Squamous cell carcinomas of the head and neck account for 3% of all new cancers diagnosed annually within the United States.¹ According to the Surveillance Epidemiology
and Ends Reports (SEER) database, 79% of patients in the US present with local or regional advanced disease and are treated with combinedmodality therapy.² Factors that influence treatment decision making include the following: resectability, function preservation, local patterns of care, and patient characteristics or preferences. In this cohort of patients, disease eradication is the goal of therapy. Conversely, for approximately 16% of patients who are diagnosed with metastatic disease at presentation, or the substantial portion of patients who develop non-curable disease recurrence, the main therapeutic objectives are palliation and prolongation of survival (accessible at http://seer.cancer.gov/statfacts/html/oralcav.html).^2,3 We define patients as having non-curable recurrence if development of metastatic disease or development of local recurrence is not amenable to either surgical resection or re-irradiation therapy. Several changes in the epidemiology and treatment of metastatic and recurrent head and neck cancer (M/RHNC) have resulted in paradigm shifts that effect treatment decision making in this population. First, a combination of standard chemotherapy with cetuximab has demonstrated a survival advantage. This is the first time that any agent or combination of agents has demonstrated superiority in the treatment of M/RHNC.⁴ Second, human papilloma virus (HPV)-associated oropharyngeal cancers are epidemic in many areas of the world. The cohort of HPV-positive patients has an excellent prognosis with currently available primary treatment regimens. The recurrence rate in this population is low; however, data regarding the treatment responsiveness of HPV-associated tumors that recur after primary therapy is lacking. Finally, with the increased use of aggressive combined modality regimens as primary therapy, patients with recurrent disease are often heavily pretreated and suffer from symptoms secondary to their initial therapy. It is important to understand how the evolving epidemiology and treatment paradigms affect decision making for our patients. This requires an understanding of how these changes affect both the benefits and risks to the patient.

Squamous cell carcinomas of the head and neck account for 3% of all new cancers diagnosed annually within the United States.¹ According to the Surveillance Epidemiology
and Ends Reports (SEER) database, 79% of patients in the US present with local or regional advanced disease and are treated with combinedmodality therapy.² Factors that influence treatment decision making include the following: resectability, function preservation, local patterns of care, and patient characteristics or preferences. In this cohort of patients, disease eradication is the goal of therapy. Conversely, for approximately 16% of patients who are diagnosed with metastatic disease at presentation, or the substantial portion of patients who develop non-curable disease recurrence, the main therapeutic objectives are palliation and prolongation of survival (accessible at http://seer.cancer.gov/statfacts/html/oralcav.html).^2,3 We define patients as having non-curable recurrence if development of metastatic disease or development of local recurrence is not amenable to either surgical resection or re-irradiation therapy. Several changes in the epidemiology and treatment of metastatic and recurrent head and neck cancer (M/RHNC) have resulted in paradigm shifts that effect treatment decision making in this population. First, a combination of standard chemotherapy with cetuximab has demonstrated a survival advantage. This is the first time that any agent or combination of agents has demonstrated superiority in the treatment of M/RHNC.⁴ Second, human papilloma virus (HPV)-associated oropharyngeal cancers are epidemic in many areas of the world. The cohort of HPV-positive patients has an excellent prognosis with currently available primary treatment regimens. The recurrence rate in this population is low; however, data regarding the treatment responsiveness of HPV-associated tumors that recur after primary therapy is lacking. Finally, with the increased use of aggressive combined modality regimens as primary therapy, patients with recurrent disease are often heavily pretreated and suffer from symptoms secondary to their initial therapy. It is important to understand how the evolving epidemiology and treatment paradigms affect decision making for our patients. This requires an understanding of how these changes affect both the benefits and risks to the patient.

Squamous cell carcinomas of the head and neck account for 3% of all new cancers diagnosed annually within the United States.¹ According to the Surveillance Epidemiology
and Ends Reports (SEER) database, 79% of patients in the US present with local or regional advanced disease and are treated with combinedmodality therapy.² Factors that influence treatment decision making include the following: resectability, function preservation, local patterns of care, and patient characteristics or preferences. In this cohort of patients, disease eradication is the goal of therapy. Conversely, for approximately 16% of patients who are diagnosed with metastatic disease at presentation, or the substantial portion of patients who develop non-curable disease recurrence, the main therapeutic objectives are palliation and prolongation of survival (accessible at http://seer.cancer.gov/statfacts/html/oralcav.html).^2,3 We define patients as having non-curable recurrence if development of metastatic disease or development of local recurrence is not amenable to either surgical resection or re-irradiation therapy. Several changes in the epidemiology and treatment of metastatic and recurrent head and neck cancer (M/RHNC) have resulted in paradigm shifts that effect treatment decision making in this population. First, a combination of standard chemotherapy with cetuximab has demonstrated a survival advantage. This is the first time that any agent or combination of agents has demonstrated superiority in the treatment of M/RHNC.⁴ Second, human papilloma virus (HPV)-associated oropharyngeal cancers are epidemic in many areas of the world. The cohort of HPV-positive patients has an excellent prognosis with currently available primary treatment regimens. The recurrence rate in this population is low; however, data regarding the treatment responsiveness of HPV-associated tumors that recur after primary therapy is lacking. Finally, with the increased use of aggressive combined modality regimens as primary therapy, patients with recurrent disease are often heavily pretreated and suffer from symptoms secondary to their initial therapy. It is important to understand how the evolving epidemiology and treatment paradigms affect decision making for our patients. This requires an understanding of how these changes affect both the benefits and risks to the patient.

I often daydream that my mom is still here and living cancer free. I like to imagine her teaching art at a prestigious private school in New York City, or maybe retired quilting in a little cottage in Vermont, or at home sketching on her back porch watching her dog playing in the yard. My mother battled cancer for over 20 years; and I find myself wondering what would it have been like to grow up without living under the shadow of the “c” word. How would things have been different? Would my mom still have been the fierce, strong, and passionate woman I remember? She never allowed herself to be a cancer patient. She was a mother, an artist, a friend, a teacher, and a cancer warrior. My mother was diagnosed with Stage II breast cancer in July of 1991. I was 7 years old and my younger sister was 2. She found a pea-sized lump in her left breast by self examination. Her treatment was to be a lumpectomy and radiation. While in surgery, they found numerous lumps in her left breast as well as her right breast and lymph nodes. My father had to make the decision for a radical mastectomy of her left breast and a partial of her right. It was very hard to see her going through all of it. I can remember having to spend a lot of time overnight with friends and family. There was a lot of crying and adults whispering. My mom was in bed most of the time and I remember waking up at night to her vomiting. At 7 years old, I knew words like mastectomy and chemotherapy. One night I couldn’t sleep and I went up stairs to ask my mom if she was dying. How do you answer that? My pediatrician told my mother to give me a journal so I could draw and write my thoughts and emotions. In the afternoons, the two of us would write in our journals. She kept my composition notebook filled with funny round people and lots of “x”s over my mommy’s “bueb”.

