiac death
Implantable cardioverter defibrillators (ICDs) are indicated for primary prevention of sudden cardiac death (SCD) in patients with reduced left ventricular function (an ejection fraction of ≤ 35%). ICD therapy is also recommended for secondary prevention of SCD in patients with a life-threatening cardiac arrhythmia, including aborted sudden cardiac death. Contraindications to ICD therapy are life expectancy ≤ 1 year, incessant arrhythmia, significant psychiatric illness, syncope without evidence of inducible ventricular arrhythmia or structural heart disease, ventricular arrhythmia amenable to catheter ablation, ventricular arrhythmia due to a reversible cause, and primary prevention of SCD in patients ineligible for cardiac transplantation or cardiac resynchronization therapy.1 In addition, relative contraindications to ICD therapy include the need for radiation therapy to the thorax, high risk for infection, and high risk for deep venous thrombosis.
A subset of patients with cancer is at risk for SCD due to a variety of cardiac causes, including chemotherapy-induced cardiomyopathy or druginduced long QT syndrome. These patients may benefit from ICD placement. However, the aforementioned relative contraindications for permanent defibrillator implantation often coexist in patients with cancer. Moreover, an individual with acute malignancy may have other contraindications for permanent defibrillator implantation, including the potential reversibility of cardiomyopathy or arrhythmia or an unclear prognosis for 1-year survival. ...
* For a PDF of the full article, click in the link to the left of this introduction.
Implantable cardioverter defibrillators (ICDs) are indicated for primary prevention of sudden cardiac death (SCD) in patients with reduced left ventricular function (an ejection fraction of ≤ 35%). ICD therapy is also recommended for secondary prevention of SCD in patients with a life-threatening cardiac arrhythmia, including aborted sudden cardiac death. Contraindications to ICD therapy are life expectancy ≤ 1 year, incessant arrhythmia, significant psychiatric illness, syncope without evidence of inducible ventricular arrhythmia or structural heart disease, ventricular arrhythmia amenable to catheter ablation, ventricular arrhythmia due to a reversible cause, and primary prevention of SCD in patients ineligible for cardiac transplantation or cardiac resynchronization therapy.1 In addition, relative contraindications to ICD therapy include the need for radiation therapy to the thorax, high risk for infection, and high risk for deep venous thrombosis.
A subset of patients with cancer is at risk for SCD due to a variety of cardiac causes, including chemotherapy-induced cardiomyopathy or druginduced long QT syndrome. These patients may benefit from ICD placement. However, the aforementioned relative contraindications for permanent defibrillator implantation often coexist in patients with cancer. Moreover, an individual with acute malignancy may have other contraindications for permanent defibrillator implantation, including the potential reversibility of cardiomyopathy or arrhythmia or an unclear prognosis for 1-year survival. ...
* For a PDF of the full article, click in the link to the left of this introduction.
Implantable cardioverter defibrillators (ICDs) are indicated for primary prevention of sudden cardiac death (SCD) in patients with reduced left ventricular function (an ejection fraction of ≤ 35%). ICD therapy is also recommended for secondary prevention of SCD in patients with a life-threatening cardiac arrhythmia, including aborted sudden cardiac death. Contraindications to ICD therapy are life expectancy ≤ 1 year, incessant arrhythmia, significant psychiatric illness, syncope without evidence of inducible ventricular arrhythmia or structural heart disease, ventricular arrhythmia amenable to catheter ablation, ventricular arrhythmia due to a reversible cause, and primary prevention of SCD in patients ineligible for cardiac transplantation or cardiac resynchronization therapy.1 In addition, relative contraindications to ICD therapy include the need for radiation therapy to the thorax, high risk for infection, and high risk for deep venous thrombosis.
A subset of patients with cancer is at risk for SCD due to a variety of cardiac causes, including chemotherapy-induced cardiomyopathy or druginduced long QT syndrome. These patients may benefit from ICD placement. However, the aforementioned relative contraindications for permanent defibrillator implantation often coexist in patients with cancer. Moreover, an individual with acute malignancy may have other contraindications for permanent defibrillator implantation, including the potential reversibility of cardiomyopathy or arrhythmia or an unclear prognosis for 1-year survival. ...
* For a PDF of the full article, click in the link to the left of this introduction.
Attitudes toward Vaccination for Pandemic H1N1 and Seasonal Influenza in Patients with Hematologic Malignancies
Original research
Benjamin H. Chin-Yeea, Katherine Monkman MDa, Zafar Hussain MD, FRCP(C)a and Leonard A. Minuk MD, FRCP(C)
Background
Patients with hematologic malignancies are at increased risk of influenza and its complications. Despite current health recommendations and evidence favoring influenza vaccination, vaccination rates remain low in cancer patients.
Objective
The purpose of this study was to determine which factors influenced vaccination rates.
Methods
During the 2009–2010 pandemic H1N1 and seasonal influenza season, we surveyed patients with hematologic malignancies in a Canadian cancer center. Of the patients participating in our study (n = 129), 66% and 57% received the H1N1 pandemic influenza and seasonal influenza vaccines, respectively.
Results
A number of reasons for vaccination refusal were reported, most relating to general skepticism about the safety and efficacy of vaccination. Physician advice was also a factor influencing vaccination rates in patients. The vaccination rate for seasonal influenza was 39% in patients <65 years old, significantly lower than the rate of 73% reported for patients aged ≥65 years (P < 0.0001).
Conclusion
Future education programs should target younger patient populations and health-care workers, focusing on vaccine safety and efficacy in the high-risk cancer population.
Despite the annual development of effective influenza vaccines, influenza remains a significant cause of morbidity and mortality in Canada. In the 2009–2010 influenza season, approximately 40,000 Canadians were infected with seasonal influenza or the pandemic H1N1 influenza virus,1 and influenza has been estimated to cause 4,000–8,000 deaths in Canada each year.2 It is estimated that a severe influenza pandemic could result in a 1% reduction in annual gross domestic product in Canada.3
Patients with hematologic malignancies are known to be at increased risk of influenza and its complications, with estimated mortality rates in the range 5%–27%.[4], [5], [6], [7] and [8] Evidence for the efficacy of the influenza vaccine is limited and contradictory, and many assume that immunocompromised patients will not be able to generate a protective antibody response. Nonetheless, current evidence favors vaccination.9 Pollyea et al10 reported that eight of 15 trials on the efficacy of vaccination in patients with hematologic malignancies concluded that vaccination was beneficial. Both the Centers for Disease Control and Prevention (CDC) and the Public Health Agency of Canada (PHAC) advised that all immunocompromised patients, including those with cancer, receive both the seasonal influenza vaccine and the pandemic H1N1 influenza vaccine in the 2009–2010 influenza season.[11] and [12]
Despite these recommendations, rates of influenza vaccination remain low for the general population and cancer patients in Canada, with rates reported at 40% and 65% respectively.[13] and [14] A recent study by Yee et al15 reported similarly low influenza vaccination rates of 58% in cancer patients in the United States. Vaccination has long been a controversial public health issue, and many people choose not to be vaccinated due to fears that vaccines may not be safe and effective.[16], [17] and [18] Lack of physician recommendation has also been cited as a significant factor in the decision to decline vaccination.16
In this study, we sought to determine what percentage of patients being treated for hematologic malignancies in an Ontario, Canada, cancer center received the H1N1 pandemic influenza vaccine in the 2009–2010 influenza season and to explore the barriers to vaccination in this high-risk population. We also collected information on the percentage of patients who received the seasonal influenza vaccine. It was general practice for physicians at this center to recommend influenza vaccination in accordance with the PHAC recommendations.
Methods
Patients being treated for hematologic malignancies at the London Regional Cancer Program (London, Canada) were invited to complete a survey regarding influenza vaccination (Appendix). The London Regional Cancer Program is a tertiary care center providing specialized cancer care to a population base of 1.2 million in southwestern Ontario. The survey was administered to patients eligible to participate in another study assessing antibody levels pre- and postvaccination with the H1N1 pandemic vaccine. Eligible patients were 18 years or older and being treated or followed for hematological malignancies at the London Regional Cancer Program who attended an appointment between October 28 and November 19, 2009, and returned for a follow-up visit between January 5 and March 26, 2010 (n = 151). Patients were asked if they had received the pandemic H1N1 influenza vaccine and the seasonal influenza vaccine during the 2009–2010 influenza season. Those who had declined vaccination were asked to describe the reasons for their choice. The survey provided a list of six possible reasons for declining vaccination and gave patients the option of writing in their own responses.
The results of the study were analyzed using InStat 3 software (GraphPad, La Jolla, CA). The Mann-Whitney U-test was used to compare continuous variables, and Fisher's exact test was used to compare proportions. The study was approved by the University of Western Ontario's Institutional Research Ethics Board (IRB 16627E).
Results
Of the 151 patients invited to participate, 129 completed the survey, yielding a response rate of 85%. Patient characteristics are shown in Table 1. The respondents ranged in age from 19 to 86 years, 56% were male and 44% were female, and patients aged 65 years or older comprised 52% of the study population. The mean age of the patient group was 62.7 ± 14.8 years. Overall 119 patients (92%) had received chemotherapy at some time during their illness, with 96 patients (76%) actively receiving chemotherapy, defined as treatment within the past 3 months. Diagnoses included acute leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, lymphoma, multiple myeloma, myelodysplastic syndromes, and myeloproliferative neoplasms.
Of the 129 patients surveyed, 85 (66%) reported that they had received the H1N1 pandemic influenza vaccine during the 2009–2010 influenza season. Fifty-seven percent had received the seasonal influenza vaccine, and 50% had received both the seasonal and the H1N1 vaccines. Of the 44 patients who did not receive the H1N1 vaccine, only three planned to receive it. Eight of the 56 patients not vaccinated with the seasonal influenza vaccine planned to receive it.
There were no significant differences in mean age, percentage of patients over 65 years old, gender, or chemotherapy status between patients who received the H1N1 vaccine and those who declined it (Table 1). The mean age of patients who received the seasonal influenza vaccine was significantly higher than that of those who did not (67.8 ±12.1 vs. 56.1 ± 15.5 years, P < 0.0001), and a significantly higher percentage of patients in the vaccinated group were over the age of 65 (67% vs. 33%, P < 0.0001).
Patient-reported reasons for not receiving the H1N1 vaccine are shown in Figure 1. The two most common reasons for declining vaccination were beliefs that “the vaccine is dangerous because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). The belief that vaccination was dangerous or not effective because of the patient's medical condition represented 16% and 12% of responses, respectively. Six percent responded that receiving the vaccine would have been too inconvenient. No patients reported concerns about pain at the injection site as a reason for avoiding vaccination. In the category of “other,” responses fell into four broad categories: “physician advised against vaccination” (8%), “vaccination is unnecessary” (8%), “previous bad experience from vaccine” (4%), and “vaccine will make me sick” (4%).
Discussion
Our study found that 66% of patients being treated for hematological malignancies at a southwestern Ontario cancer center received the H1N1 vaccine during the 2009–2010 influenza season. This was higher than the rate of H1N1 vaccination in the general Canadian population, which was reported as 41%.14 Canadian cancer patients have been previously shown to have higher rates of participation in vaccination programs. In 2005, 64% of Canadians with cancer received the seasonal influenza vaccine compared with 34% of the overall population.13 This trend may be driven in part by the higher average age of patients receiving cancer treatment as adults 65 years of age or older comprised 52% of the respondents in our study.
Worldwide, Canada ranks among the highest countries in vaccination coverage. The United Kingdom reported a vaccination rate of 28.7% during the 2007–2008 influenza season, which was at the time one of the highest in Europe.19 Other European countries, including Germany, Italy, and France, showed vaccination rates similar to that of the United Kingdom. In all of these countries vaccination coverage increased with age. The United States has vaccination rates most similar to those of Canada, estimated at 40% in the overall population and 68% in the population ≥65 years old during the 2009–2010 influenza season.20
Higher vaccination rates have been reported in the elderly compared to younger adult population,[13] and [14] and our findings prove to be consistent with this reported trend. In this study, the group vaccinated with the seasonal influenza vaccine had a mean age of 67.8 ± 12.1 years compared with the unvaccinated group aged 56.1 ± 15.5 years (P < 0.0001). Interestingly, there was no significant difference in mean age between the vaccinated and unvaccinated groups for the H1N1 pandemic influenza vaccine (P > 0.05). This was not entirely unexpected since public health campaigns during the 2009–2010 influenza season focused on the younger age group due to their increased susceptibility to severe H1N1 disease. Nonetheless, there was a trend toward an increased mean age for those who received the vaccine (64.0 ± 12.5 years) compared to those who did not (60.4 ± 18.4 years), and it is possible that statistical significance was not reached due to the small sample size. Our study reported an alarmingly low 39% vaccination rate for seasonal influenza in cancer patients <65, suggesting that the PHAC's message is not adequately reaching this potentially at-risk group.
Reasons for refusal of vaccination have been well described in previous studies.[16], [17], [18], [21], [22], [23], [24], [25] and [26] We found that the most common reasons for refusal of vaccination by cancer patients were very similar to those reported in healthy individuals. Specifically, concerns about the safety and efficacy of vaccines in general were more common than concerns related to cancer or chemotherapy. The most common reasons for refusal of vaccination were “I think the vaccine will be dangerous for people in general because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). Despite the publicity, 8% of unvaccinated patients responded that they did not feel that H1N1 influenza was a significant threat. In this study, the belief that the vaccine was dangerous because of lack of testing or a previous medical condition was responsible for 13% of patients not receiving the vaccine. Five percent of patients elected not to be vaccinated because of questions of efficacy. The H1N1 vaccine is an adjuvant with AsO3, which may cause more vaccine reactions, while the seasonal influenza vaccine is not an adjuvant. It is possible that the presence of adjuvant contributed to some patients' safety concerns, though we did not specifically ask if the adjuvant influenced their decision.
Physician advice may have played a significant role in patients' decisions to vaccinate. Eight percent of patients who did not receive the vaccine reported that they were not vaccinated due to advice from a physician. It is our routine institutional policy to recommend vaccination for all cancer patients irrespective of underlying diagnosis or treatment regimen. We do not, however, provide standardized written information to patients or referring physicians, so some patients may have been advised against vaccination by other physicians. Some primary care physicians might not have been familiar with the current PHAC recommendations or the recent literature suggesting the vaccine's potential benefits in this group. Public health campaigns should therefore seek to educate physicians as well as patients regarding the safety and efficacy of the influenza vaccine for cancer patients.
Conclusion
We found that rates of H1N1 and seasonal influenza vaccination in a southwestern Ontario cancer center were higher than those reported for the general population. Nevertheless, despite a large public health education campaign, a significant number of patients declined vaccination due to fear that it would not be safe or effective or due to a belief that vaccination was not necessary. Although the rate of seasonal influenza vaccination was high for those ≥65 years old, it was poor for those aged <65 years, despite vaccination being recommended for all adults with chronic medical conditions. Future education programs should target younger patient populations and health-care workers and focus on vaccine safety and efficacy in immunocompromised patients as well as in other high-risk groups.
References1
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2 Public Health Agency of Canada, Influenza http://www.phac-aspc.gc.ca/influenza/index-eng.php Accessed August 5, 2010.