I often daydream that my mom is still here and living cancer free. I like to imagine her teaching art at a prestigious private school in New York City, or maybe retired quilting in a little cottage in Vermont, or at home sketching on her back porch watching her dog playing in the yard. My mother battled cancer for over 20 years; and I find myself wondering what would it have been like to grow up without living under the shadow of the “c” word. How would things have been different? Would my mom still have been the fierce, strong, and passionate woman I remember? She never allowed herself to be a cancer patient. She was a mother, an artist, a friend, a teacher, and a cancer warrior. My mother was diagnosed with Stage II breast cancer in July of 1991. I was 7 years old and my younger sister was 2. She found a pea-sized lump in her left breast by self examination. Her treatment was to be a lumpectomy and radiation. While in surgery, they found numerous lumps in her left breast as well as her right breast and lymph nodes. My father had to make the decision for a radical mastectomy of her left breast and a partial of her right. It was very hard to see her going through all of it. I can remember having to spend a lot of time overnight with friends and family. There was a lot of crying and adults whispering. My mom was in bed most of the time and I remember waking up at night to her vomiting. At 7 years old, I knew words like mastectomy and chemotherapy. One night I couldn’t sleep and I went up stairs to ask my mom if she was dying. How do you answer that? My pediatrician told my mother to give me a journal so I could draw and write my thoughts and emotions. In the afternoons, the two of us would write in our journals. She kept my composition notebook filled with funny round people and lots of “x”s over my mommy’s “bueb”.

I often daydream that my mom is still here and living cancer free. I like to imagine her teaching art at a prestigious private school in New York City, or maybe retired quilting in a little cottage in Vermont, or at home sketching on her back porch watching her dog playing in the yard. My mother battled cancer for over 20 years; and I find myself wondering what would it have been like to grow up without living under the shadow of the “c” word. How would things have been different? Would my mom still have been the fierce, strong, and passionate woman I remember? She never allowed herself to be a cancer patient. She was a mother, an artist, a friend, a teacher, and a cancer warrior. My mother was diagnosed with Stage II breast cancer in July of 1991. I was 7 years old and my younger sister was 2. She found a pea-sized lump in her left breast by self examination. Her treatment was to be a lumpectomy and radiation. While in surgery, they found numerous lumps in her left breast as well as her right breast and lymph nodes. My father had to make the decision for a radical mastectomy of her left breast and a partial of her right. It was very hard to see her going through all of it. I can remember having to spend a lot of time overnight with friends and family. There was a lot of crying and adults whispering. My mom was in bed most of the time and I remember waking up at night to her vomiting. At 7 years old, I knew words like mastectomy and chemotherapy. One night I couldn’t sleep and I went up stairs to ask my mom if she was dying. How do you answer that? My pediatrician told my mother to give me a journal so I could draw and write my thoughts and emotions. In the afternoons, the two of us would write in our journals. She kept my composition notebook filled with funny round people and lots of “x”s over my mommy’s “bueb”.

Background Skin reactions and pain are commonly reported side effects of radiation therapy (RT).

Objective To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain.

Methods A self-report survey—adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire—assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity of pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain.

Results Survey respondents (N = 106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (P ≤ .007). Patients receiving head/neck/brain RT reported increased skin problems (P < .0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (P = .066 and P = .122, respectively).

Limitations Small sample size, exploratory analyses, and nonvalidated measure.

Conclusions Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site while patients receiving head/neck/brain RT had increased skin problems but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain and that interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients.

Click on the PDF icon at the top of this introduction to read the full article.

Background Skin reactions and pain are commonly reported side effects of radiation therapy (RT).

Objective To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain.

Methods A self-report survey—adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire—assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity of pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain.

Results Survey respondents (N = 106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (P ≤ .007). Patients receiving head/neck/brain RT reported increased skin problems (P < .0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (P = .066 and P = .122, respectively).

Limitations Small sample size, exploratory analyses, and nonvalidated measure.

Conclusions Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site while patients receiving head/neck/brain RT had increased skin problems but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain and that interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients.

Click on the PDF icon at the top of this introduction to read the full article.

Background Skin reactions and pain are commonly reported side effects of radiation therapy (RT).

Objective To characterize RT-induced symptoms according to treatment site subgroups and identify skin symptoms that correlate with pain.

Methods A self-report survey—adapted from the MD Anderson Symptom Inventory and the McGill Pain Questionnaire—assessed RT-induced skin problems, pain, and specific skin symptoms. Wilcoxon Sign Ranked tests compared mean severity of pre- and post-RT pain and skin problems within each RT-site subgroup. Multiple linear regression (MLR) investigated associations between skin symptoms and pain.

Results Survey respondents (N = 106) were 58% female and on average 64 years old. RT sites included lung, breast, lower abdomen, head/neck/brain, and upper abdomen. Only patients receiving breast RT reported significant increases in treatment site pain and skin problems (P ≤ .007). Patients receiving head/neck/brain RT reported increased skin problems (P < .0009). MLR showed that post-RT skin tenderness and tightness were most strongly associated with post-RT pain (P = .066 and P = .122, respectively).

Limitations Small sample size, exploratory analyses, and nonvalidated measure.

Conclusions Only patients receiving breast RT reported significant increases in pain and skin problems at the RT site while patients receiving head/neck/brain RT had increased skin problems but not pain. These findings suggest that the severity of skin problems is not the only factor that contributes to pain and that interventions should be tailored to specifically target pain at the RT site, possibly by targeting tenderness and tightness. These findings should be confirmed in a larger sampling of RT patients.

Click on the PDF icon at the top of this introduction to read the full article.

Over 170,000 cases of metastatic brain tumors are diagnosed in the United States each year; and the length of survival for patients with brain metastases is often quite limited, ranging from a few weeks to several months.¹ The Radiation Therapy Oncology Group (RTOG) Recursive Partitioning Analysis (RPA) and the Graded Prognostic Assessment (GPA) are 2 prognostic indices that have been validated to predict survival and guide the treatment of these patients.^2-5 The RPA and GPA indices were formulated by comparing survival to patient and tumor characteristics compiled from RTOG brain metastasis treatment protocols spanning greater than 3 decades. The RPA has 3 classes of patients enumerated as “I”, “II”, and “III,” with class I patients having the longest predicted survival and class III patients having the worst prognosis. The RPA classes are based upon factors that include patient age and Karnofsky Performance Status (KPS) as well as control of the primary tumor and evidence of extra-cranial metastases (Table 1).² The GPA has 4 classes of patients with a score that may be considered analogous to a grade point average achieved by students in school. The classes are arranged into 4 groupings, which are divided from best to worst prognosis as follows: 3.5 to 4.0, 3.0, 1.5 to 2.5, and 0.0 to 1.0. The GPA employs criteria similar to but slightly different from those used in the RPA, estimating survival by patient age and performance status as well as the number of brain metastases and evidence of extracranial metastases (Table 2).⁴

Treatment options for patients with brain metastases include surgery, stereotactic radiosurgery (SRS), whole brain radiation therapy (WBRT), supportive measures such as corticosteroids, or a combination of these modalities. The survival of the worst prognosis brain metastases patients treated with WBRT and steroids is estimated by the RPA and GPA tools to be 2.3 months and 2.6 months, respectively.^2,4 As noted above, the patient data from which the RPA and GPA indices were created included patients treated on clinical trials. This could have resulted in the selection of patients more fit than average patients and lead to an overestimation of survival when applied to all patients. The clinical trial data used were drawn from over 3 decades, during which supportive care and chemotherapy treatments improved. This could result in an underestimation of survival when applied to patients treated with current systemic therapies and supportive care. It is important for physicians to have an accurate method to predict survival in patients to ensure that appropriate treatments can be recommended.

Over 170,000 cases of metastatic brain tumors are diagnosed in the United States each year; and the length of survival for patients with brain metastases is often quite limited, ranging from a few weeks to several months.¹ The Radiation Therapy Oncology Group (RTOG) Recursive Partitioning Analysis (RPA) and the Graded Prognostic Assessment (GPA) are 2 prognostic indices that have been validated to predict survival and guide the treatment of these patients.^2-5 The RPA and GPA indices were formulated by comparing survival to patient and tumor characteristics compiled from RTOG brain metastasis treatment protocols spanning greater than 3 decades. The RPA has 3 classes of patients enumerated as “I”, “II”, and “III,” with class I patients having the longest predicted survival and class III patients having the worst prognosis. The RPA classes are based upon factors that include patient age and Karnofsky Performance Status (KPS) as well as control of the primary tumor and evidence of extra-cranial metastases (Table 1).² The GPA has 4 classes of patients with a score that may be considered analogous to a grade point average achieved by students in school. The classes are arranged into 4 groupings, which are divided from best to worst prognosis as follows: 3.5 to 4.0, 3.0, 1.5 to 2.5, and 0.0 to 1.0. The GPA employs criteria similar to but slightly different from those used in the RPA, estimating survival by patient age and performance status as well as the number of brain metastases and evidence of extracranial metastases (Table 2).⁴

Treatment options for patients with brain metastases include surgery, stereotactic radiosurgery (SRS), whole brain radiation therapy (WBRT), supportive measures such as corticosteroids, or a combination of these modalities. The survival of the worst prognosis brain metastases patients treated with WBRT and steroids is estimated by the RPA and GPA tools to be 2.3 months and 2.6 months, respectively.^2,4 As noted above, the patient data from which the RPA and GPA indices were created included patients treated on clinical trials. This could have resulted in the selection of patients more fit than average patients and lead to an overestimation of survival when applied to all patients. The clinical trial data used were drawn from over 3 decades, during which supportive care and chemotherapy treatments improved. This could result in an underestimation of survival when applied to patients treated with current systemic therapies and supportive care. It is important for physicians to have an accurate method to predict survival in patients to ensure that appropriate treatments can be recommended.

Over 170,000 cases of metastatic brain tumors are diagnosed in the United States each year; and the length of survival for patients with brain metastases is often quite limited, ranging from a few weeks to several months.¹ The Radiation Therapy Oncology Group (RTOG) Recursive Partitioning Analysis (RPA) and the Graded Prognostic Assessment (GPA) are 2 prognostic indices that have been validated to predict survival and guide the treatment of these patients.^2-5 The RPA and GPA indices were formulated by comparing survival to patient and tumor characteristics compiled from RTOG brain metastasis treatment protocols spanning greater than 3 decades. The RPA has 3 classes of patients enumerated as “I”, “II”, and “III,” with class I patients having the longest predicted survival and class III patients having the worst prognosis. The RPA classes are based upon factors that include patient age and Karnofsky Performance Status (KPS) as well as control of the primary tumor and evidence of extra-cranial metastases (Table 1).² The GPA has 4 classes of patients with a score that may be considered analogous to a grade point average achieved by students in school. The classes are arranged into 4 groupings, which are divided from best to worst prognosis as follows: 3.5 to 4.0, 3.0, 1.5 to 2.5, and 0.0 to 1.0. The GPA employs criteria similar to but slightly different from those used in the RPA, estimating survival by patient age and performance status as well as the number of brain metastases and evidence of extracranial metastases (Table 2).⁴

Treatment options for patients with brain metastases include surgery, stereotactic radiosurgery (SRS), whole brain radiation therapy (WBRT), supportive measures such as corticosteroids, or a combination of these modalities. The survival of the worst prognosis brain metastases patients treated with WBRT and steroids is estimated by the RPA and GPA tools to be 2.3 months and 2.6 months, respectively.^2,4 As noted above, the patient data from which the RPA and GPA indices were created included patients treated on clinical trials. This could have resulted in the selection of patients more fit than average patients and lead to an overestimation of survival when applied to all patients. The clinical trial data used were drawn from over 3 decades, during which supportive care and chemotherapy treatments improved. This could result in an underestimation of survival when applied to patients treated with current systemic therapies and supportive care. It is important for physicians to have an accurate method to predict survival in patients to ensure that appropriate treatments can be recommended.