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4 R.F. Chemaly, S. Ghosh, G.P. Bodey, N. Rohatgi, A. Safdar, M.J. Keating, R.E. Champlin, E.A. Aguilera, J.J. Tarrand and I.I. Raad, Respiratory viral infections in adults with hematologic malignancies and human stem cell transplantation recipients: a retrospective study at a major cancer center, Medicine 85 (5) (2006), pp. 278–287. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (66)
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17 R.K. Zimmerman, T.A. Santibanez, J.E. Janosky, M.J. Fine, M. Raymund, S.A. Wilson, I.J. Bardella, A.R. Medsger and M.P. Nowalk, What affects influenza vaccination rates among older patients?: An analysis from inner-city, suburban, rural, and Veterans Affairs practices, Am J Med 114 (1) (2003), pp. 31–38. Article |
18 M.W. Mah, N.A. Hagen, K. Pauling-Shepard, J.S. Hawthorne, M. Mysak, T. Lye and T.J. Louie, Understanding influenza vaccination attitudes at a Canadian cancer center, Am J Infect Control 33 (4) (2005), pp. 243–250. Article |
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21 X. Dedoukou, G. Nikolopoulos, A. Maragos, S. Giannoulidou and H.C. Maltezou, Attitudes towards vaccination against seasonal influenza of health-care workers in primary health-care settings in Greece, Vaccine 28 (37) (2010), pp. 5931–5933. Article |
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23 M. Madjid, A. Alfred, A. Sahai, J.L. Conyers and S.W. Casscells, Factors contributing to suboptimal vaccination against influenza: results of a nationwide telephone survey of persons with cardiovascular disease, Tex Heart Inst J 36 (6) (2009), pp. 546–552. View Record in Scopus | Cited By in Scopus (5)
24 K.W. To, S. Lee, T.O. Chan and S.S. Lee, Exploring determinants of acceptance of the pandemic influenza A (H1N1) 2009 vaccination in nurses, Am J Infect Control 38 (8) (2010), pp. 623–630. Article |
25 S.D. Torun and F. Torun, Vaccination against pandemic influenza A/H1N1 among healthcare workers and reasons for refusing vaccination in Istanbul in last pandemic alert phase, Vaccine 28 (35) (2010), pp. 5703–5710. Article |
26 S. Vírseda, M.A. Restrepo, E. Arranz, P. Magán-Tapia, M. Fernández-Ruiz, A.G. de la Cámara, J.M. Aguado and F. López-Medrano, Seasonal and pandemic A (H1N1) 2009 influenza vaccination coverage and attitudes among health-care workers in a Spanish university hospital, Vaccine 28 (30) (2010), pp. 4751–4757. Article |
Appendix
Questionnaire
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
_________________________________________
5) If you are not planning to get the H1N1 vaccine, what best describes your reason for not getting vaccinated? Please circle one.
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
8) If you are not planning to get the seasonal flu vaccine, what best describes your reason for not getting vaccinated? Please circle one.
_____________________________________
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Original research
Benjamin H. Chin-Yeea, Katherine Monkman MDa, Zafar Hussain MD, FRCP(C)a and Leonard A. Minuk MD, FRCP(C)
Background
Patients with hematologic malignancies are at increased risk of influenza and its complications. Despite current health recommendations and evidence favoring influenza vaccination, vaccination rates remain low in cancer patients.
Objective
The purpose of this study was to determine which factors influenced vaccination rates.
Methods
During the 2009–2010 pandemic H1N1 and seasonal influenza season, we surveyed patients with hematologic malignancies in a Canadian cancer center. Of the patients participating in our study (n = 129), 66% and 57% received the H1N1 pandemic influenza and seasonal influenza vaccines, respectively.
Results
A number of reasons for vaccination refusal were reported, most relating to general skepticism about the safety and efficacy of vaccination. Physician advice was also a factor influencing vaccination rates in patients. The vaccination rate for seasonal influenza was 39% in patients <65 years old, significantly lower than the rate of 73% reported for patients aged ≥65 years (P < 0.0001).
Conclusion
Future education programs should target younger patient populations and health-care workers, focusing on vaccine safety and efficacy in the high-risk cancer population.
Despite the annual development of effective influenza vaccines, influenza remains a significant cause of morbidity and mortality in Canada. In the 2009–2010 influenza season, approximately 40,000 Canadians were infected with seasonal influenza or the pandemic H1N1 influenza virus,1 and influenza has been estimated to cause 4,000–8,000 deaths in Canada each year.2 It is estimated that a severe influenza pandemic could result in a 1% reduction in annual gross domestic product in Canada.3
Patients with hematologic malignancies are known to be at increased risk of influenza and its complications, with estimated mortality rates in the range 5%–27%.[4], [5], [6], [7] and [8] Evidence for the efficacy of the influenza vaccine is limited and contradictory, and many assume that immunocompromised patients will not be able to generate a protective antibody response. Nonetheless, current evidence favors vaccination.9 Pollyea et al10 reported that eight of 15 trials on the efficacy of vaccination in patients with hematologic malignancies concluded that vaccination was beneficial. Both the Centers for Disease Control and Prevention (CDC) and the Public Health Agency of Canada (PHAC) advised that all immunocompromised patients, including those with cancer, receive both the seasonal influenza vaccine and the pandemic H1N1 influenza vaccine in the 2009–2010 influenza season.[11] and [12]
Despite these recommendations, rates of influenza vaccination remain low for the general population and cancer patients in Canada, with rates reported at 40% and 65% respectively.[13] and [14] A recent study by Yee et al15 reported similarly low influenza vaccination rates of 58% in cancer patients in the United States. Vaccination has long been a controversial public health issue, and many people choose not to be vaccinated due to fears that vaccines may not be safe and effective.[16], [17] and [18] Lack of physician recommendation has also been cited as a significant factor in the decision to decline vaccination.16
In this study, we sought to determine what percentage of patients being treated for hematologic malignancies in an Ontario, Canada, cancer center received the H1N1 pandemic influenza vaccine in the 2009–2010 influenza season and to explore the barriers to vaccination in this high-risk population. We also collected information on the percentage of patients who received the seasonal influenza vaccine. It was general practice for physicians at this center to recommend influenza vaccination in accordance with the PHAC recommendations.
Methods
Patients being treated for hematologic malignancies at the London Regional Cancer Program (London, Canada) were invited to complete a survey regarding influenza vaccination (Appendix). The London Regional Cancer Program is a tertiary care center providing specialized cancer care to a population base of 1.2 million in southwestern Ontario. The survey was administered to patients eligible to participate in another study assessing antibody levels pre- and postvaccination with the H1N1 pandemic vaccine. Eligible patients were 18 years or older and being treated or followed for hematological malignancies at the London Regional Cancer Program who attended an appointment between October 28 and November 19, 2009, and returned for a follow-up visit between January 5 and March 26, 2010 (n = 151). Patients were asked if they had received the pandemic H1N1 influenza vaccine and the seasonal influenza vaccine during the 2009–2010 influenza season. Those who had declined vaccination were asked to describe the reasons for their choice. The survey provided a list of six possible reasons for declining vaccination and gave patients the option of writing in their own responses.
The results of the study were analyzed using InStat 3 software (GraphPad, La Jolla, CA). The Mann-Whitney U-test was used to compare continuous variables, and Fisher's exact test was used to compare proportions. The study was approved by the University of Western Ontario's Institutional Research Ethics Board (IRB 16627E).
Results
Of the 151 patients invited to participate, 129 completed the survey, yielding a response rate of 85%. Patient characteristics are shown in Table 1. The respondents ranged in age from 19 to 86 years, 56% were male and 44% were female, and patients aged 65 years or older comprised 52% of the study population. The mean age of the patient group was 62.7 ± 14.8 years. Overall 119 patients (92%) had received chemotherapy at some time during their illness, with 96 patients (76%) actively receiving chemotherapy, defined as treatment within the past 3 months. Diagnoses included acute leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, lymphoma, multiple myeloma, myelodysplastic syndromes, and myeloproliferative neoplasms.
Of the 129 patients surveyed, 85 (66%) reported that they had received the H1N1 pandemic influenza vaccine during the 2009–2010 influenza season. Fifty-seven percent had received the seasonal influenza vaccine, and 50% had received both the seasonal and the H1N1 vaccines. Of the 44 patients who did not receive the H1N1 vaccine, only three planned to receive it. Eight of the 56 patients not vaccinated with the seasonal influenza vaccine planned to receive it.
There were no significant differences in mean age, percentage of patients over 65 years old, gender, or chemotherapy status between patients who received the H1N1 vaccine and those who declined it (Table 1). The mean age of patients who received the seasonal influenza vaccine was significantly higher than that of those who did not (67.8 ±12.1 vs. 56.1 ± 15.5 years, P < 0.0001), and a significantly higher percentage of patients in the vaccinated group were over the age of 65 (67% vs. 33%, P < 0.0001).
Patient-reported reasons for not receiving the H1N1 vaccine are shown in Figure 1. The two most common reasons for declining vaccination were beliefs that “the vaccine is dangerous because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). The belief that vaccination was dangerous or not effective because of the patient's medical condition represented 16% and 12% of responses, respectively. Six percent responded that receiving the vaccine would have been too inconvenient. No patients reported concerns about pain at the injection site as a reason for avoiding vaccination. In the category of “other,” responses fell into four broad categories: “physician advised against vaccination” (8%), “vaccination is unnecessary” (8%), “previous bad experience from vaccine” (4%), and “vaccine will make me sick” (4%).
Discussion
Our study found that 66% of patients being treated for hematological malignancies at a southwestern Ontario cancer center received the H1N1 vaccine during the 2009–2010 influenza season. This was higher than the rate of H1N1 vaccination in the general Canadian population, which was reported as 41%.14 Canadian cancer patients have been previously shown to have higher rates of participation in vaccination programs. In 2005, 64% of Canadians with cancer received the seasonal influenza vaccine compared with 34% of the overall population.13 This trend may be driven in part by the higher average age of patients receiving cancer treatment as adults 65 years of age or older comprised 52% of the respondents in our study.
Worldwide, Canada ranks among the highest countries in vaccination coverage. The United Kingdom reported a vaccination rate of 28.7% during the 2007–2008 influenza season, which was at the time one of the highest in Europe.19 Other European countries, including Germany, Italy, and France, showed vaccination rates similar to that of the United Kingdom. In all of these countries vaccination coverage increased with age. The United States has vaccination rates most similar to those of Canada, estimated at 40% in the overall population and 68% in the population ≥65 years old during the 2009–2010 influenza season.20
Higher vaccination rates have been reported in the elderly compared to younger adult population,[13] and [14] and our findings prove to be consistent with this reported trend. In this study, the group vaccinated with the seasonal influenza vaccine had a mean age of 67.8 ± 12.1 years compared with the unvaccinated group aged 56.1 ± 15.5 years (P < 0.0001). Interestingly, there was no significant difference in mean age between the vaccinated and unvaccinated groups for the H1N1 pandemic influenza vaccine (P > 0.05). This was not entirely unexpected since public health campaigns during the 2009–2010 influenza season focused on the younger age group due to their increased susceptibility to severe H1N1 disease. Nonetheless, there was a trend toward an increased mean age for those who received the vaccine (64.0 ± 12.5 years) compared to those who did not (60.4 ± 18.4 years), and it is possible that statistical significance was not reached due to the small sample size. Our study reported an alarmingly low 39% vaccination rate for seasonal influenza in cancer patients <65, suggesting that the PHAC's message is not adequately reaching this potentially at-risk group.
Reasons for refusal of vaccination have been well described in previous studies.[16], [17], [18], [21], [22], [23], [24], [25] and [26] We found that the most common reasons for refusal of vaccination by cancer patients were very similar to those reported in healthy individuals. Specifically, concerns about the safety and efficacy of vaccines in general were more common than concerns related to cancer or chemotherapy. The most common reasons for refusal of vaccination were “I think the vaccine will be dangerous for people in general because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). Despite the publicity, 8% of unvaccinated patients responded that they did not feel that H1N1 influenza was a significant threat. In this study, the belief that the vaccine was dangerous because of lack of testing or a previous medical condition was responsible for 13% of patients not receiving the vaccine. Five percent of patients elected not to be vaccinated because of questions of efficacy. The H1N1 vaccine is an adjuvant with AsO3, which may cause more vaccine reactions, while the seasonal influenza vaccine is not an adjuvant. It is possible that the presence of adjuvant contributed to some patients' safety concerns, though we did not specifically ask if the adjuvant influenced their decision.
Physician advice may have played a significant role in patients' decisions to vaccinate. Eight percent of patients who did not receive the vaccine reported that they were not vaccinated due to advice from a physician. It is our routine institutional policy to recommend vaccination for all cancer patients irrespective of underlying diagnosis or treatment regimen. We do not, however, provide standardized written information to patients or referring physicians, so some patients may have been advised against vaccination by other physicians. Some primary care physicians might not have been familiar with the current PHAC recommendations or the recent literature suggesting the vaccine's potential benefits in this group. Public health campaigns should therefore seek to educate physicians as well as patients regarding the safety and efficacy of the influenza vaccine for cancer patients.
Conclusion
We found that rates of H1N1 and seasonal influenza vaccination in a southwestern Ontario cancer center were higher than those reported for the general population. Nevertheless, despite a large public health education campaign, a significant number of patients declined vaccination due to fear that it would not be safe or effective or due to a belief that vaccination was not necessary. Although the rate of seasonal influenza vaccination was high for those ≥65 years old, it was poor for those aged <65 years, despite vaccination being recommended for all adults with chronic medical conditions. Future education programs should target younger patient populations and health-care workers and focus on vaccine safety and efficacy in immunocompromised patients as well as in other high-risk groups.
References1
1 Public Health Agency of Canada, FluWatch http://www.phac-aspc.gc.ca/fluwatch/09-10/w28_10/index-eng.php Accessed August 5, 2010.
2 Public Health Agency of Canada, Influenza http://www.phac-aspc.gc.ca/influenza/index-eng.php Accessed August 5, 2010.
3 S. James and T. Sargent, The Economic Impact of an Influenza Pandemic, Department of Finance Canada, Ottawa (2006), p. 90.
4 R.F. Chemaly, S. Ghosh, G.P. Bodey, N. Rohatgi, A. Safdar, M.J. Keating, R.E. Champlin, E.A. Aguilera, J.J. Tarrand and I.I. Raad, Respiratory viral infections in adults with hematologic malignancies and human stem cell transplantation recipients: a retrospective study at a major cancer center, Medicine 85 (5) (2006), pp. 278–287. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (66)
5 H.M. Yousuf, J. Englund, R. Couch, K. Rolston, M. Luna, J. Goodrich, V. Lewis, N.Q. Mirza, M. Andreeff, C. Koller, L. Elting, G.P. Bodey and E. Whimbey, Influenza among hospitalized adults with leukemia, Clin Infect Dis 24 (6) (1997), pp. 1095–1099. View Record in Scopus | Cited By in Scopus (55)
6 C.D. Cooksley, E.B. Avritscher, B.N. Bekele, K.V. Rolston, J.M. Geraci and L.S. Elting, Epidemiology and outcomes of serious influenza-related infections in the cancer population, Cancer 104 (3) (2005), pp. 618–628. View Record in Scopus | Cited By in Scopus (24)
7 L.S. Elting, E. Whimbey, W. Lo, R. Couch, M. Andreeff and G.P. Bodey, Epidemiology of influenza A virus infection in patients with acute or chronic leukemia, Support Care Cancer 3 (3) (1995), pp. 198–202. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (32)
8 E. Whimbey, L.S. Elting, R.B. Couch, W. Lo, L. Williams, R.E. Champlin and G.P. Bodey, Influenza A virus infections among hospitalized adult bone marrow transplant recipients, Bone Marrow Transplant 13 (4) (1994), pp. 437–440. View Record in Scopus | Cited By in Scopus (110)
9 M. Tiseo, B. Calatafimi, L. Ferri, A. Menardi and A. Ardizzoni, Efficacy and safety of influenza vaccination during chemotherapy treatment, J Support Oncol 8 (6) (2010), pp. 271–272. Article |
10 D.A. Pollyea, J.M. Brown and S.J. Horning, Utility of influenza vaccination for oncology patients, J Clin Oncol 28 (14) (2010), pp. 2481–2490. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (8)
11 Public Health Agency of Canada, Guidance Document on the Use of Pandemic Influenza A (H1N1) 2009: Inactivated Monovalent Vaccine, Public Health Agency of Canada, Ottawa (2009).