Palliative care quality indicators should be part of oncology performance assessment initiatives. Palliative care programs should also include initiatives to address the overall quality of palliative care issues, such as pain management, in the settings where the programs are located.1 Measuring quality facilitates justifying palliative care initiatives and documenting their impact, targeting quality improvement efforts, monitoring care for deficiencies, and evaluating providers (Table 1). However, measurement in this field is often not straightforward. Potential challenges include defining the population to measure and data sources, collection and analysis, as well as choosing among many potentially relevant issues and quality measures. This article describes an approach to quality measurement in palliative care, beginning with a description of key frameworks to guide the measurement approach. The article also reviews key steps in designing a quality measurement program, which include defining the quality problem and population to measure and choosing domains and specific measures. Finally, the article addresses other key considerations, such as considering unintended consequences and using data for quality improvement.

Frameworks for evaluating quality

The Donabedian framework of structure (stable elements of the health care system), process (what health care services are provided), and outcome (end results for the patient and family) can be
applied to relevant domains to guide evaluation design (Table 2).^2-8 Key structural elements may include characteristics of programs (eg, palliative clinic availability), providers (eg, multidisciplinary members of the palliative care team), and tools (eg, do-not-resuscitate policies). Processes may include technical aspects of care, such as appropriate prescribing and interpersonal aspects of care (eg, coordination among providers). Outcomes may include patient quality of life or symptoms, perceptions of care, or caregiver outcomes such as burden. Outcomes may also be categorized as overuse (eg, use of chemotherapy at the end of life compared to national benchmarks), underuse (eg, lower rates of hospice care or use of antinausea drugs), or appropriateness of care (eg, accurately documenting patients’ preferences for care).

Palliative care quality indicators should be part of oncology performance assessment initiatives. Palliative care programs should also include initiatives to address the overall quality of palliative care issues, such as pain management, in the settings where the programs are located.1 Measuring quality facilitates justifying palliative care initiatives and documenting their impact, targeting quality improvement efforts, monitoring care for deficiencies, and evaluating providers (Table 1). However, measurement in this field is often not straightforward. Potential challenges include defining the population to measure and data sources, collection and analysis, as well as choosing among many potentially relevant issues and quality measures. This article describes an approach to quality measurement in palliative care, beginning with a description of key frameworks to guide the measurement approach. The article also reviews key steps in designing a quality measurement program, which include defining the quality problem and population to measure and choosing domains and specific measures. Finally, the article addresses other key considerations, such as considering unintended consequences and using data for quality improvement.

Frameworks for evaluating quality

The Donabedian framework of structure (stable elements of the health care system), process (what health care services are provided), and outcome (end results for the patient and family) can be
applied to relevant domains to guide evaluation design (Table 2).^2-8 Key structural elements may include characteristics of programs (eg, palliative clinic availability), providers (eg, multidisciplinary members of the palliative care team), and tools (eg, do-not-resuscitate policies). Processes may include technical aspects of care, such as appropriate prescribing and interpersonal aspects of care (eg, coordination among providers). Outcomes may include patient quality of life or symptoms, perceptions of care, or caregiver outcomes such as burden. Outcomes may also be categorized as overuse (eg, use of chemotherapy at the end of life compared to national benchmarks), underuse (eg, lower rates of hospice care or use of antinausea drugs), or appropriateness of care (eg, accurately documenting patients’ preferences for care).

Palliative care quality indicators should be part of oncology performance assessment initiatives. Palliative care programs should also include initiatives to address the overall quality of palliative care issues, such as pain management, in the settings where the programs are located.1 Measuring quality facilitates justifying palliative care initiatives and documenting their impact, targeting quality improvement efforts, monitoring care for deficiencies, and evaluating providers (Table 1). However, measurement in this field is often not straightforward. Potential challenges include defining the population to measure and data sources, collection and analysis, as well as choosing among many potentially relevant issues and quality measures. This article describes an approach to quality measurement in palliative care, beginning with a description of key frameworks to guide the measurement approach. The article also reviews key steps in designing a quality measurement program, which include defining the quality problem and population to measure and choosing domains and specific measures. Finally, the article addresses other key considerations, such as considering unintended consequences and using data for quality improvement.

Frameworks for evaluating quality

The Donabedian framework of structure (stable elements of the health care system), process (what health care services are provided), and outcome (end results for the patient and family) can be
applied to relevant domains to guide evaluation design (Table 2).^2-8 Key structural elements may include characteristics of programs (eg, palliative clinic availability), providers (eg, multidisciplinary members of the palliative care team), and tools (eg, do-not-resuscitate policies). Processes may include technical aspects of care, such as appropriate prescribing and interpersonal aspects of care (eg, coordination among providers). Outcomes may include patient quality of life or symptoms, perceptions of care, or caregiver outcomes such as burden. Outcomes may also be categorized as overuse (eg, use of chemotherapy at the end of life compared to national benchmarks), underuse (eg, lower rates of hospice care or use of antinausea drugs), or appropriateness of care (eg, accurately documenting patients’ preferences for care).

To the Editor: We would like to raise the following points about the paper by Dr. Aggarwal et al¹ interpreting the Future Revascularization Evaluation in Patients With Diabetes Mellitus: Optimal Management of Multivessel Disease (FREEDOM) trial.²

The patients enrolled in the FREEDOM trial do not in our opinion completely reflect the real patients that we meet in our daily “real-world” practice.² The patients in the FREEDOM trial did not have a high-risk profile. Rather, the mean European System for Cardiac Operative Risk Evaluation score (EuroSCORE) was 2.7 ± 2.4 in the percutaneous coronary intervention (PCI) group and 2.8 ± 2.5 in the coronary artery bypass grafting group—whereas a score of 5 or more on the EuroSCORE is associated with decreased rates of survival.²

Furthermore, patients with left main coronary artery stenosis were completely excluded from the FREEDOM trial,² but this type of stenosis, with different grades, is found in about 30% of diabetic patients with multivessel coronary artery disease, a fact that may significantly influence the decision regarding the revascularization strategy (bypass grafting or PCI), especially in a clinical setting such as acute coronary syndrome.^3–5