12 Centers for Disease Control, 2009 H1N1 Vaccination Recommendations http://www.cdc.gov/h1n1flu/vaccination/acip.htm Accessed August 5, 2010.
13 J.C. Kwong, L.C. Rosella and H. Johansen, Trends in influenza vaccination in Canada, 1996/1997 to 2005, Health Rep 18 (4) (2007), pp. 9–19. View Record in Scopus | Cited By in Scopus (14)
14 Statistics Canda, Canadian Community Health Survey: H1N1 Vaccinations http://www.statcan.gc.ca/daily-quotidien/100719/dq100719b-eng.htm Accessed August 5, 2010.
15 S.S. Yee, P.R. Dutta, L.J. Solin, N. Vapiwala and G.D. Kao, Lack of compliance with national vaccination guidelines in oncology patients receiving radiation therapy, J Support Oncol 8 (1) (2010), pp. 28–34. View Record in Scopus | Cited By in Scopus (2)
16 P. Loulergue, O. Mir, J. Alexandre, S. Ropert, F. Goldwasser and O. Launay, Low influenza vaccination rate among patients receiving chemotherapy for cancer, Ann Oncol 19 (9) (2008), p. 1658. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (10)
17 R.K. Zimmerman, T.A. Santibanez, J.E. Janosky, M.J. Fine, M. Raymund, S.A. Wilson, I.J. Bardella, A.R. Medsger and M.P. Nowalk, What affects influenza vaccination rates among older patients?: An analysis from inner-city, suburban, rural, and Veterans Affairs practices, Am J Med 114 (1) (2003), pp. 31–38. Article |
18 M.W. Mah, N.A. Hagen, K. Pauling-Shepard, J.S. Hawthorne, M. Mysak, T. Lye and T.J. Louie, Understanding influenza vaccination attitudes at a Canadian cancer center, Am J Infect Control 33 (4) (2005), pp. 243–250. Article |
19 P.R. Blank, M. Schwenkglenks and T.D. Szucs, Vaccination coverage rates in eleven European countries during two consecutive influenza seasons, J Infect 58 (6) (2009), pp. 446–458. Article |
20 Centers for Disease Control and Prevention, Interim Results: State-Specific Seasonal Influenza Vaccination Coverage—United States, August 2009–January 2010, MMWR Morb Mortal Wkly Rep 59 (16) (2010), pp. 477–484.
21 X. Dedoukou, G. Nikolopoulos, A. Maragos, S. Giannoulidou and H.C. Maltezou, Attitudes towards vaccination against seasonal influenza of health-care workers in primary health-care settings in Greece, Vaccine 28 (37) (2010), pp. 5931–5933. Article |
22 J.N. Kent, C.S. Lea, X. Fang, L.F. Novick and J. Morgan, Seasonal influenza vaccination coverage among local health department personnel in North Carolina, 2007–2008, Am J Prev Med 39 (1) (2010), pp. 74–77. Article |
23 M. Madjid, A. Alfred, A. Sahai, J.L. Conyers and S.W. Casscells, Factors contributing to suboptimal vaccination against influenza: results of a nationwide telephone survey of persons with cardiovascular disease, Tex Heart Inst J 36 (6) (2009), pp. 546–552. View Record in Scopus | Cited By in Scopus (5)
24 K.W. To, S. Lee, T.O. Chan and S.S. Lee, Exploring determinants of acceptance of the pandemic influenza A (H1N1) 2009 vaccination in nurses, Am J Infect Control 38 (8) (2010), pp. 623–630. Article |
25 S.D. Torun and F. Torun, Vaccination against pandemic influenza A/H1N1 among healthcare workers and reasons for refusing vaccination in Istanbul in last pandemic alert phase, Vaccine 28 (35) (2010), pp. 5703–5710. Article |
26 S. Vírseda, M.A. Restrepo, E. Arranz, P. Magán-Tapia, M. Fernández-Ruiz, A.G. de la Cámara, J.M. Aguado and F. López-Medrano, Seasonal and pandemic A (H1N1) 2009 influenza vaccination coverage and attitudes among health-care workers in a Spanish university hospital, Vaccine 28 (30) (2010), pp. 4751–4757. Article |
Appendix
Questionnaire
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
_________________________________________
5) If you are not planning to get the H1N1 vaccine, what best describes your reason for not getting vaccinated? Please circle one.
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
8) If you are not planning to get the seasonal flu vaccine, what best describes your reason for not getting vaccinated? Please circle one.
_____________________________________
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Original research
Benjamin H. Chin-Yeea, Katherine Monkman MDa, Zafar Hussain MD, FRCP(C)a and Leonard A. Minuk MD, FRCP(C)
Background
Patients with hematologic malignancies are at increased risk of influenza and its complications. Despite current health recommendations and evidence favoring influenza vaccination, vaccination rates remain low in cancer patients.
Objective
The purpose of this study was to determine which factors influenced vaccination rates.
Methods
During the 2009–2010 pandemic H1N1 and seasonal influenza season, we surveyed patients with hematologic malignancies in a Canadian cancer center. Of the patients participating in our study (n = 129), 66% and 57% received the H1N1 pandemic influenza and seasonal influenza vaccines, respectively.
Results
A number of reasons for vaccination refusal were reported, most relating to general skepticism about the safety and efficacy of vaccination. Physician advice was also a factor influencing vaccination rates in patients. The vaccination rate for seasonal influenza was 39% in patients <65 years old, significantly lower than the rate of 73% reported for patients aged ≥65 years (P < 0.0001).
Conclusion
Future education programs should target younger patient populations and health-care workers, focusing on vaccine safety and efficacy in the high-risk cancer population.
Despite the annual development of effective influenza vaccines, influenza remains a significant cause of morbidity and mortality in Canada. In the 2009–2010 influenza season, approximately 40,000 Canadians were infected with seasonal influenza or the pandemic H1N1 influenza virus,1 and influenza has been estimated to cause 4,000–8,000 deaths in Canada each year.2 It is estimated that a severe influenza pandemic could result in a 1% reduction in annual gross domestic product in Canada.3
Patients with hematologic malignancies are known to be at increased risk of influenza and its complications, with estimated mortality rates in the range 5%–27%.[4], [5], [6], [7] and [8] Evidence for the efficacy of the influenza vaccine is limited and contradictory, and many assume that immunocompromised patients will not be able to generate a protective antibody response. Nonetheless, current evidence favors vaccination.9 Pollyea et al10 reported that eight of 15 trials on the efficacy of vaccination in patients with hematologic malignancies concluded that vaccination was beneficial. Both the Centers for Disease Control and Prevention (CDC) and the Public Health Agency of Canada (PHAC) advised that all immunocompromised patients, including those with cancer, receive both the seasonal influenza vaccine and the pandemic H1N1 influenza vaccine in the 2009–2010 influenza season.[11] and [12]
Despite these recommendations, rates of influenza vaccination remain low for the general population and cancer patients in Canada, with rates reported at 40% and 65% respectively.[13] and [14] A recent study by Yee et al15 reported similarly low influenza vaccination rates of 58% in cancer patients in the United States. Vaccination has long been a controversial public health issue, and many people choose not to be vaccinated due to fears that vaccines may not be safe and effective.[16], [17] and [18] Lack of physician recommendation has also been cited as a significant factor in the decision to decline vaccination.16
In this study, we sought to determine what percentage of patients being treated for hematologic malignancies in an Ontario, Canada, cancer center received the H1N1 pandemic influenza vaccine in the 2009–2010 influenza season and to explore the barriers to vaccination in this high-risk population. We also collected information on the percentage of patients who received the seasonal influenza vaccine. It was general practice for physicians at this center to recommend influenza vaccination in accordance with the PHAC recommendations.
Methods
Patients being treated for hematologic malignancies at the London Regional Cancer Program (London, Canada) were invited to complete a survey regarding influenza vaccination (Appendix). The London Regional Cancer Program is a tertiary care center providing specialized cancer care to a population base of 1.2 million in southwestern Ontario. The survey was administered to patients eligible to participate in another study assessing antibody levels pre- and postvaccination with the H1N1 pandemic vaccine. Eligible patients were 18 years or older and being treated or followed for hematological malignancies at the London Regional Cancer Program who attended an appointment between October 28 and November 19, 2009, and returned for a follow-up visit between January 5 and March 26, 2010 (n = 151). Patients were asked if they had received the pandemic H1N1 influenza vaccine and the seasonal influenza vaccine during the 2009–2010 influenza season. Those who had declined vaccination were asked to describe the reasons for their choice. The survey provided a list of six possible reasons for declining vaccination and gave patients the option of writing in their own responses.
The results of the study were analyzed using InStat 3 software (GraphPad, La Jolla, CA). The Mann-Whitney U-test was used to compare continuous variables, and Fisher's exact test was used to compare proportions. The study was approved by the University of Western Ontario's Institutional Research Ethics Board (IRB 16627E).
Results
Of the 151 patients invited to participate, 129 completed the survey, yielding a response rate of 85%. Patient characteristics are shown in Table 1. The respondents ranged in age from 19 to 86 years, 56% were male and 44% were female, and patients aged 65 years or older comprised 52% of the study population. The mean age of the patient group was 62.7 ± 14.8 years. Overall 119 patients (92%) had received chemotherapy at some time during their illness, with 96 patients (76%) actively receiving chemotherapy, defined as treatment within the past 3 months. Diagnoses included acute leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, lymphoma, multiple myeloma, myelodysplastic syndromes, and myeloproliferative neoplasms.
Of the 129 patients surveyed, 85 (66%) reported that they had received the H1N1 pandemic influenza vaccine during the 2009–2010 influenza season. Fifty-seven percent had received the seasonal influenza vaccine, and 50% had received both the seasonal and the H1N1 vaccines. Of the 44 patients who did not receive the H1N1 vaccine, only three planned to receive it. Eight of the 56 patients not vaccinated with the seasonal influenza vaccine planned to receive it.
There were no significant differences in mean age, percentage of patients over 65 years old, gender, or chemotherapy status between patients who received the H1N1 vaccine and those who declined it (Table 1). The mean age of patients who received the seasonal influenza vaccine was significantly higher than that of those who did not (67.8 ±12.1 vs. 56.1 ± 15.5 years, P < 0.0001), and a significantly higher percentage of patients in the vaccinated group were over the age of 65 (67% vs. 33%, P < 0.0001).
Patient-reported reasons for not receiving the H1N1 vaccine are shown in Figure 1. The two most common reasons for declining vaccination were beliefs that “the vaccine is dangerous because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). The belief that vaccination was dangerous or not effective because of the patient's medical condition represented 16% and 12% of responses, respectively. Six percent responded that receiving the vaccine would have been too inconvenient. No patients reported concerns about pain at the injection site as a reason for avoiding vaccination. In the category of “other,” responses fell into four broad categories: “physician advised against vaccination” (8%), “vaccination is unnecessary” (8%), “previous bad experience from vaccine” (4%), and “vaccine will make me sick” (4%).
Discussion
Our study found that 66% of patients being treated for hematological malignancies at a southwestern Ontario cancer center received the H1N1 vaccine during the 2009–2010 influenza season. This was higher than the rate of H1N1 vaccination in the general Canadian population, which was reported as 41%.14 Canadian cancer patients have been previously shown to have higher rates of participation in vaccination programs. In 2005, 64% of Canadians with cancer received the seasonal influenza vaccine compared with 34% of the overall population.13 This trend may be driven in part by the higher average age of patients receiving cancer treatment as adults 65 years of age or older comprised 52% of the respondents in our study.
Worldwide, Canada ranks among the highest countries in vaccination coverage. The United Kingdom reported a vaccination rate of 28.7% during the 2007–2008 influenza season, which was at the time one of the highest in Europe.19 Other European countries, including Germany, Italy, and France, showed vaccination rates similar to that of the United Kingdom. In all of these countries vaccination coverage increased with age. The United States has vaccination rates most similar to those of Canada, estimated at 40% in the overall population and 68% in the population ≥65 years old during the 2009–2010 influenza season.20
Higher vaccination rates have been reported in the elderly compared to younger adult population,[13] and [14] and our findings prove to be consistent with this reported trend. In this study, the group vaccinated with the seasonal influenza vaccine had a mean age of 67.8 ± 12.1 years compared with the unvaccinated group aged 56.1 ± 15.5 years (P < 0.0001). Interestingly, there was no significant difference in mean age between the vaccinated and unvaccinated groups for the H1N1 pandemic influenza vaccine (P > 0.05). This was not entirely unexpected since public health campaigns during the 2009–2010 influenza season focused on the younger age group due to their increased susceptibility to severe H1N1 disease. Nonetheless, there was a trend toward an increased mean age for those who received the vaccine (64.0 ± 12.5 years) compared to those who did not (60.4 ± 18.4 years), and it is possible that statistical significance was not reached due to the small sample size. Our study reported an alarmingly low 39% vaccination rate for seasonal influenza in cancer patients <65, suggesting that the PHAC's message is not adequately reaching this potentially at-risk group.
Reasons for refusal of vaccination have been well described in previous studies.[16], [17], [18], [21], [22], [23], [24], [25] and [26] We found that the most common reasons for refusal of vaccination by cancer patients were very similar to those reported in healthy individuals. Specifically, concerns about the safety and efficacy of vaccines in general were more common than concerns related to cancer or chemotherapy. The most common reasons for refusal of vaccination were “I think the vaccine will be dangerous for people in general because of lack of testing” (22%) and “I don't believe in vaccination in general” (18%). Despite the publicity, 8% of unvaccinated patients responded that they did not feel that H1N1 influenza was a significant threat. In this study, the belief that the vaccine was dangerous because of lack of testing or a previous medical condition was responsible for 13% of patients not receiving the vaccine. Five percent of patients elected not to be vaccinated because of questions of efficacy. The H1N1 vaccine is an adjuvant with AsO3, which may cause more vaccine reactions, while the seasonal influenza vaccine is not an adjuvant. It is possible that the presence of adjuvant contributed to some patients' safety concerns, though we did not specifically ask if the adjuvant influenced their decision.