In addition, the authors did not clearly highlight that diabetes mellitus is an independent risk factor for coronary lesion progression, coronary bypass graft occlusion, and cardiac mortality after bypass grafting surgery.^6–8 Clinical outcomes after bypass grafting in diabetic patients are worse than in nondiabetic patients; diabetic patients have higher rates of morbidity (deep sternal instability, wound infection, stroke, renal dysfunction, and respiratory problems), longer intensive care unit and hospital stays, and poorer postoperative physical functioning and quality of life.^6–8

The authors correctly explain the reasons for the superiority of coronary artery bypass grafting vs PCI in diabetic patients, either by the ability to achieve complete revascularization or by using more arterial grafts, and especially the left internal thoracic artery.¹ However, clarifying details on the strategy of revascularization in the FREEDOM trial are scarcely provided.² All we know from the provided details in this regard is that “for CABG surgery, arterial revascularization was encouraged” and 94.4% of the patients undergoing bypass grafting received left internal thoracic artery grafts.²

In addition, whereas off-pump coronary artery bypass grafting surgery is superior to conventional bypass grafting in terms of lower rates of death and major adverse cardiac and cerebrovascular events in diabetic patients with multivessel coronary artery disease,³ only 165 (18.5%) of the 893 patients who underwent bypass grafting in the FREEDOM trial underwent an off-pump procedure.^2,3

Therefore, all these considerations should be taken into account as the physician team discusses the therapeutic options (PCI and bypass grafting surgery) with diabetic patients who have multivessel coronary artery disease.

To the Editor: We would like to raise the following points about the paper by Dr. Aggarwal et al¹ interpreting the Future Revascularization Evaluation in Patients With Diabetes Mellitus: Optimal Management of Multivessel Disease (FREEDOM) trial.²

The patients enrolled in the FREEDOM trial do not in our opinion completely reflect the real patients that we meet in our daily “real-world” practice.² The patients in the FREEDOM trial did not have a high-risk profile. Rather, the mean European System for Cardiac Operative Risk Evaluation score (EuroSCORE) was 2.7 ± 2.4 in the percutaneous coronary intervention (PCI) group and 2.8 ± 2.5 in the coronary artery bypass grafting group—whereas a score of 5 or more on the EuroSCORE is associated with decreased rates of survival.²

Furthermore, patients with left main coronary artery stenosis were completely excluded from the FREEDOM trial,² but this type of stenosis, with different grades, is found in about 30% of diabetic patients with multivessel coronary artery disease, a fact that may significantly influence the decision regarding the revascularization strategy (bypass grafting or PCI), especially in a clinical setting such as acute coronary syndrome.^3–5

In addition, the authors did not clearly highlight that diabetes mellitus is an independent risk factor for coronary lesion progression, coronary bypass graft occlusion, and cardiac mortality after bypass grafting surgery.^6–8 Clinical outcomes after bypass grafting in diabetic patients are worse than in nondiabetic patients; diabetic patients have higher rates of morbidity (deep sternal instability, wound infection, stroke, renal dysfunction, and respiratory problems), longer intensive care unit and hospital stays, and poorer postoperative physical functioning and quality of life.^6–8

The authors correctly explain the reasons for the superiority of coronary artery bypass grafting vs PCI in diabetic patients, either by the ability to achieve complete revascularization or by using more arterial grafts, and especially the left internal thoracic artery.¹ However, clarifying details on the strategy of revascularization in the FREEDOM trial are scarcely provided.² All we know from the provided details in this regard is that “for CABG surgery, arterial revascularization was encouraged” and 94.4% of the patients undergoing bypass grafting received left internal thoracic artery grafts.²

In addition, whereas off-pump coronary artery bypass grafting surgery is superior to conventional bypass grafting in terms of lower rates of death and major adverse cardiac and cerebrovascular events in diabetic patients with multivessel coronary artery disease,³ only 165 (18.5%) of the 893 patients who underwent bypass grafting in the FREEDOM trial underwent an off-pump procedure.^2,3

Therefore, all these considerations should be taken into account as the physician team discusses the therapeutic options (PCI and bypass grafting surgery) with diabetic patients who have multivessel coronary artery disease.

To the Editor: We would like to raise the following points about the paper by Dr. Aggarwal et al¹ interpreting the Future Revascularization Evaluation in Patients With Diabetes Mellitus: Optimal Management of Multivessel Disease (FREEDOM) trial.²

The patients enrolled in the FREEDOM trial do not in our opinion completely reflect the real patients that we meet in our daily “real-world” practice.² The patients in the FREEDOM trial did not have a high-risk profile. Rather, the mean European System for Cardiac Operative Risk Evaluation score (EuroSCORE) was 2.7 ± 2.4 in the percutaneous coronary intervention (PCI) group and 2.8 ± 2.5 in the coronary artery bypass grafting group—whereas a score of 5 or more on the EuroSCORE is associated with decreased rates of survival.²

Furthermore, patients with left main coronary artery stenosis were completely excluded from the FREEDOM trial,² but this type of stenosis, with different grades, is found in about 30% of diabetic patients with multivessel coronary artery disease, a fact that may significantly influence the decision regarding the revascularization strategy (bypass grafting or PCI), especially in a clinical setting such as acute coronary syndrome.^3–5

In addition, the authors did not clearly highlight that diabetes mellitus is an independent risk factor for coronary lesion progression, coronary bypass graft occlusion, and cardiac mortality after bypass grafting surgery.^6–8 Clinical outcomes after bypass grafting in diabetic patients are worse than in nondiabetic patients; diabetic patients have higher rates of morbidity (deep sternal instability, wound infection, stroke, renal dysfunction, and respiratory problems), longer intensive care unit and hospital stays, and poorer postoperative physical functioning and quality of life.^6–8

The authors correctly explain the reasons for the superiority of coronary artery bypass grafting vs PCI in diabetic patients, either by the ability to achieve complete revascularization or by using more arterial grafts, and especially the left internal thoracic artery.¹ However, clarifying details on the strategy of revascularization in the FREEDOM trial are scarcely provided.² All we know from the provided details in this regard is that “for CABG surgery, arterial revascularization was encouraged” and 94.4% of the patients undergoing bypass grafting received left internal thoracic artery grafts.²

In addition, whereas off-pump coronary artery bypass grafting surgery is superior to conventional bypass grafting in terms of lower rates of death and major adverse cardiac and cerebrovascular events in diabetic patients with multivessel coronary artery disease,³ only 165 (18.5%) of the 893 patients who underwent bypass grafting in the FREEDOM trial underwent an off-pump procedure.^2,3

Therefore, all these considerations should be taken into account as the physician team discusses the therapeutic options (PCI and bypass grafting surgery) with diabetic patients who have multivessel coronary artery disease.