Physician advice may have played a significant role in patients' decisions to vaccinate. Eight percent of patients who did not receive the vaccine reported that they were not vaccinated due to advice from a physician. It is our routine institutional policy to recommend vaccination for all cancer patients irrespective of underlying diagnosis or treatment regimen. We do not, however, provide standardized written information to patients or referring physicians, so some patients may have been advised against vaccination by other physicians. Some primary care physicians might not have been familiar with the current PHAC recommendations or the recent literature suggesting the vaccine's potential benefits in this group. Public health campaigns should therefore seek to educate physicians as well as patients regarding the safety and efficacy of the influenza vaccine for cancer patients.
Conclusion
We found that rates of H1N1 and seasonal influenza vaccination in a southwestern Ontario cancer center were higher than those reported for the general population. Nevertheless, despite a large public health education campaign, a significant number of patients declined vaccination due to fear that it would not be safe or effective or due to a belief that vaccination was not necessary. Although the rate of seasonal influenza vaccination was high for those ≥65 years old, it was poor for those aged <65 years, despite vaccination being recommended for all adults with chronic medical conditions. Future education programs should target younger patient populations and health-care workers and focus on vaccine safety and efficacy in immunocompromised patients as well as in other high-risk groups.
References1
1 Public Health Agency of Canada, FluWatch http://www.phac-aspc.gc.ca/fluwatch/09-10/w28_10/index-eng.php Accessed August 5, 2010.
2 Public Health Agency of Canada, Influenza http://www.phac-aspc.gc.ca/influenza/index-eng.php Accessed August 5, 2010.
3 S. James and T. Sargent, The Economic Impact of an Influenza Pandemic, Department of Finance Canada, Ottawa (2006), p. 90.
4 R.F. Chemaly, S. Ghosh, G.P. Bodey, N. Rohatgi, A. Safdar, M.J. Keating, R.E. Champlin, E.A. Aguilera, J.J. Tarrand and I.I. Raad, Respiratory viral infections in adults with hematologic malignancies and human stem cell transplantation recipients: a retrospective study at a major cancer center, Medicine 85 (5) (2006), pp. 278–287. Full Text via CrossRef | View Record in Scopus | Cited By in Scopus (66)
5 H.M. Yousuf, J. Englund, R. Couch, K. Rolston, M. Luna, J. Goodrich, V. Lewis, N.Q. Mirza, M. Andreeff, C. Koller, L. Elting, G.P. Bodey and E. Whimbey, Influenza among hospitalized adults with leukemia, Clin Infect Dis 24 (6) (1997), pp. 1095–1099. View Record in Scopus | Cited By in Scopus (55)
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Appendix
Questionnaire
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
_________________________________________
5) If you are not planning to get the H1N1 vaccine, what best describes your reason for not getting vaccinated? Please circle one.
- a) I do not think it will be effective for me because of my medical condition
b) I am concerned it might be dangerous for me because of my medical condition
c) I am concerned it might be dangerous for people in general because not enough testing has been done
d) Receiving the vaccination would be too inconvenient (long lineups, etc.)
8) If you are not planning to get the seasonal flu vaccine, what best describes your reason for not getting vaccinated? Please circle one.
_____________________________________
Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Spirituality, patients' worry, and follow-up health-care utilization among cancer survivors
Background Spirituality may aid cancer survivors as they attempt to interpret the meaning of their experience.
Objective We examined the relationship between spirituality, patient-rated worry, and health-care utilization among 551 cancer survivors with different malignancies, who were evaluated prospectively.
Methods Baseline spirituality scores were categorized into low and high spirituality groups. Patient-rated worries regarding disease recurrence/progression, developing new cancer, and developing complications from treatment were collected at baseline and at 6 and 12 months. Follow-up health-care utilization was also examined at 6 and 12 months.
Results Among the survivors, 271 (49%) reported low spirituality and 280 (51%) reported high spirituality. Of the cohort, 59% had some kind of worry regarding disease recurrence/progression, development of new cancers, and treatment complications. Highly spiritual survivors were less likely to have high levels of worries at both 6 and 12 months. Highly worried survivors were significantly more likely to place phone calls to their follow-up providers and had more frequent follow-up visits at 6 and 12 months. No interactions between spirituality and level of worry were noted to affect follow-up health-care utilization.
Conclusion Given spirituality's effect on anxiety, spirituality-based intervention may have a role in addressing cancer survivors' worries but may not improve health-care utilization.
Article Outline
- Results
- Study Participation
- Characteristics of Study Participants
- Prevalence of Spirituality and Patient Worry
- Relationship Between Spirituality and Patient Worry
- Relationship Between Patient Worry and Follow-Up Health-Care Utilization
- Relationship Between Spirituality and Health-Care Utilization
- Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Receiving a diagnosis of cancer is a life-changing event. Patients commonly seek understanding of not only the medical aspects of their disease but also how the diagnosis will affect their lives. Often, this quest to understand the meaning behind the unfortunate circumstance of disease is aided by spirituality. Spirituality motivates an individual to find meaning or purpose in his or her life experience.1 Most studies indicate that spirituality gives meaningful insight to an individual's existence and aids in the interpretation of events and relationships.[2], [3], [4], [5], [6], [7], [8] and [9]
Spiritual beliefs are widespread among cancer patients. Studies have shown that a better quality of life (QOL) is achieved in patients who practice spirituality or have those needs met by their health-care providers. They require less health care as well as experience less anxiety and a greater sense of well-being.[10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20] and [21] One may conclude that spirituality helps patients understand the meaning of their disease and provides the catalyst for significant improvement in health-related outcomes.
Vast amounts of literature affirm spirituality's positive effects on health outcomes for advanced-stage/terminally ill patients. However, very little is known about how spirituality affects the common concerns of cancer survivors. It can be inferred that spirituality continues to aid cancer survivors as they attempt to interpret the meaning of their experience during follow-up care. After completing various cancer treatments, survivors may experience worries of cancer recurrence or progression, worries of developing a different cancer, and worries of developing complications from their initial treatment.22 We explored the relationship between spirituality, patient-rated cancer-related worry, and cancer survivors' follow-up health-care utilization (follow-up doctor visits, phone calls to follow-up providers regarding medical inquiries, and emergency room visits).
Participants and Methods
Subject Selection and Eligibility
Data for this study were obtained from CANCER CARE, an observational cohort study using a self-administered questionnaire designed to evaluate follow-up care among cancer survivors.23 Participants were seen at the University of Nebraska Medical Center (UNMC) and consented to participate in a data-collection protocol (ONCOBASE) since March 2006. ONCOBASE has a 90% consent rate. To be eligible for the study, participants were at least 19 years of age (age of majority in Nebraska) and completed their cancer treatment at UNMC. Participants varied in time since completion of last cancer treatment. From a list of 5,500 eligible subjects, 2,500 were screened. The list was sorted by date of consent, and the first 2,000 subjects received the study questionnaire. Survey forms were mailed in August 2008 (baseline) and follow-up surveys were mailed in February (month 6) and August 2009 (month 12). Participants were not paid for study participation but were told that a donation to a charitable institution was made on their behalf as an altruistic incentive.23 The study was approved by the Institutional Review Board at UNMC.
Variables Analyzed
We analyzed the participants' spirituality from baseline surveys using the Functional Assessment of Cancer Therapy–Spirituality Scale (FACT-SP).24 Total spirituality scores were computed for each participant using instrument standard calculations. The cohort was categorized into two groups, consisting of low or high spirituality based on the median calculated score (<47 vs. ≥47) for the entire population. Other variables included in the analyses are shown in Table 1. Patient-rated worry pertaining to (1) disease recurrence/progression, (2) development of a new malignancy, and (3) complications related to treatment were evaluated at baseline and at 6 and 12 months. Respondents were asked to rate their level of worry for each of the above three items using a five-point Likert scale (none at all, little of the time, some of the time, most of the time, and all of the time). Each worry item was categorized as low (none at all to a little of the time) vs. high (some of the time, most of the time, all of the time). Follow-up health-care utilization was assessed at 6 and 12 months and consisted of (1) follow-up clinic visits (low, defined as none or one follow-up visit per year, vs. high, more than one follow-up visit per year), (2) phone calls to follow-up providers for medical issues (no vs. yes), and (3) emergency room visits (no vs. yes). These indices of health-care utilization were selected on the basis of whether they are discretionary (patient-driven) or nondiscretionary (physician-driven).[25] and [26] For example, follow-up clinic visits are mainly nondiscretionary in the sense that the follow-up provider primarily determines the frequency at which they are conducted, while phone calls made to follow-up providers and emergency room visits are inherently discretionary. We also evaluated the relationships between spirituality and QOL (Short Form 12 [SF-12]),27 social support,28 and religiosity (with the survey question [data not shown] “Overall, how much would you say that religious beliefs have influenced your life in the past two months?”), to establish the external validity of our spirituality cut-off score since these constructs have been associated with spirituality.[10], [15], [17], [19], [29], [30] and [31] Our analyses showed a high correlation between our categorization of low or high spirituality with QOL, social support, and religiosity.
| EVALUABLE (N) | LOW SPIRITUALITY | HIGH SPIRITUALITY | P | |||
|---|---|---|---|---|---|---|
| FREQUENCY | PERCENT | FREQUENCY | PERCENT | |||
| n | 551 | 271 | 49 | 280 | 51 | |
| Median age (range) | 59 (19–85) | 59 (22–83) | 0.99 | |||
| ≤40 | 551 | 17 | 6 | 21 | 8 | 0.78 |
| 41–60 | 137 | 51 | 135 | 48 | ||
| >60 | 117 | 43 | 124 | 44 | ||
| Sex | ||||||
| Female | 551 | 112 | 41 | 89 | 32 | 0.02 |
| Male | 159 | 59 | 191 | 68 | ||
| Race/ethnicity | ||||||
| White | 551 | 256 | 94 | 272 | 97 | 0.21 |
| Hispanic | 6 | 2 | 2 | 1 | ||
| African American | 3 | 1 | 4 | 1 | ||
| Other | 6 | 2 | 2 | 1 | ||
| Marital status | ||||||
| Single/never married | 551 | 14 | 5 | 19 | 7 | 0.67 |
| Married | 219 | 81 | 219 | 78 | ||
| Divorced/widowed | 38 | 14 | 42 | 15 | ||
| Education | ||||||
| High school | 551 | 90 | 33 | 83 | 30 | 0.49 |
| College | 105 | 39 | 122 | 44 | ||
| Postgraduate | 76 | 28 | 75 | 27 | ||
| Religion | ||||||
| Protestant | 551 | 121 | 45 | 161 | 58 | <0.01 |
| Catholic | 101 | 37 | 80 | 29 | ||
| Other | 36 | 13 | 35 | 13 | ||
| None/atheist | 13 | 5 | 4 | 1 | ||
| Income (US$) | ||||||
| <25,000 | 551 | 37 | 14 | 37 | 13 | 0.71 |
| 25,000–49,999 | 64 | 24 | 61 | 22 | ||
| 50,000–74,999 | 59 | 22 | 54 | 19 | ||
| 75,000–100,000 | 35 | 13 | 44 | 16 | ||
| >100,000 | 57 | 21 | 56 | 20 | ||
| Missing | 19 | 7 | 28 | 10 | ||
| Place of residence | ||||||
| Urban | 551 | 194 | 72 | 201 | 72 | 0.96 |
| Rural | 77 | 28 | 79 | 28 | ||
| Distance (miles) | ||||||
| ≤15 | 551 | 108 | 40 | 98 | 35 | 0.32 |
| 15–100 | 83 | 31 | 94 | 34 | ||
| 100–250 | 44 | 16 | 58 | 21 | ||
| >250 | 36 | 13 | 30 | 11 | ||
| Employment status | ||||||
| Full time | 551 | 160 | 59 | 163 | 58 | 0.93 |
| Part time | 22 | 8 | 27 | 10 | ||
| Homemaker | 25 | 9 | 26 | 9 | ||
| Student | 3 | 1 | 4 | 1 | ||
| Retired | 48 | 18 | 51 | 18 | ||
| Other | 13 | 5 | 9 | 3 | ||
| Patient is the primary income provider | 551 | 137 | 51 | 132 | 47 | 0.42 |
| Insurance | ||||||
| Employer-based | 551 | 149 | 55 | 153 | 55 | 0.95 |
| Individual-based | 47 | 17 | 48 | 17 | ||
| Medicare/Medicaid | 56 | 21 | 59 | 21 | ||
| Other | 17 | 6 | 16 | 6 | ||
| None | 2 | 1 | 4 | 1 | ||
| Prescription insurance | 551 | 239 | 88 | 242 | 86 | 0.53 |
| Type of malignancy | ||||||
| Leukemia, lymphoma, multiple myeloma | 551 | 136 | 50 | 147 | 53 | 0.86 |
| Breast, colon, prostate | 101 | 37 | 100 | 36 | ||
| Lung, pancreatic | 34 | 13 | 33 | 12 | ||
| Median time from diagnosis to study enrollment in years (range) | 4.5 (0.5–26.6) | 4.2 (0.6–26.6) | 0.28 | |||
| 0–2 years | 551 | 56 | 21 | 62 | 22 | 0.09 |
| 2–4 years | 70 | 26 | 76 | 27 | ||
| 4–8 years | 74 | 27 | 93 | 33 | ||
| >8 years | 71 | 26 | 49 | 18 | ||
| Median time from last treatment to study enrollment in years (range) | 3.6 (0.1–13.6) | 3.6 (0.4–18.7) | 0.87 | |||
| 0–2 years | 551 | 97 | 36 | 99 | 35 | 0.84 |
| 2–5 years | 83 | 31 | 92 | 33 | ||
| >5 years | 91 | 34 | 89 | 32 | ||
| Affiliation of follow-up provider | ||||||
| University-based | 551 | 193 | 71 | 190 | 68 | 0.16 |
| Community-based | 28 | 10 | 31 | 11 | ||
| Both | 50 | 18 | 54 | 19 | ||
| Missing | 0 | 0 | 5 | 2 | ||
| Treatment received | ||||||
| Chemotherapy only | 551 | 82 | 30 | 89 | 32 | 0.93 |
| Chemo + surgery + radiation | 125 | 46 | 126 | 45 | ||
| Stem cell transplantation | 64 | 24 | 65 | 23 | ||
| Prior treatment outside university | 551 | 116 | 43 | 126 | 45 | 0.60 |
Statistical Analysis
Participant characteristics were compared according to level of spirituality using a chi-square test for categorical data and the Wilcoxon test for continuous data (Table 1). Multivariate logistic regression models were fitted to evaluate separately the relationship between (1) spirituality with patient-rated worry as the outcome, (2) spirituality with follow-up health-care utilization as the outcome, and (3) patient-rated worry with follow-up health-care utilization as the outcome. In the above models, the following covariates were forced into each model: age, sex, cancer type, time from last cancer-related treatment to study start time, income, and type of medical insurance. These models were also fitted using outcomes ascertained at both 6 and 12 months. Interaction models between patient-rated worry and level of spirituality were also evaluated for an association with follow-up health-care utilization at 12 months to explore the role of spirituality in the relationship between patient-rated worry and health-care utilization. A P value of at least 0.05 was considered statistically significant.
Results
Study Participation
Of the 2,000 participants invited, 1,881 were deemed eligible (minus those who died or had wrong addresses). Baseline questionnaires were returned by 939 participants (baseline response rate of 50%). Seventeen wanted to participate only in the baseline survey. Of the 922 baseline participants, 691 returned the 6-month survey at the time of the analysis for this study, for a response rate of 76% when adjusted for deaths (182 no response, 18 deaths, 25 declined, 12 returned with wrong address). At 1 year, 691 surveys were mailed, with 588 surveys returned (58 no response, 17 deaths, 14 declined, 13 returned with wrong address, and one in hospice); a response rate of 87% was achieved after adjusting for deaths. Thirty-seven participants had missing information on spirituality, leaving a total of 551 included in this study. No differences in age, sex, and type of cancer were noted between patients included and excluded in the current analysis.
Characteristics of Study Participants
Demographic characteristics of the 551 study participants included in this study are shown in Table 1. We found that cancer survivors with low or high spirituality were more similar than different in all but two characteristics: highly spiritual survivors were more likely to be Protestant and male.
Prevalence of Spirituality and Patient Worry
Within our population, 271 (49%) survivors reported low spirituality and 280 (51%) reported high spirituality (Table 1). Also, at baseline, 277 (51%) survivors reported high levels of recurrence/progression-related worry, 190 survivors (35%) reported high levels of new malignancy–related worry, and 178 survivors (33%) reported high levels of treatment-related complication worry. As some participants may have reported one or more types of worry, this translates to 322 (59%) reporting any type of worry. Highly spiritual survivors reported significantly lower levels of high worry concerning recurrence/progression (6-month 27% vs. 38%, P < 0.01; 12-month 21% vs. 38%, P < 0.01), development of a different type of cancer (6-month 22% vs. 31%, P = 0.03; 12-month 15% vs. 26%, P < 0.01), and complications from treatment (6-month 17% vs. 30%, P < 0.01; 12-month 16% vs. 26%, P < 0.01). Highly spiritual survivors reported significantly lower levels for any type of worry at both 6 and 12 months (6 months 37% vs. 54%, P <0.01; 12 months 28% vs. 47%, P < 0.01) (Table 2).
| BASELINE | 6-MONTH | 12-MONTH | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | ||
| Recurrence/progression-related worry | Low | 106 (40) | 160 (58) | <0.01 | 154 (62) | 184 (73) | <0.01 | 166 (62) | 218 (79) | <0.01 |
| High | 160 (60) | 117 (42) | 95 (38) | 69 (27) | 103 (38) | 59 (21) | ||||
| New primary–related worry | Low | 158 (59) | 200 (72) | <0.01 | 172 (69) | 202 (78) | 0.03 | 199 (74) | 235 (85) | <0.01 |
| High | 111 (41) | 79 (28) | 76 (31) | 58 (22) | 71 (26) | 42 (15) | ||||
| Complication-related worry | Low | 166 (61) | 203 (73) | <0.01 | 175 (70) | 214 (83) | <0.01 | 200 (74) | 232 (84) | <0.01 |
| High | 104 (39) | 74 (27) | 74 (30) | 45 (17) | 69 (26) | 44 (16) | ||||
| Any worry | Low | 85 (32) | 138 (50) | <0.01 | 120 (46) | 165 (63) | <0.01 | 142 (53) | 198 (72) | <0.01 |
| High | 182 (68) | 140 (50) | 139 (54) | 97 (37) | 128 (47) | 78 (28) | ||||
Relationship Between Spirituality and Patient Worry
At the 6- and 12-month time points, after adjusting for covariates, highly spiritual survivors were significantly less likely to have worries than survivors who reported lower spirituality regarding disease recurrence/progression at 6 months (odds ratio [OR] = 0.61, 95% confidence interval [CI] 0.42–0.89, P < 0.01) and at 12 months (OR = 0.43, 95% CI 0.29–0.63, P < 0.01), complications from treatment at 6 months (OR = 0.50, 95% CI 0.33–0.76, P < 0.01) and at 12 months (OR = 0.54, 95% CI 0.35–0.83, P < 0.01), and development of a different type of cancer at 6 months (OR = 0.65, 95% CI 0.44–0.97, P = 0.04) and at 12 months (OR = 0.50, 95% CI 0.33–0.77, P < 0.01) (Table 3A).
| A | N | 6-MONTH | 12-MONTH | |||||
|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | ||
| Outcome | ||||||||
| Recurrence/progression-related worry | 502 | 1.00 | 0.61 (0.42–0.89) | 0.01 | 546 | 1.00 | 0.43 (0.29–0.63) | <0.01 |
| New primary–related worry | 508 | 1.00 | 0.65 (0.44–0.97) | 0.04 | 547 | 1.00 | 0.50 (0.33–0.77) | <0.01 |
| Complication-related worry | 508 | 1.00 | 0.50 (0.33–0.76) | <0.01 | 545 | 1.00 | 0.54 (0.35–0.83) | <0.01 |
| B | N | LOW WORRY, OR (95% CI) | HIGH WORRY, OR (95% CI) | P | N | LOW WORRY, OR (95% CI) | HIGH WORRY,OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 485 | 1.00 | 1.81 (1.04–3.12) | 0.03 | 534 | 1.00 | 1.49 (1.00–2.22) | 0.05 |
| Phone call to follow-up clinic | 504 | 1.00 | 2.21 (1.48–3.31) | <0.01 | 543 | 1.00 | 1.74 (1.20–2.53) | 0.01 |
| Emergency room visit | 503 | 1.00 | 1.75 (0.90–3.43) | 0.10 | 549 | 1.00 | 0.88 (0.52–1.51) | 0.65 |
| C | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 487 | 1.00 | 0.63 (0.37–1.10) | 0.11 | 536 | 1.00 | 0.88 (0.60–1.30) | 0.52 |
| Phone call to follow-up clinic | 506 | 1.00 | 0.77 (0.53–1.12) | 0.17 | 545 | 1.00 | 0.70 (0.49–1.00) | 0.04 |
| Emergency room visit | 505 | 1.00 | 0.56 (0.30–1.05) | 0.07 | 551 | 1.00 | 0.84 (0.50–1.41) | 0.50 |
Models adjusted for age, sex, cancer type, income, type of insurance, and time from last treatment
Relationship Between Patient Worry and Follow-Up Health-Care Utilization
Survivors who were highly worried about disease recurrence/progression, development of another type of cancer, and/or complications from treatment were more likely to visit their providers for follow-up care when compared with survivors who were less worried at 6 months (OR = 1.81, 95% CI 1.04–3.12, P = 0.03) and at 12 months (OR = 1.49, 95% CI 1.00–2.22, P = 0.05). Similarly, survivors who were highly worried were also more likely to place phone calls to their follow-up providers for medical inquiries than survivors who were less worried at 6 months (OR = 2.21, 95% CI 1.48–3.31, P < 0.01) and at 12 months (OR = 1.74, 95% CI 1.20–2.53, P = 0.01). We did not observe differences in emergency room visits between survivors with low and those with high rates of worrying at both 6 and 12 months (Table 3B).
Relationship Between Spirituality and Health-Care Utilization
No significant differences were noted for the frequency of follow-up visits, changes in follow-up providers, and emergency room visits between the levels of spirituality at both 6 and 12 months. However, at 12 months, highly spiritual survivors were less likely to call their follow-up providers for medical inquiries compared to survivors with low spirituality scores (OR = 0.70, 95% CI 0.49–1.00, P = 0.04) (Table 3C).
Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Interaction between patient-rated worry and level of spirituality as it relates to health-care utilization was not statistically significant (data not shown). This suggests that spirituality does not modify the effect of patient worry in producing change in follow-up health-care utilization.
Discussion
Our study examined the relationships between spirituality, patient-rated worry, and follow-up health-care utilization among cancer survivors and found that individuals who possess higher levels of spirituality tend to have less worry of disease recurrence/progression, development of treatment-related complications, and development of new cancers. These findings are consistent with previous research among patients with advanced or terminal cancers that consistently showed such correlations between spirituality and general measures of anxiety.[10], [15], [17], [19], [30] and [31] Additionally, our study showed that a higher degree of worry about common concerns of cancer survivors is associated with more follow-up visits and calls to health-care providers. However, our data also showed that spirituality by itself is for the most part not associated with follow-up health-care utilization.
It has been documented that psychosocial factors like anxiety and spirituality can influence behaviors.[32], [33], [34], [35] and [36] Our analysis showed that both discretionary and nondiscretionary indices of health-care utilization increased significantly among highly worried cancer survivors. However, these increases are independent of one's level of spirituality. These results suggest that cancer survivors with a high degree of worry about disease recurrence/progression, development of treatment-related complications, or development of a new cancer produce a change in care-seeking behavior and may concomitantly alter the health provider's need to see the patient. Our results also suggest that while spirituality has an impact on one's level of worry, being less spiritual does not necessarily alter a cancer survivor's care-seeking behavior.
Worried patients present a potential problem for clinicians in that they may need more attention during clinic visits,37 may result in requests for more ancillary/diagnostic tests including imaging modalities,[38] and [39] or may use more medications[40] and [41] or resort to other alternative therapies[42], [43], [44] and [45] available to reduce their worries. Given that cancer patients already receive many chemotherapeutic agents for their treatment, many of them are more inclined to undergo alternative therapies.[16], [43], [46], [47] and [48] Spirituality-based interventions shown to be effective at reducing anxiety and increasing QOL may therefore have a role among cancer survivors. And because spirituality and religiosity are closely linked,29 faith-based interventions may also benefit the patient.
Our study has several implications in the assessment of cancer survivors in multidisciplinary survivorship clinics. While much attention about assessing depression, anxiety, and QOL has been given to cancer survivors, our study shows that the evaluation of one's spirituality may have some merit as well. Participants with low spirituality and a high degree of worry may benefit from activities that enhance spirituality (e.g., yoga, meditation). Because of the increasing number of cancer survivors,[32] and [49] development of clinic-based spiritual interventions to address common worries of cancer survivors may be appropriate. In addition to the implications for clinical practice, our study has implications for future research. While the literature has shown a correlation between spirituality and religiosity,29 these two concepts are not the same.[1], [2], [50], [51] and [52] It would have been interesting to compare outcomes by level of spirituality and religiosity, but our data revealed a high degree of correlation between these two concepts. Over 90% of individuals who are spiritual are also religious.[28], [53] and [54] This may be the reason that some spirituality-based interventions have enhancement of religious activities as main approaches to improve spirituality.[28] and [53]
While our study has the strengths associated with a prospective study in a relatively large number of cancer survivors treated in a single medical center, it has several limitations. Our participation rate at baseline was only 50%, although our retention rates at 6 and 12 months were on average 80%. Another limitation of our study is that the baseline surveys were conducted at different time intervals from last treatment, although this limitation also allowed us to include all kinds of cancer survivors in terms of disease and time interval from last cancer treatment. Analysis confined to patients who received treatment within the last 5 years (n = 371) showed essentially the same results. We also compared the baseline spirituality scores of the study participants according to time from last treatment to study participation (0–2, 2–5, >5) and showed no statistically significant differences. Additionally, we adjusted for time from last treatment to study participation in the multivariate analyses. Combining all the participants into one analysis allowed for our exploratory analyses to have stronger statistical power. Another limitation of our study is the crude measurement of patient worry. However, in the absence of validated instruments to measure these worries, we felt the measures reflected subjective ratings of common worries by cancer survivors. Health-care utilization would have been ideally measured continuously to better quantify the medical services utilized. However, because we included a heterogeneous group of cancer patients, this measure would be highly variable and depend on the type of disease and treatment received by the patient. Thus, type of disease and time period from last treatment were adjusted for in the multivariate analyses.
In summary, cancer survivors who possess higher levels of spirituality tend to have a lesser degree of worry over disease recurrence/progression, development of treatment complications, and development of new cancers. A higher degree of worry about the common concerns of cancer survivors is associated with more follow-up visits and calls to health providers. However, our data showed that, for the most part, spirituality is not associated with follow-up health-care utilization.
Acknowledgments
The authors thank Linda Bauer, Garrett Frost, and Gregory McFadden for their help in coordinating the study and processing the data. This work was supported by the University of Nebraska Medical Center–Eppley Cancer Center (Support Grant P30 CA 036727) and the Medical Student Research Program. The funding source had no role in the design, collection, analysis, and interpretation of the data or in the writing of the article.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Background Spirituality may aid cancer survivors as they attempt to interpret the meaning of their experience.
Objective We examined the relationship between spirituality, patient-rated worry, and health-care utilization among 551 cancer survivors with different malignancies, who were evaluated prospectively.
Methods Baseline spirituality scores were categorized into low and high spirituality groups. Patient-rated worries regarding disease recurrence/progression, developing new cancer, and developing complications from treatment were collected at baseline and at 6 and 12 months. Follow-up health-care utilization was also examined at 6 and 12 months.
Results Among the survivors, 271 (49%) reported low spirituality and 280 (51%) reported high spirituality. Of the cohort, 59% had some kind of worry regarding disease recurrence/progression, development of new cancers, and treatment complications. Highly spiritual survivors were less likely to have high levels of worries at both 6 and 12 months. Highly worried survivors were significantly more likely to place phone calls to their follow-up providers and had more frequent follow-up visits at 6 and 12 months. No interactions between spirituality and level of worry were noted to affect follow-up health-care utilization.
Conclusion Given spirituality's effect on anxiety, spirituality-based intervention may have a role in addressing cancer survivors' worries but may not improve health-care utilization.
Article Outline
- Results
- Study Participation
- Characteristics of Study Participants
- Prevalence of Spirituality and Patient Worry
- Relationship Between Spirituality and Patient Worry
- Relationship Between Patient Worry and Follow-Up Health-Care Utilization
- Relationship Between Spirituality and Health-Care Utilization
- Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Receiving a diagnosis of cancer is a life-changing event. Patients commonly seek understanding of not only the medical aspects of their disease but also how the diagnosis will affect their lives. Often, this quest to understand the meaning behind the unfortunate circumstance of disease is aided by spirituality. Spirituality motivates an individual to find meaning or purpose in his or her life experience.1 Most studies indicate that spirituality gives meaningful insight to an individual's existence and aids in the interpretation of events and relationships.[2], [3], [4], [5], [6], [7], [8] and [9]
Spiritual beliefs are widespread among cancer patients. Studies have shown that a better quality of life (QOL) is achieved in patients who practice spirituality or have those needs met by their health-care providers. They require less health care as well as experience less anxiety and a greater sense of well-being.[10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20] and [21] One may conclude that spirituality helps patients understand the meaning of their disease and provides the catalyst for significant improvement in health-related outcomes.
Vast amounts of literature affirm spirituality's positive effects on health outcomes for advanced-stage/terminally ill patients. However, very little is known about how spirituality affects the common concerns of cancer survivors. It can be inferred that spirituality continues to aid cancer survivors as they attempt to interpret the meaning of their experience during follow-up care. After completing various cancer treatments, survivors may experience worries of cancer recurrence or progression, worries of developing a different cancer, and worries of developing complications from their initial treatment.22 We explored the relationship between spirituality, patient-rated cancer-related worry, and cancer survivors' follow-up health-care utilization (follow-up doctor visits, phone calls to follow-up providers regarding medical inquiries, and emergency room visits).