In Reply: We appreciate the comments of Dr. Saeed and colleagues. As stated in our article, given that the patients included in the FREEDOM trial represent a select group with diabetes and multivessel coronary artery disease, they may not represent all patients encountered in a real-world setting. We highlighted that only 10% of the patients screened were included for randomization, which limits the generalizability of the results. Also, the overall patient population may not be at high risk, as evidenced by low mean EuroSCORE and SYNTAX scores and by the low proportion of patients with ejection fractions less than 40%. However, patients with left main coronary artery disease (even without diabetes) have been shown to have better outcomes with coronary artery bypass grafting than with PCI, although a head-to-head trial in a diabetic subgroup is currently not available.^1,2 In addition, it is important to realize that the FREEDOM trial deals with stable angina; therefore, the results may not extend to patients with acute coronary syndrome wherein primary PCI remains the most feasible option in most cases.

Diabetes mellitus is independently associated with complex, accelerated, and multifocal coronary artery disease. Therefore, outcomes after revascularization (with bypass grafting or PCI) are worse in diabetic patients than in those without diabetes. However, this association does not prove the superiority of PCI over bypass grafting.

As we stated in our paper, the FREEDOM trial did not clearly define the strategy for arterial grafts in patients undergoing bypass grafting. The mean number of coronary lesions in the bypass grafting group was high (mean = 5.74), but the average number of grafts used was only 2.9, and data were not provided on the use of sequential grafting and multiple arterial conduits. Lastly, it is true that the FREEDOM trial had relatively fewer patients (18.5%) that underwent off-pump bypass grafting surgery; however, this approach has never been shown to be superior in large randomized trials.^3,4

In conclusion, no randomized trial should replace clinical judgment to define the targeted revascularization strategy for an individual patient. Rather, results from the FREEDOM trial should help support clinical decision-making in the context of the patient and the institution.

In Reply: We appreciate the comments of Dr. Saeed and colleagues. As stated in our article, given that the patients included in the FREEDOM trial represent a select group with diabetes and multivessel coronary artery disease, they may not represent all patients encountered in a real-world setting. We highlighted that only 10% of the patients screened were included for randomization, which limits the generalizability of the results. Also, the overall patient population may not be at high risk, as evidenced by low mean EuroSCORE and SYNTAX scores and by the low proportion of patients with ejection fractions less than 40%. However, patients with left main coronary artery disease (even without diabetes) have been shown to have better outcomes with coronary artery bypass grafting than with PCI, although a head-to-head trial in a diabetic subgroup is currently not available.^1,2 In addition, it is important to realize that the FREEDOM trial deals with stable angina; therefore, the results may not extend to patients with acute coronary syndrome wherein primary PCI remains the most feasible option in most cases.

Diabetes mellitus is independently associated with complex, accelerated, and multifocal coronary artery disease. Therefore, outcomes after revascularization (with bypass grafting or PCI) are worse in diabetic patients than in those without diabetes. However, this association does not prove the superiority of PCI over bypass grafting.

As we stated in our paper, the FREEDOM trial did not clearly define the strategy for arterial grafts in patients undergoing bypass grafting. The mean number of coronary lesions in the bypass grafting group was high (mean = 5.74), but the average number of grafts used was only 2.9, and data were not provided on the use of sequential grafting and multiple arterial conduits. Lastly, it is true that the FREEDOM trial had relatively fewer patients (18.5%) that underwent off-pump bypass grafting surgery; however, this approach has never been shown to be superior in large randomized trials.^3,4

In conclusion, no randomized trial should replace clinical judgment to define the targeted revascularization strategy for an individual patient. Rather, results from the FREEDOM trial should help support clinical decision-making in the context of the patient and the institution.

In Reply: We appreciate the comments of Dr. Saeed and colleagues. As stated in our article, given that the patients included in the FREEDOM trial represent a select group with diabetes and multivessel coronary artery disease, they may not represent all patients encountered in a real-world setting. We highlighted that only 10% of the patients screened were included for randomization, which limits the generalizability of the results. Also, the overall patient population may not be at high risk, as evidenced by low mean EuroSCORE and SYNTAX scores and by the low proportion of patients with ejection fractions less than 40%. However, patients with left main coronary artery disease (even without diabetes) have been shown to have better outcomes with coronary artery bypass grafting than with PCI, although a head-to-head trial in a diabetic subgroup is currently not available.^1,2 In addition, it is important to realize that the FREEDOM trial deals with stable angina; therefore, the results may not extend to patients with acute coronary syndrome wherein primary PCI remains the most feasible option in most cases.

Diabetes mellitus is independently associated with complex, accelerated, and multifocal coronary artery disease. Therefore, outcomes after revascularization (with bypass grafting or PCI) are worse in diabetic patients than in those without diabetes. However, this association does not prove the superiority of PCI over bypass grafting.

As we stated in our paper, the FREEDOM trial did not clearly define the strategy for arterial grafts in patients undergoing bypass grafting. The mean number of coronary lesions in the bypass grafting group was high (mean = 5.74), but the average number of grafts used was only 2.9, and data were not provided on the use of sequential grafting and multiple arterial conduits. Lastly, it is true that the FREEDOM trial had relatively fewer patients (18.5%) that underwent off-pump bypass grafting surgery; however, this approach has never been shown to be superior in large randomized trials.^3,4

In conclusion, no randomized trial should replace clinical judgment to define the targeted revascularization strategy for an individual patient. Rather, results from the FREEDOM trial should help support clinical decision-making in the context of the patient and the institution.

To the Editor: The July 2013 Cleveland Clinic Journal of Medicine includes timely articles addressing the problems of electronic health records (EHRs). At least to this reader, there is little that is surprising in the observations.

A common inside joke among programmers, sometimes displayed at one’s cubicle, is: “Fast, good, or cheap (pick two).” In other words, there is always a compromise to be had between a good product and one that is punched out on a given timetable and inexpensive. Economists call this the “second best.”

Any truly great software product accomplishes three goals. First, it allows the user to do everything previously doable at least as well or as easily as before. Second, it eliminates drudgery. And third, ideally, it provides new functionality, which previously was difficult or impossible to accomplish or to afford.

The reality is that much software is sold on the basis of the third goal, whereas goal number 1 and sometimes goal number 2 get short shrift. And for EHRs in particular, it is a fallacy for physicians to think that EHRs were brought out primarily for their benefit rather than for the benefit of the front office. This was all the more true a decade ago, when very few physicians were employed by hospitals. Thus, if the physician’s workload was increased because of the hospital’s choice of EHR, the hospital felt no financial pain. With greater reliance on an employment model, we can hope that hospitals will recognize that physicians should not be turned into very expensive secretaries.

To the Editor: The July 2013 Cleveland Clinic Journal of Medicine includes timely articles addressing the problems of electronic health records (EHRs). At least to this reader, there is little that is surprising in the observations.

A common inside joke among programmers, sometimes displayed at one’s cubicle, is: “Fast, good, or cheap (pick two).” In other words, there is always a compromise to be had between a good product and one that is punched out on a given timetable and inexpensive. Economists call this the “second best.”

Any truly great software product accomplishes three goals. First, it allows the user to do everything previously doable at least as well or as easily as before. Second, it eliminates drudgery. And third, ideally, it provides new functionality, which previously was difficult or impossible to accomplish or to afford.

The reality is that much software is sold on the basis of the third goal, whereas goal number 1 and sometimes goal number 2 get short shrift. And for EHRs in particular, it is a fallacy for physicians to think that EHRs were brought out primarily for their benefit rather than for the benefit of the front office. This was all the more true a decade ago, when very few physicians were employed by hospitals. Thus, if the physician’s workload was increased because of the hospital’s choice of EHR, the hospital felt no financial pain. With greater reliance on an employment model, we can hope that hospitals will recognize that physicians should not be turned into very expensive secretaries.

To the Editor: The July 2013 Cleveland Clinic Journal of Medicine includes timely articles addressing the problems of electronic health records (EHRs). At least to this reader, there is little that is surprising in the observations.

A common inside joke among programmers, sometimes displayed at one’s cubicle, is: “Fast, good, or cheap (pick two).” In other words, there is always a compromise to be had between a good product and one that is punched out on a given timetable and inexpensive. Economists call this the “second best.”

Any truly great software product accomplishes three goals. First, it allows the user to do everything previously doable at least as well or as easily as before. Second, it eliminates drudgery. And third, ideally, it provides new functionality, which previously was difficult or impossible to accomplish or to afford.

The reality is that much software is sold on the basis of the third goal, whereas goal number 1 and sometimes goal number 2 get short shrift. And for EHRs in particular, it is a fallacy for physicians to think that EHRs were brought out primarily for their benefit rather than for the benefit of the front office. This was all the more true a decade ago, when very few physicians were employed by hospitals. Thus, if the physician’s workload was increased because of the hospital’s choice of EHR, the hospital felt no financial pain. With greater reliance on an employment model, we can hope that hospitals will recognize that physicians should not be turned into very expensive secretaries.

Research on symptom management and monitoring of health-related quality of life (HRQOL) among cancer patients has typically focused on the active treatment phase.^1-7 More recently, greater attention has been given to the psychosocial needs and follow-up care plans for survivors.⁸ Several technology-assisted symptom/HRQOL monitoring systems with routine assessments have been shown to be easy to use,^1,3,5,9-16 readily accepted by patients,^{3,9,11,14,15,17,18} helpful in communication between patients and providers, ^3,9,11,13,15 and a means of overcoming numerous barriers to conducting routine assessments.^16,19-23 Real-time clinician feedback at the point-of-care appears to be a crucial component of these systems, giving patients and providers a systematic way of discussing symptoms and aspects of HRQOL that are often addressed only informally or not at all.

To date, 6 randomized controlled trials (RCTs) have assessed the impact of technology-assisted interventions among cancer patients.^6,23-27 There was significant variability across these studies, including differing sample sizes, number of intervention contacts, tumor site (eg, breast, lung, colon), outcomes assessed (eg, symptom distress, communication, and HRQOL), and types of technology used (eg, touch-screen computers, telephone systems). The methodological differences make it difficult to compare these studies, although a common thread was that patients found the systems easy to use and they generally perceived the systems as beneficial.^6,23-27 

Despite the positive response from participants, only 2 of the 6 RCTs demonstrated positive outcomes for the intervention over the control group.^23,25 In a study of 286 cancer patients and 28 oncologists, Velikova et al (2004) found that both the intervention and the attentioncontrol groups had better HRQOL than the control group over a 6-month period.²³ Among the intervention patients, the HRQOL improvement was related to clear use of the HRQOL data by physicians, and to physician/ patient discussion of pain and role function. A positive effect on emotional well-being was associated with feedback of the data to physicians. However, there were no significant differences between the intervention and attention-control groups.

Research on symptom management and monitoring of health-related quality of life (HRQOL) among cancer patients has typically focused on the active treatment phase.^1-7 More recently, greater attention has been given to the psychosocial needs and follow-up care plans for survivors.⁸ Several technology-assisted symptom/HRQOL monitoring systems with routine assessments have been shown to be easy to use,^1,3,5,9-16 readily accepted by patients,^{3,9,11,14,15,17,18} helpful in communication between patients and providers, ^3,9,11,13,15 and a means of overcoming numerous barriers to conducting routine assessments.^16,19-23 Real-time clinician feedback at the point-of-care appears to be a crucial component of these systems, giving patients and providers a systematic way of discussing symptoms and aspects of HRQOL that are often addressed only informally or not at all.

To date, 6 randomized controlled trials (RCTs) have assessed the impact of technology-assisted interventions among cancer patients.^6,23-27 There was significant variability across these studies, including differing sample sizes, number of intervention contacts, tumor site (eg, breast, lung, colon), outcomes assessed (eg, symptom distress, communication, and HRQOL), and types of technology used (eg, touch-screen computers, telephone systems). The methodological differences make it difficult to compare these studies, although a common thread was that patients found the systems easy to use and they generally perceived the systems as beneficial.^6,23-27 

Despite the positive response from participants, only 2 of the 6 RCTs demonstrated positive outcomes for the intervention over the control group.^23,25 In a study of 286 cancer patients and 28 oncologists, Velikova et al (2004) found that both the intervention and the attentioncontrol groups had better HRQOL than the control group over a 6-month period.²³ Among the intervention patients, the HRQOL improvement was related to clear use of the HRQOL data by physicians, and to physician/ patient discussion of pain and role function. A positive effect on emotional well-being was associated with feedback of the data to physicians. However, there were no significant differences between the intervention and attention-control groups.