Participants and Methods
Subject Selection and Eligibility
Data for this study were obtained from CANCER CARE, an observational cohort study using a self-administered questionnaire designed to evaluate follow-up care among cancer survivors.23 Participants were seen at the University of Nebraska Medical Center (UNMC) and consented to participate in a data-collection protocol (ONCOBASE) since March 2006. ONCOBASE has a 90% consent rate. To be eligible for the study, participants were at least 19 years of age (age of majority in Nebraska) and completed their cancer treatment at UNMC. Participants varied in time since completion of last cancer treatment. From a list of 5,500 eligible subjects, 2,500 were screened. The list was sorted by date of consent, and the first 2,000 subjects received the study questionnaire. Survey forms were mailed in August 2008 (baseline) and follow-up surveys were mailed in February (month 6) and August 2009 (month 12). Participants were not paid for study participation but were told that a donation to a charitable institution was made on their behalf as an altruistic incentive.23 The study was approved by the Institutional Review Board at UNMC.
Variables Analyzed
We analyzed the participants' spirituality from baseline surveys using the Functional Assessment of Cancer Therapy–Spirituality Scale (FACT-SP).24 Total spirituality scores were computed for each participant using instrument standard calculations. The cohort was categorized into two groups, consisting of low or high spirituality based on the median calculated score (<47 vs. ≥47) for the entire population. Other variables included in the analyses are shown in Table 1. Patient-rated worry pertaining to (1) disease recurrence/progression, (2) development of a new malignancy, and (3) complications related to treatment were evaluated at baseline and at 6 and 12 months. Respondents were asked to rate their level of worry for each of the above three items using a five-point Likert scale (none at all, little of the time, some of the time, most of the time, and all of the time). Each worry item was categorized as low (none at all to a little of the time) vs. high (some of the time, most of the time, all of the time). Follow-up health-care utilization was assessed at 6 and 12 months and consisted of (1) follow-up clinic visits (low, defined as none or one follow-up visit per year, vs. high, more than one follow-up visit per year), (2) phone calls to follow-up providers for medical issues (no vs. yes), and (3) emergency room visits (no vs. yes). These indices of health-care utilization were selected on the basis of whether they are discretionary (patient-driven) or nondiscretionary (physician-driven).[25] and [26] For example, follow-up clinic visits are mainly nondiscretionary in the sense that the follow-up provider primarily determines the frequency at which they are conducted, while phone calls made to follow-up providers and emergency room visits are inherently discretionary. We also evaluated the relationships between spirituality and QOL (Short Form 12 [SF-12]),27 social support,28 and religiosity (with the survey question [data not shown] “Overall, how much would you say that religious beliefs have influenced your life in the past two months?”), to establish the external validity of our spirituality cut-off score since these constructs have been associated with spirituality.[10], [15], [17], [19], [29], [30] and [31] Our analyses showed a high correlation between our categorization of low or high spirituality with QOL, social support, and religiosity.
| EVALUABLE (N) | LOW SPIRITUALITY | HIGH SPIRITUALITY | P | |||
|---|---|---|---|---|---|---|
| FREQUENCY | PERCENT | FREQUENCY | PERCENT | |||
| n | 551 | 271 | 49 | 280 | 51 | |
| Median age (range) | 59 (19–85) | 59 (22–83) | 0.99 | |||
| ≤40 | 551 | 17 | 6 | 21 | 8 | 0.78 |
| 41–60 | 137 | 51 | 135 | 48 | ||
| >60 | 117 | 43 | 124 | 44 | ||
| Sex | ||||||
| Female | 551 | 112 | 41 | 89 | 32 | 0.02 |
| Male | 159 | 59 | 191 | 68 | ||
| Race/ethnicity | ||||||
| White | 551 | 256 | 94 | 272 | 97 | 0.21 |
| Hispanic | 6 | 2 | 2 | 1 | ||
| African American | 3 | 1 | 4 | 1 | ||
| Other | 6 | 2 | 2 | 1 | ||
| Marital status | ||||||
| Single/never married | 551 | 14 | 5 | 19 | 7 | 0.67 |
| Married | 219 | 81 | 219 | 78 | ||
| Divorced/widowed | 38 | 14 | 42 | 15 | ||
| Education | ||||||
| High school | 551 | 90 | 33 | 83 | 30 | 0.49 |
| College | 105 | 39 | 122 | 44 | ||
| Postgraduate | 76 | 28 | 75 | 27 | ||
| Religion | ||||||
| Protestant | 551 | 121 | 45 | 161 | 58 | <0.01 |
| Catholic | 101 | 37 | 80 | 29 | ||
| Other | 36 | 13 | 35 | 13 | ||
| None/atheist | 13 | 5 | 4 | 1 | ||
| Income (US$) | ||||||
| <25,000 | 551 | 37 | 14 | 37 | 13 | 0.71 |
| 25,000–49,999 | 64 | 24 | 61 | 22 | ||
| 50,000–74,999 | 59 | 22 | 54 | 19 | ||
| 75,000–100,000 | 35 | 13 | 44 | 16 | ||
| >100,000 | 57 | 21 | 56 | 20 | ||
| Missing | 19 | 7 | 28 | 10 | ||
| Place of residence | ||||||
| Urban | 551 | 194 | 72 | 201 | 72 | 0.96 |
| Rural | 77 | 28 | 79 | 28 | ||
| Distance (miles) | ||||||
| ≤15 | 551 | 108 | 40 | 98 | 35 | 0.32 |
| 15–100 | 83 | 31 | 94 | 34 | ||
| 100–250 | 44 | 16 | 58 | 21 | ||
| >250 | 36 | 13 | 30 | 11 | ||
| Employment status | ||||||
| Full time | 551 | 160 | 59 | 163 | 58 | 0.93 |
| Part time | 22 | 8 | 27 | 10 | ||
| Homemaker | 25 | 9 | 26 | 9 | ||
| Student | 3 | 1 | 4 | 1 | ||
| Retired | 48 | 18 | 51 | 18 | ||
| Other | 13 | 5 | 9 | 3 | ||
| Patient is the primary income provider | 551 | 137 | 51 | 132 | 47 | 0.42 |
| Insurance | ||||||
| Employer-based | 551 | 149 | 55 | 153 | 55 | 0.95 |
| Individual-based | 47 | 17 | 48 | 17 | ||
| Medicare/Medicaid | 56 | 21 | 59 | 21 | ||
| Other | 17 | 6 | 16 | 6 | ||
| None | 2 | 1 | 4 | 1 | ||
| Prescription insurance | 551 | 239 | 88 | 242 | 86 | 0.53 |
| Type of malignancy | ||||||
| Leukemia, lymphoma, multiple myeloma | 551 | 136 | 50 | 147 | 53 | 0.86 |
| Breast, colon, prostate | 101 | 37 | 100 | 36 | ||
| Lung, pancreatic | 34 | 13 | 33 | 12 | ||
| Median time from diagnosis to study enrollment in years (range) | 4.5 (0.5–26.6) | 4.2 (0.6–26.6) | 0.28 | |||
| 0–2 years | 551 | 56 | 21 | 62 | 22 | 0.09 |
| 2–4 years | 70 | 26 | 76 | 27 | ||
| 4–8 years | 74 | 27 | 93 | 33 | ||
| >8 years | 71 | 26 | 49 | 18 | ||
| Median time from last treatment to study enrollment in years (range) | 3.6 (0.1–13.6) | 3.6 (0.4–18.7) | 0.87 | |||
| 0–2 years | 551 | 97 | 36 | 99 | 35 | 0.84 |
| 2–5 years | 83 | 31 | 92 | 33 | ||
| >5 years | 91 | 34 | 89 | 32 | ||
| Affiliation of follow-up provider | ||||||
| University-based | 551 | 193 | 71 | 190 | 68 | 0.16 |
| Community-based | 28 | 10 | 31 | 11 | ||
| Both | 50 | 18 | 54 | 19 | ||
| Missing | 0 | 0 | 5 | 2 | ||
| Treatment received | ||||||
| Chemotherapy only | 551 | 82 | 30 | 89 | 32 | 0.93 |
| Chemo + surgery + radiation | 125 | 46 | 126 | 45 | ||
| Stem cell transplantation | 64 | 24 | 65 | 23 | ||
| Prior treatment outside university | 551 | 116 | 43 | 126 | 45 | 0.60 |
Statistical Analysis
Participant characteristics were compared according to level of spirituality using a chi-square test for categorical data and the Wilcoxon test for continuous data (Table 1). Multivariate logistic regression models were fitted to evaluate separately the relationship between (1) spirituality with patient-rated worry as the outcome, (2) spirituality with follow-up health-care utilization as the outcome, and (3) patient-rated worry with follow-up health-care utilization as the outcome. In the above models, the following covariates were forced into each model: age, sex, cancer type, time from last cancer-related treatment to study start time, income, and type of medical insurance. These models were also fitted using outcomes ascertained at both 6 and 12 months. Interaction models between patient-rated worry and level of spirituality were also evaluated for an association with follow-up health-care utilization at 12 months to explore the role of spirituality in the relationship between patient-rated worry and health-care utilization. A P value of at least 0.05 was considered statistically significant.
Results
Study Participation
Of the 2,000 participants invited, 1,881 were deemed eligible (minus those who died or had wrong addresses). Baseline questionnaires were returned by 939 participants (baseline response rate of 50%). Seventeen wanted to participate only in the baseline survey. Of the 922 baseline participants, 691 returned the 6-month survey at the time of the analysis for this study, for a response rate of 76% when adjusted for deaths (182 no response, 18 deaths, 25 declined, 12 returned with wrong address). At 1 year, 691 surveys were mailed, with 588 surveys returned (58 no response, 17 deaths, 14 declined, 13 returned with wrong address, and one in hospice); a response rate of 87% was achieved after adjusting for deaths. Thirty-seven participants had missing information on spirituality, leaving a total of 551 included in this study. No differences in age, sex, and type of cancer were noted between patients included and excluded in the current analysis.
Characteristics of Study Participants
Demographic characteristics of the 551 study participants included in this study are shown in Table 1. We found that cancer survivors with low or high spirituality were more similar than different in all but two characteristics: highly spiritual survivors were more likely to be Protestant and male.
Prevalence of Spirituality and Patient Worry
Within our population, 271 (49%) survivors reported low spirituality and 280 (51%) reported high spirituality (Table 1). Also, at baseline, 277 (51%) survivors reported high levels of recurrence/progression-related worry, 190 survivors (35%) reported high levels of new malignancy–related worry, and 178 survivors (33%) reported high levels of treatment-related complication worry. As some participants may have reported one or more types of worry, this translates to 322 (59%) reporting any type of worry. Highly spiritual survivors reported significantly lower levels of high worry concerning recurrence/progression (6-month 27% vs. 38%, P < 0.01; 12-month 21% vs. 38%, P < 0.01), development of a different type of cancer (6-month 22% vs. 31%, P = 0.03; 12-month 15% vs. 26%, P < 0.01), and complications from treatment (6-month 17% vs. 30%, P < 0.01; 12-month 16% vs. 26%, P < 0.01). Highly spiritual survivors reported significantly lower levels for any type of worry at both 6 and 12 months (6 months 37% vs. 54%, P <0.01; 12 months 28% vs. 47%, P < 0.01) (Table 2).
| BASELINE | 6-MONTH | 12-MONTH | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | ||
| Recurrence/progression-related worry | Low | 106 (40) | 160 (58) | <0.01 | 154 (62) | 184 (73) | <0.01 | 166 (62) | 218 (79) | <0.01 |
| High | 160 (60) | 117 (42) | 95 (38) | 69 (27) | 103 (38) | 59 (21) | ||||
| New primary–related worry | Low | 158 (59) | 200 (72) | <0.01 | 172 (69) | 202 (78) | 0.03 | 199 (74) | 235 (85) | <0.01 |
| High | 111 (41) | 79 (28) | 76 (31) | 58 (22) | 71 (26) | 42 (15) | ||||
| Complication-related worry | Low | 166 (61) | 203 (73) | <0.01 | 175 (70) | 214 (83) | <0.01 | 200 (74) | 232 (84) | <0.01 |
| High | 104 (39) | 74 (27) | 74 (30) | 45 (17) | 69 (26) | 44 (16) | ||||
| Any worry | Low | 85 (32) | 138 (50) | <0.01 | 120 (46) | 165 (63) | <0.01 | 142 (53) | 198 (72) | <0.01 |
| High | 182 (68) | 140 (50) | 139 (54) | 97 (37) | 128 (47) | 78 (28) | ||||
Relationship Between Spirituality and Patient Worry
At the 6- and 12-month time points, after adjusting for covariates, highly spiritual survivors were significantly less likely to have worries than survivors who reported lower spirituality regarding disease recurrence/progression at 6 months (odds ratio [OR] = 0.61, 95% confidence interval [CI] 0.42–0.89, P < 0.01) and at 12 months (OR = 0.43, 95% CI 0.29–0.63, P < 0.01), complications from treatment at 6 months (OR = 0.50, 95% CI 0.33–0.76, P < 0.01) and at 12 months (OR = 0.54, 95% CI 0.35–0.83, P < 0.01), and development of a different type of cancer at 6 months (OR = 0.65, 95% CI 0.44–0.97, P = 0.04) and at 12 months (OR = 0.50, 95% CI 0.33–0.77, P < 0.01) (Table 3A).
| A | N | 6-MONTH | 12-MONTH | |||||
|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | ||
| Outcome | ||||||||
| Recurrence/progression-related worry | 502 | 1.00 | 0.61 (0.42–0.89) | 0.01 | 546 | 1.00 | 0.43 (0.29–0.63) | <0.01 |
| New primary–related worry | 508 | 1.00 | 0.65 (0.44–0.97) | 0.04 | 547 | 1.00 | 0.50 (0.33–0.77) | <0.01 |
| Complication-related worry | 508 | 1.00 | 0.50 (0.33–0.76) | <0.01 | 545 | 1.00 | 0.54 (0.35–0.83) | <0.01 |
| B | N | LOW WORRY, OR (95% CI) | HIGH WORRY, OR (95% CI) | P | N | LOW WORRY, OR (95% CI) | HIGH WORRY,OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 485 | 1.00 | 1.81 (1.04–3.12) | 0.03 | 534 | 1.00 | 1.49 (1.00–2.22) | 0.05 |
| Phone call to follow-up clinic | 504 | 1.00 | 2.21 (1.48–3.31) | <0.01 | 543 | 1.00 | 1.74 (1.20–2.53) | 0.01 |
| Emergency room visit | 503 | 1.00 | 1.75 (0.90–3.43) | 0.10 | 549 | 1.00 | 0.88 (0.52–1.51) | 0.65 |
| C | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 487 | 1.00 | 0.63 (0.37–1.10) | 0.11 | 536 | 1.00 | 0.88 (0.60–1.30) | 0.52 |
| Phone call to follow-up clinic | 506 | 1.00 | 0.77 (0.53–1.12) | 0.17 | 545 | 1.00 | 0.70 (0.49–1.00) | 0.04 |
| Emergency room visit | 505 | 1.00 | 0.56 (0.30–1.05) | 0.07 | 551 | 1.00 | 0.84 (0.50–1.41) | 0.50 |
Models adjusted for age, sex, cancer type, income, type of insurance, and time from last treatment
Relationship Between Patient Worry and Follow-Up Health-Care Utilization
Survivors who were highly worried about disease recurrence/progression, development of another type of cancer, and/or complications from treatment were more likely to visit their providers for follow-up care when compared with survivors who were less worried at 6 months (OR = 1.81, 95% CI 1.04–3.12, P = 0.03) and at 12 months (OR = 1.49, 95% CI 1.00–2.22, P = 0.05). Similarly, survivors who were highly worried were also more likely to place phone calls to their follow-up providers for medical inquiries than survivors who were less worried at 6 months (OR = 2.21, 95% CI 1.48–3.31, P < 0.01) and at 12 months (OR = 1.74, 95% CI 1.20–2.53, P = 0.01). We did not observe differences in emergency room visits between survivors with low and those with high rates of worrying at both 6 and 12 months (Table 3B).
Relationship Between Spirituality and Health-Care Utilization
No significant differences were noted for the frequency of follow-up visits, changes in follow-up providers, and emergency room visits between the levels of spirituality at both 6 and 12 months. However, at 12 months, highly spiritual survivors were less likely to call their follow-up providers for medical inquiries compared to survivors with low spirituality scores (OR = 0.70, 95% CI 0.49–1.00, P = 0.04) (Table 3C).
Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Interaction between patient-rated worry and level of spirituality as it relates to health-care utilization was not statistically significant (data not shown). This suggests that spirituality does not modify the effect of patient worry in producing change in follow-up health-care utilization.
Discussion
Our study examined the relationships between spirituality, patient-rated worry, and follow-up health-care utilization among cancer survivors and found that individuals who possess higher levels of spirituality tend to have less worry of disease recurrence/progression, development of treatment-related complications, and development of new cancers. These findings are consistent with previous research among patients with advanced or terminal cancers that consistently showed such correlations between spirituality and general measures of anxiety.[10], [15], [17], [19], [30] and [31] Additionally, our study showed that a higher degree of worry about common concerns of cancer survivors is associated with more follow-up visits and calls to health-care providers. However, our data also showed that spirituality by itself is for the most part not associated with follow-up health-care utilization.
It has been documented that psychosocial factors like anxiety and spirituality can influence behaviors.[32], [33], [34], [35] and [36] Our analysis showed that both discretionary and nondiscretionary indices of health-care utilization increased significantly among highly worried cancer survivors. However, these increases are independent of one's level of spirituality. These results suggest that cancer survivors with a high degree of worry about disease recurrence/progression, development of treatment-related complications, or development of a new cancer produce a change in care-seeking behavior and may concomitantly alter the health provider's need to see the patient. Our results also suggest that while spirituality has an impact on one's level of worry, being less spiritual does not necessarily alter a cancer survivor's care-seeking behavior.
Worried patients present a potential problem for clinicians in that they may need more attention during clinic visits,37 may result in requests for more ancillary/diagnostic tests including imaging modalities,[38] and [39] or may use more medications[40] and [41] or resort to other alternative therapies[42], [43], [44] and [45] available to reduce their worries. Given that cancer patients already receive many chemotherapeutic agents for their treatment, many of them are more inclined to undergo alternative therapies.[16], [43], [46], [47] and [48] Spirituality-based interventions shown to be effective at reducing anxiety and increasing QOL may therefore have a role among cancer survivors. And because spirituality and religiosity are closely linked,29 faith-based interventions may also benefit the patient.
Our study has several implications in the assessment of cancer survivors in multidisciplinary survivorship clinics. While much attention about assessing depression, anxiety, and QOL has been given to cancer survivors, our study shows that the evaluation of one's spirituality may have some merit as well. Participants with low spirituality and a high degree of worry may benefit from activities that enhance spirituality (e.g., yoga, meditation). Because of the increasing number of cancer survivors,[32] and [49] development of clinic-based spiritual interventions to address common worries of cancer survivors may be appropriate. In addition to the implications for clinical practice, our study has implications for future research. While the literature has shown a correlation between spirituality and religiosity,29 these two concepts are not the same.[1], [2], [50], [51] and [52] It would have been interesting to compare outcomes by level of spirituality and religiosity, but our data revealed a high degree of correlation between these two concepts. Over 90% of individuals who are spiritual are also religious.[28], [53] and [54] This may be the reason that some spirituality-based interventions have enhancement of religious activities as main approaches to improve spirituality.[28] and [53]
While our study has the strengths associated with a prospective study in a relatively large number of cancer survivors treated in a single medical center, it has several limitations. Our participation rate at baseline was only 50%, although our retention rates at 6 and 12 months were on average 80%. Another limitation of our study is that the baseline surveys were conducted at different time intervals from last treatment, although this limitation also allowed us to include all kinds of cancer survivors in terms of disease and time interval from last cancer treatment. Analysis confined to patients who received treatment within the last 5 years (n = 371) showed essentially the same results. We also compared the baseline spirituality scores of the study participants according to time from last treatment to study participation (0–2, 2–5, >5) and showed no statistically significant differences. Additionally, we adjusted for time from last treatment to study participation in the multivariate analyses. Combining all the participants into one analysis allowed for our exploratory analyses to have stronger statistical power. Another limitation of our study is the crude measurement of patient worry. However, in the absence of validated instruments to measure these worries, we felt the measures reflected subjective ratings of common worries by cancer survivors. Health-care utilization would have been ideally measured continuously to better quantify the medical services utilized. However, because we included a heterogeneous group of cancer patients, this measure would be highly variable and depend on the type of disease and treatment received by the patient. Thus, type of disease and time period from last treatment were adjusted for in the multivariate analyses.
In summary, cancer survivors who possess higher levels of spirituality tend to have a lesser degree of worry over disease recurrence/progression, development of treatment complications, and development of new cancers. A higher degree of worry about the common concerns of cancer survivors is associated with more follow-up visits and calls to health providers. However, our data showed that, for the most part, spirituality is not associated with follow-up health-care utilization.
Acknowledgments
The authors thank Linda Bauer, Garrett Frost, and Gregory McFadden for their help in coordinating the study and processing the data. This work was supported by the University of Nebraska Medical Center–Eppley Cancer Center (Support Grant P30 CA 036727) and the Medical Student Research Program. The funding source had no role in the design, collection, analysis, and interpretation of the data or in the writing of the article.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Background Spirituality may aid cancer survivors as they attempt to interpret the meaning of their experience.
Objective We examined the relationship between spirituality, patient-rated worry, and health-care utilization among 551 cancer survivors with different malignancies, who were evaluated prospectively.
Methods Baseline spirituality scores were categorized into low and high spirituality groups. Patient-rated worries regarding disease recurrence/progression, developing new cancer, and developing complications from treatment were collected at baseline and at 6 and 12 months. Follow-up health-care utilization was also examined at 6 and 12 months.
Results Among the survivors, 271 (49%) reported low spirituality and 280 (51%) reported high spirituality. Of the cohort, 59% had some kind of worry regarding disease recurrence/progression, development of new cancers, and treatment complications. Highly spiritual survivors were less likely to have high levels of worries at both 6 and 12 months. Highly worried survivors were significantly more likely to place phone calls to their follow-up providers and had more frequent follow-up visits at 6 and 12 months. No interactions between spirituality and level of worry were noted to affect follow-up health-care utilization.
Conclusion Given spirituality's effect on anxiety, spirituality-based intervention may have a role in addressing cancer survivors' worries but may not improve health-care utilization.
Article Outline
- Results
- Study Participation
- Characteristics of Study Participants
- Prevalence of Spirituality and Patient Worry
- Relationship Between Spirituality and Patient Worry
- Relationship Between Patient Worry and Follow-Up Health-Care Utilization
- Relationship Between Spirituality and Health-Care Utilization
- Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Receiving a diagnosis of cancer is a life-changing event. Patients commonly seek understanding of not only the medical aspects of their disease but also how the diagnosis will affect their lives. Often, this quest to understand the meaning behind the unfortunate circumstance of disease is aided by spirituality. Spirituality motivates an individual to find meaning or purpose in his or her life experience.1 Most studies indicate that spirituality gives meaningful insight to an individual's existence and aids in the interpretation of events and relationships.[2], [3], [4], [5], [6], [7], [8] and [9]
Spiritual beliefs are widespread among cancer patients. Studies have shown that a better quality of life (QOL) is achieved in patients who practice spirituality or have those needs met by their health-care providers. They require less health care as well as experience less anxiety and a greater sense of well-being.[10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20] and [21] One may conclude that spirituality helps patients understand the meaning of their disease and provides the catalyst for significant improvement in health-related outcomes.
Vast amounts of literature affirm spirituality's positive effects on health outcomes for advanced-stage/terminally ill patients. However, very little is known about how spirituality affects the common concerns of cancer survivors. It can be inferred that spirituality continues to aid cancer survivors as they attempt to interpret the meaning of their experience during follow-up care. After completing various cancer treatments, survivors may experience worries of cancer recurrence or progression, worries of developing a different cancer, and worries of developing complications from their initial treatment.22 We explored the relationship between spirituality, patient-rated cancer-related worry, and cancer survivors' follow-up health-care utilization (follow-up doctor visits, phone calls to follow-up providers regarding medical inquiries, and emergency room visits).
Participants and Methods
Subject Selection and Eligibility
Data for this study were obtained from CANCER CARE, an observational cohort study using a self-administered questionnaire designed to evaluate follow-up care among cancer survivors.23 Participants were seen at the University of Nebraska Medical Center (UNMC) and consented to participate in a data-collection protocol (ONCOBASE) since March 2006. ONCOBASE has a 90% consent rate. To be eligible for the study, participants were at least 19 years of age (age of majority in Nebraska) and completed their cancer treatment at UNMC. Participants varied in time since completion of last cancer treatment. From a list of 5,500 eligible subjects, 2,500 were screened. The list was sorted by date of consent, and the first 2,000 subjects received the study questionnaire. Survey forms were mailed in August 2008 (baseline) and follow-up surveys were mailed in February (month 6) and August 2009 (month 12). Participants were not paid for study participation but were told that a donation to a charitable institution was made on their behalf as an altruistic incentive.23 The study was approved by the Institutional Review Board at UNMC.
Variables Analyzed
We analyzed the participants' spirituality from baseline surveys using the Functional Assessment of Cancer Therapy–Spirituality Scale (FACT-SP).24 Total spirituality scores were computed for each participant using instrument standard calculations. The cohort was categorized into two groups, consisting of low or high spirituality based on the median calculated score (<47 vs. ≥47) for the entire population. Other variables included in the analyses are shown in Table 1. Patient-rated worry pertaining to (1) disease recurrence/progression, (2) development of a new malignancy, and (3) complications related to treatment were evaluated at baseline and at 6 and 12 months. Respondents were asked to rate their level of worry for each of the above three items using a five-point Likert scale (none at all, little of the time, some of the time, most of the time, and all of the time). Each worry item was categorized as low (none at all to a little of the time) vs. high (some of the time, most of the time, all of the time). Follow-up health-care utilization was assessed at 6 and 12 months and consisted of (1) follow-up clinic visits (low, defined as none or one follow-up visit per year, vs. high, more than one follow-up visit per year), (2) phone calls to follow-up providers for medical issues (no vs. yes), and (3) emergency room visits (no vs. yes). These indices of health-care utilization were selected on the basis of whether they are discretionary (patient-driven) or nondiscretionary (physician-driven).[25] and [26] For example, follow-up clinic visits are mainly nondiscretionary in the sense that the follow-up provider primarily determines the frequency at which they are conducted, while phone calls made to follow-up providers and emergency room visits are inherently discretionary. We also evaluated the relationships between spirituality and QOL (Short Form 12 [SF-12]),27 social support,28 and religiosity (with the survey question [data not shown] “Overall, how much would you say that religious beliefs have influenced your life in the past two months?”), to establish the external validity of our spirituality cut-off score since these constructs have been associated with spirituality.[10], [15], [17], [19], [29], [30] and [31] Our analyses showed a high correlation between our categorization of low or high spirituality with QOL, social support, and religiosity.
| EVALUABLE (N) | LOW SPIRITUALITY | HIGH SPIRITUALITY | P | |||
|---|---|---|---|---|---|---|
| FREQUENCY | PERCENT | FREQUENCY | PERCENT | |||
| n | 551 | 271 | 49 | 280 | 51 | |
| Median age (range) | 59 (19–85) | 59 (22–83) | 0.99 | |||
| ≤40 | 551 | 17 | 6 | 21 | 8 | 0.78 |
| 41–60 | 137 | 51 | 135 | 48 | ||
| >60 | 117 | 43 | 124 | 44 | ||
| Sex | ||||||
| Female | 551 | 112 | 41 | 89 | 32 | 0.02 |
| Male | 159 | 59 | 191 | 68 | ||
| Race/ethnicity | ||||||
| White | 551 | 256 | 94 | 272 | 97 | 0.21 |
| Hispanic | 6 | 2 | 2 | 1 | ||
| African American | 3 | 1 | 4 | 1 | ||
| Other | 6 | 2 | 2 | 1 | ||
| Marital status | ||||||
| Single/never married | 551 | 14 | 5 | 19 | 7 | 0.67 |
| Married | 219 | 81 | 219 | 78 | ||
| Divorced/widowed | 38 | 14 | 42 | 15 | ||
| Education | ||||||
| High school | 551 | 90 | 33 | 83 | 30 | 0.49 |
| College | 105 | 39 | 122 | 44 | ||
| Postgraduate | 76 | 28 | 75 | 27 | ||
| Religion | ||||||
| Protestant | 551 | 121 | 45 | 161 | 58 | <0.01 |
| Catholic | 101 | 37 | 80 | 29 | ||
| Other | 36 | 13 | 35 | 13 | ||
| None/atheist | 13 | 5 | 4 | 1 | ||
| Income (US$) | ||||||
| <25,000 | 551 | 37 | 14 | 37 | 13 | 0.71 |
| 25,000–49,999 | 64 | 24 | 61 | 22 | ||
| 50,000–74,999 | 59 | 22 | 54 | 19 | ||
| 75,000–100,000 | 35 | 13 | 44 | 16 | ||
| >100,000 | 57 | 21 | 56 | 20 | ||
| Missing | 19 | 7 | 28 | 10 | ||
| Place of residence | ||||||
| Urban | 551 | 194 | 72 | 201 | 72 | 0.96 |
| Rural | 77 | 28 | 79 | 28 | ||
| Distance (miles) | ||||||
| ≤15 | 551 | 108 | 40 | 98 | 35 | 0.32 |
| 15–100 | 83 | 31 | 94 | 34 | ||
| 100–250 | 44 | 16 | 58 | 21 | ||
| >250 | 36 | 13 | 30 | 11 | ||
| Employment status | ||||||
| Full time | 551 | 160 | 59 | 163 | 58 | 0.93 |
| Part time | 22 | 8 | 27 | 10 | ||
| Homemaker | 25 | 9 | 26 | 9 | ||
| Student | 3 | 1 | 4 | 1 | ||
| Retired | 48 | 18 | 51 | 18 | ||
| Other | 13 | 5 | 9 | 3 | ||
| Patient is the primary income provider | 551 | 137 | 51 | 132 | 47 | 0.42 |
| Insurance | ||||||
| Employer-based | 551 | 149 | 55 | 153 | 55 | 0.95 |
| Individual-based | 47 | 17 | 48 | 17 | ||
| Medicare/Medicaid | 56 | 21 | 59 | 21 | ||
| Other | 17 | 6 | 16 | 6 | ||
| None | 2 | 1 | 4 | 1 | ||
| Prescription insurance | 551 | 239 | 88 | 242 | 86 | 0.53 |
| Type of malignancy | ||||||
| Leukemia, lymphoma, multiple myeloma | 551 | 136 | 50 | 147 | 53 | 0.86 |
| Breast, colon, prostate | 101 | 37 | 100 | 36 | ||
| Lung, pancreatic | 34 | 13 | 33 | 12 | ||
| Median time from diagnosis to study enrollment in years (range) | 4.5 (0.5–26.6) | 4.2 (0.6–26.6) | 0.28 | |||
| 0–2 years | 551 | 56 | 21 | 62 | 22 | 0.09 |
| 2–4 years | 70 | 26 | 76 | 27 | ||
| 4–8 years | 74 | 27 | 93 | 33 | ||
| >8 years | 71 | 26 | 49 | 18 | ||
| Median time from last treatment to study enrollment in years (range) | 3.6 (0.1–13.6) | 3.6 (0.4–18.7) | 0.87 | |||
| 0–2 years | 551 | 97 | 36 | 99 | 35 | 0.84 |
| 2–5 years | 83 | 31 | 92 | 33 | ||
| >5 years | 91 | 34 | 89 | 32 | ||
| Affiliation of follow-up provider | ||||||
| University-based | 551 | 193 | 71 | 190 | 68 | 0.16 |
| Community-based | 28 | 10 | 31 | 11 | ||
| Both | 50 | 18 | 54 | 19 | ||
| Missing | 0 | 0 | 5 | 2 | ||
| Treatment received | ||||||
| Chemotherapy only | 551 | 82 | 30 | 89 | 32 | 0.93 |
| Chemo + surgery + radiation | 125 | 46 | 126 | 45 | ||
| Stem cell transplantation | 64 | 24 | 65 | 23 | ||
| Prior treatment outside university | 551 | 116 | 43 | 126 | 45 | 0.60 |
Statistical Analysis
Participant characteristics were compared according to level of spirituality using a chi-square test for categorical data and the Wilcoxon test for continuous data (Table 1). Multivariate logistic regression models were fitted to evaluate separately the relationship between (1) spirituality with patient-rated worry as the outcome, (2) spirituality with follow-up health-care utilization as the outcome, and (3) patient-rated worry with follow-up health-care utilization as the outcome. In the above models, the following covariates were forced into each model: age, sex, cancer type, time from last cancer-related treatment to study start time, income, and type of medical insurance. These models were also fitted using outcomes ascertained at both 6 and 12 months. Interaction models between patient-rated worry and level of spirituality were also evaluated for an association with follow-up health-care utilization at 12 months to explore the role of spirituality in the relationship between patient-rated worry and health-care utilization. A P value of at least 0.05 was considered statistically significant.