Research on symptom management and monitoring of health-related quality of life (HRQOL) among cancer patients has typically focused on the active treatment phase.^1-7 More recently, greater attention has been given to the psychosocial needs and follow-up care plans for survivors.⁸ Several technology-assisted symptom/HRQOL monitoring systems with routine assessments have been shown to be easy to use,^1,3,5,9-16 readily accepted by patients,^{3,9,11,14,15,17,18} helpful in communication between patients and providers, ^3,9,11,13,15 and a means of overcoming numerous barriers to conducting routine assessments.^16,19-23 Real-time clinician feedback at the point-of-care appears to be a crucial component of these systems, giving patients and providers a systematic way of discussing symptoms and aspects of HRQOL that are often addressed only informally or not at all.

To date, 6 randomized controlled trials (RCTs) have assessed the impact of technology-assisted interventions among cancer patients.^6,23-27 There was significant variability across these studies, including differing sample sizes, number of intervention contacts, tumor site (eg, breast, lung, colon), outcomes assessed (eg, symptom distress, communication, and HRQOL), and types of technology used (eg, touch-screen computers, telephone systems). The methodological differences make it difficult to compare these studies, although a common thread was that patients found the systems easy to use and they generally perceived the systems as beneficial.^6,23-27 

Despite the positive response from participants, only 2 of the 6 RCTs demonstrated positive outcomes for the intervention over the control group.^23,25 In a study of 286 cancer patients and 28 oncologists, Velikova et al (2004) found that both the intervention and the attentioncontrol groups had better HRQOL than the control group over a 6-month period.²³ Among the intervention patients, the HRQOL improvement was related to clear use of the HRQOL data by physicians, and to physician/ patient discussion of pain and role function. A positive effect on emotional well-being was associated with feedback of the data to physicians. However, there were no significant differences between the intervention and attention-control groups.

Background Patients with late-stage cancer are living longer, making it important to understand factors that contribute to maintaining quality of life (QOL) and completing advanced illness behaviors (eg, advance directives).

Objective To examine whether illness perceptions—the cognitive beliefs that patients form about their cancer—may be more important guides to adjustment than clinical characteristics of the cancer.

Methods In a cross-sectional study, 105 female patients diagnosed with stage III (n 66) or IV (n 39) breast (n 44), gynecological (n 38), or lung (n 23) cancer completed self-report measures of illness perceptions, QOL, and advanced illness behaviors. Clinical data was obtained from medical records.

Results Despite modest associations, patients’ beliefs about the cancer were clearly unique from the clinical characteristics of the cancer. Illness perception variables accounted for a large portion of the variance (PS .01) for QOL and advanced illness behaviors, whereas clinical characteristics did not. QOL scores were predicted by patients’ reports of experiencing more cancer related symptoms (ie, illness identity), believing that their cancer is central to their self-identity, and higher income. Higher completion of advanced illness behaviors was predicted by higher income, the cancer being recurrent, and participants perceiving their cancer as more severe but also more understandable.

Limitations This study was limited by a cross-sectional design, small sample size, and focus on female patients.

Conclusion Addressing patients’ beliefs about their cancer diagnosis may provide important targets for intervention to improve QOL and illness behaviors in patients with late-stage cancer.

Click on the PDF icon at the top of this introduction to read the full article.

Background Patients with late-stage cancer are living longer, making it important to understand factors that contribute to maintaining quality of life (QOL) and completing advanced illness behaviors (eg, advance directives).

Objective To examine whether illness perceptions—the cognitive beliefs that patients form about their cancer—may be more important guides to adjustment than clinical characteristics of the cancer.

Methods In a cross-sectional study, 105 female patients diagnosed with stage III (n 66) or IV (n 39) breast (n 44), gynecological (n 38), or lung (n 23) cancer completed self-report measures of illness perceptions, QOL, and advanced illness behaviors. Clinical data was obtained from medical records.

Results Despite modest associations, patients’ beliefs about the cancer were clearly unique from the clinical characteristics of the cancer. Illness perception variables accounted for a large portion of the variance (PS .01) for QOL and advanced illness behaviors, whereas clinical characteristics did not. QOL scores were predicted by patients’ reports of experiencing more cancer related symptoms (ie, illness identity), believing that their cancer is central to their self-identity, and higher income. Higher completion of advanced illness behaviors was predicted by higher income, the cancer being recurrent, and participants perceiving their cancer as more severe but also more understandable.

Limitations This study was limited by a cross-sectional design, small sample size, and focus on female patients.

Conclusion Addressing patients’ beliefs about their cancer diagnosis may provide important targets for intervention to improve QOL and illness behaviors in patients with late-stage cancer.

Click on the PDF icon at the top of this introduction to read the full article.

Background Patients with late-stage cancer are living longer, making it important to understand factors that contribute to maintaining quality of life (QOL) and completing advanced illness behaviors (eg, advance directives).

Objective To examine whether illness perceptions—the cognitive beliefs that patients form about their cancer—may be more important guides to adjustment than clinical characteristics of the cancer.

Methods In a cross-sectional study, 105 female patients diagnosed with stage III (n 66) or IV (n 39) breast (n 44), gynecological (n 38), or lung (n 23) cancer completed self-report measures of illness perceptions, QOL, and advanced illness behaviors. Clinical data was obtained from medical records.

Results Despite modest associations, patients’ beliefs about the cancer were clearly unique from the clinical characteristics of the cancer. Illness perception variables accounted for a large portion of the variance (PS .01) for QOL and advanced illness behaviors, whereas clinical characteristics did not. QOL scores were predicted by patients’ reports of experiencing more cancer related symptoms (ie, illness identity), believing that their cancer is central to their self-identity, and higher income. Higher completion of advanced illness behaviors was predicted by higher income, the cancer being recurrent, and participants perceiving their cancer as more severe but also more understandable.

Limitations This study was limited by a cross-sectional design, small sample size, and focus on female patients.

Conclusion Addressing patients’ beliefs about their cancer diagnosis may provide important targets for intervention to improve QOL and illness behaviors in patients with late-stage cancer.

Click on the PDF icon at the top of this introduction to read the full article.