Results
Study Participation
Of the 2,000 participants invited, 1,881 were deemed eligible (minus those who died or had wrong addresses). Baseline questionnaires were returned by 939 participants (baseline response rate of 50%). Seventeen wanted to participate only in the baseline survey. Of the 922 baseline participants, 691 returned the 6-month survey at the time of the analysis for this study, for a response rate of 76% when adjusted for deaths (182 no response, 18 deaths, 25 declined, 12 returned with wrong address). At 1 year, 691 surveys were mailed, with 588 surveys returned (58 no response, 17 deaths, 14 declined, 13 returned with wrong address, and one in hospice); a response rate of 87% was achieved after adjusting for deaths. Thirty-seven participants had missing information on spirituality, leaving a total of 551 included in this study. No differences in age, sex, and type of cancer were noted between patients included and excluded in the current analysis.
Characteristics of Study Participants
Demographic characteristics of the 551 study participants included in this study are shown in Table 1. We found that cancer survivors with low or high spirituality were more similar than different in all but two characteristics: highly spiritual survivors were more likely to be Protestant and male.
Prevalence of Spirituality and Patient Worry
Within our population, 271 (49%) survivors reported low spirituality and 280 (51%) reported high spirituality (Table 1). Also, at baseline, 277 (51%) survivors reported high levels of recurrence/progression-related worry, 190 survivors (35%) reported high levels of new malignancy–related worry, and 178 survivors (33%) reported high levels of treatment-related complication worry. As some participants may have reported one or more types of worry, this translates to 322 (59%) reporting any type of worry. Highly spiritual survivors reported significantly lower levels of high worry concerning recurrence/progression (6-month 27% vs. 38%, P < 0.01; 12-month 21% vs. 38%, P < 0.01), development of a different type of cancer (6-month 22% vs. 31%, P = 0.03; 12-month 15% vs. 26%, P < 0.01), and complications from treatment (6-month 17% vs. 30%, P < 0.01; 12-month 16% vs. 26%, P < 0.01). Highly spiritual survivors reported significantly lower levels for any type of worry at both 6 and 12 months (6 months 37% vs. 54%, P <0.01; 12 months 28% vs. 47%, P < 0.01) (Table 2).
| BASELINE | 6-MONTH | 12-MONTH | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | LOW SPIRITUALITY, N (%) | HIGH SPIRITUALITY, N (%) | P | ||
| Recurrence/progression-related worry | Low | 106 (40) | 160 (58) | <0.01 | 154 (62) | 184 (73) | <0.01 | 166 (62) | 218 (79) | <0.01 |
| High | 160 (60) | 117 (42) | 95 (38) | 69 (27) | 103 (38) | 59 (21) | ||||
| New primary–related worry | Low | 158 (59) | 200 (72) | <0.01 | 172 (69) | 202 (78) | 0.03 | 199 (74) | 235 (85) | <0.01 |
| High | 111 (41) | 79 (28) | 76 (31) | 58 (22) | 71 (26) | 42 (15) | ||||
| Complication-related worry | Low | 166 (61) | 203 (73) | <0.01 | 175 (70) | 214 (83) | <0.01 | 200 (74) | 232 (84) | <0.01 |
| High | 104 (39) | 74 (27) | 74 (30) | 45 (17) | 69 (26) | 44 (16) | ||||
| Any worry | Low | 85 (32) | 138 (50) | <0.01 | 120 (46) | 165 (63) | <0.01 | 142 (53) | 198 (72) | <0.01 |
| High | 182 (68) | 140 (50) | 139 (54) | 97 (37) | 128 (47) | 78 (28) | ||||
Relationship Between Spirituality and Patient Worry
At the 6- and 12-month time points, after adjusting for covariates, highly spiritual survivors were significantly less likely to have worries than survivors who reported lower spirituality regarding disease recurrence/progression at 6 months (odds ratio [OR] = 0.61, 95% confidence interval [CI] 0.42–0.89, P < 0.01) and at 12 months (OR = 0.43, 95% CI 0.29–0.63, P < 0.01), complications from treatment at 6 months (OR = 0.50, 95% CI 0.33–0.76, P < 0.01) and at 12 months (OR = 0.54, 95% CI 0.35–0.83, P < 0.01), and development of a different type of cancer at 6 months (OR = 0.65, 95% CI 0.44–0.97, P = 0.04) and at 12 months (OR = 0.50, 95% CI 0.33–0.77, P < 0.01) (Table 3A).
| A | N | 6-MONTH | 12-MONTH | |||||
|---|---|---|---|---|---|---|---|---|
| LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | ||
| Outcome | ||||||||
| Recurrence/progression-related worry | 502 | 1.00 | 0.61 (0.42–0.89) | 0.01 | 546 | 1.00 | 0.43 (0.29–0.63) | <0.01 |
| New primary–related worry | 508 | 1.00 | 0.65 (0.44–0.97) | 0.04 | 547 | 1.00 | 0.50 (0.33–0.77) | <0.01 |
| Complication-related worry | 508 | 1.00 | 0.50 (0.33–0.76) | <0.01 | 545 | 1.00 | 0.54 (0.35–0.83) | <0.01 |
| B | N | LOW WORRY, OR (95% CI) | HIGH WORRY, OR (95% CI) | P | N | LOW WORRY, OR (95% CI) | HIGH WORRY,OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 485 | 1.00 | 1.81 (1.04–3.12) | 0.03 | 534 | 1.00 | 1.49 (1.00–2.22) | 0.05 |
| Phone call to follow-up clinic | 504 | 1.00 | 2.21 (1.48–3.31) | <0.01 | 543 | 1.00 | 1.74 (1.20–2.53) | 0.01 |
| Emergency room visit | 503 | 1.00 | 1.75 (0.90–3.43) | 0.10 | 549 | 1.00 | 0.88 (0.52–1.51) | 0.65 |
| C | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P | N | LOW SPIRITUALITY, OR (95% CI) | HIGH SPIRITUALITY, OR (95% CI) | P |
| Outcome | ||||||||
| Follow-up frequency | 487 | 1.00 | 0.63 (0.37–1.10) | 0.11 | 536 | 1.00 | 0.88 (0.60–1.30) | 0.52 |
| Phone call to follow-up clinic | 506 | 1.00 | 0.77 (0.53–1.12) | 0.17 | 545 | 1.00 | 0.70 (0.49–1.00) | 0.04 |
| Emergency room visit | 505 | 1.00 | 0.56 (0.30–1.05) | 0.07 | 551 | 1.00 | 0.84 (0.50–1.41) | 0.50 |
Models adjusted for age, sex, cancer type, income, type of insurance, and time from last treatment
Relationship Between Patient Worry and Follow-Up Health-Care Utilization
Survivors who were highly worried about disease recurrence/progression, development of another type of cancer, and/or complications from treatment were more likely to visit their providers for follow-up care when compared with survivors who were less worried at 6 months (OR = 1.81, 95% CI 1.04–3.12, P = 0.03) and at 12 months (OR = 1.49, 95% CI 1.00–2.22, P = 0.05). Similarly, survivors who were highly worried were also more likely to place phone calls to their follow-up providers for medical inquiries than survivors who were less worried at 6 months (OR = 2.21, 95% CI 1.48–3.31, P < 0.01) and at 12 months (OR = 1.74, 95% CI 1.20–2.53, P = 0.01). We did not observe differences in emergency room visits between survivors with low and those with high rates of worrying at both 6 and 12 months (Table 3B).
Relationship Between Spirituality and Health-Care Utilization
No significant differences were noted for the frequency of follow-up visits, changes in follow-up providers, and emergency room visits between the levels of spirituality at both 6 and 12 months. However, at 12 months, highly spiritual survivors were less likely to call their follow-up providers for medical inquiries compared to survivors with low spirituality scores (OR = 0.70, 95% CI 0.49–1.00, P = 0.04) (Table 3C).
Interaction Between Spirituality and Patient Worry With Health-Care Utilization
Interaction between patient-rated worry and level of spirituality as it relates to health-care utilization was not statistically significant (data not shown). This suggests that spirituality does not modify the effect of patient worry in producing change in follow-up health-care utilization.
Discussion
Our study examined the relationships between spirituality, patient-rated worry, and follow-up health-care utilization among cancer survivors and found that individuals who possess higher levels of spirituality tend to have less worry of disease recurrence/progression, development of treatment-related complications, and development of new cancers. These findings are consistent with previous research among patients with advanced or terminal cancers that consistently showed such correlations between spirituality and general measures of anxiety.[10], [15], [17], [19], [30] and [31] Additionally, our study showed that a higher degree of worry about common concerns of cancer survivors is associated with more follow-up visits and calls to health-care providers. However, our data also showed that spirituality by itself is for the most part not associated with follow-up health-care utilization.
It has been documented that psychosocial factors like anxiety and spirituality can influence behaviors.[32], [33], [34], [35] and [36] Our analysis showed that both discretionary and nondiscretionary indices of health-care utilization increased significantly among highly worried cancer survivors. However, these increases are independent of one's level of spirituality. These results suggest that cancer survivors with a high degree of worry about disease recurrence/progression, development of treatment-related complications, or development of a new cancer produce a change in care-seeking behavior and may concomitantly alter the health provider's need to see the patient. Our results also suggest that while spirituality has an impact on one's level of worry, being less spiritual does not necessarily alter a cancer survivor's care-seeking behavior.
Worried patients present a potential problem for clinicians in that they may need more attention during clinic visits,37 may result in requests for more ancillary/diagnostic tests including imaging modalities,[38] and [39] or may use more medications[40] and [41] or resort to other alternative therapies[42], [43], [44] and [45] available to reduce their worries. Given that cancer patients already receive many chemotherapeutic agents for their treatment, many of them are more inclined to undergo alternative therapies.[16], [43], [46], [47] and [48] Spirituality-based interventions shown to be effective at reducing anxiety and increasing QOL may therefore have a role among cancer survivors. And because spirituality and religiosity are closely linked,29 faith-based interventions may also benefit the patient.
Our study has several implications in the assessment of cancer survivors in multidisciplinary survivorship clinics. While much attention about assessing depression, anxiety, and QOL has been given to cancer survivors, our study shows that the evaluation of one's spirituality may have some merit as well. Participants with low spirituality and a high degree of worry may benefit from activities that enhance spirituality (e.g., yoga, meditation). Because of the increasing number of cancer survivors,[32] and [49] development of clinic-based spiritual interventions to address common worries of cancer survivors may be appropriate. In addition to the implications for clinical practice, our study has implications for future research. While the literature has shown a correlation between spirituality and religiosity,29 these two concepts are not the same.[1], [2], [50], [51] and [52] It would have been interesting to compare outcomes by level of spirituality and religiosity, but our data revealed a high degree of correlation between these two concepts. Over 90% of individuals who are spiritual are also religious.[28], [53] and [54] This may be the reason that some spirituality-based interventions have enhancement of religious activities as main approaches to improve spirituality.[28] and [53]
While our study has the strengths associated with a prospective study in a relatively large number of cancer survivors treated in a single medical center, it has several limitations. Our participation rate at baseline was only 50%, although our retention rates at 6 and 12 months were on average 80%. Another limitation of our study is that the baseline surveys were conducted at different time intervals from last treatment, although this limitation also allowed us to include all kinds of cancer survivors in terms of disease and time interval from last cancer treatment. Analysis confined to patients who received treatment within the last 5 years (n = 371) showed essentially the same results. We also compared the baseline spirituality scores of the study participants according to time from last treatment to study participation (0–2, 2–5, >5) and showed no statistically significant differences. Additionally, we adjusted for time from last treatment to study participation in the multivariate analyses. Combining all the participants into one analysis allowed for our exploratory analyses to have stronger statistical power. Another limitation of our study is the crude measurement of patient worry. However, in the absence of validated instruments to measure these worries, we felt the measures reflected subjective ratings of common worries by cancer survivors. Health-care utilization would have been ideally measured continuously to better quantify the medical services utilized. However, because we included a heterogeneous group of cancer patients, this measure would be highly variable and depend on the type of disease and treatment received by the patient. Thus, type of disease and time period from last treatment were adjusted for in the multivariate analyses.
In summary, cancer survivors who possess higher levels of spirituality tend to have a lesser degree of worry over disease recurrence/progression, development of treatment complications, and development of new cancers. A higher degree of worry about the common concerns of cancer survivors is associated with more follow-up visits and calls to health providers. However, our data showed that, for the most part, spirituality is not associated with follow-up health-care utilization.
Acknowledgments
The authors thank Linda Bauer, Garrett Frost, and Gregory McFadden for their help in coordinating the study and processing the data. This work was supported by the University of Nebraska Medical Center–Eppley Cancer Center (Support Grant P30 CA 036727) and the Medical Student Research Program. The funding source had no role in the design, collection, analysis, and interpretation of the data or in the writing of the article.
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Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.