Effects of patient-reported outcome assessment order.

BACKGROUND: In clinical trials and clinical practice, patient-reported outcomes are almost always assessed using multiple patient-reported outcome measures at the same time. This raises concerns about whether patient responses are affected by the order in which the patient-reported outcome measures are administered. METHODS: This questionnaire-based study of order effects included adult cancer patients from five cancer centers. Patients were randomly assigned to complete questionnaires via paper booklets, interactive voice response system, or tablet web survey. Linear Analogue Self-Assessment, Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events, and Patient-Reported Outcomes Measurement Information System assessment tools were each used to measure general health, physical function, social function, emotional distress/anxiety, emotional distress/depression, fatigue, sleep, and pain. The order in which the three tools, and domains within tools, were presented to patients was randomized. Rates of missing data, scale scores, and Cronbach's alpha coefficients were compared by the order in which they were assessed. Analyses included Cochran-Armitage trend tests and mixed models adjusted for performance score, age, sex, cancer type, and curative intent. RESULTS: A total of 1830 patients provided baseline patient-reported outcome assessments. There were no significant trends in rates of missing values by whether a scale was assessed earlier or later. The largest order effect for scale scores was due to a large mean score at one assessment time point. The largest difference in Cronbach's alpha between the versions for the Patient-Reported Outcomes Measurement Information System scales was 0.106. CONCLUSION: The well-being of a cancer patient has many different aspects such as pain, fatigue, depression, and anxiety. These are assessed using a variety of surveys often collected at the same time. This study shows that the order in which the different aspects are collected from the patient is not important.

Caregivers of patients with cancer fatigue: a high level of symptom burden.

Fatigue is the problematic symptom identified by patients with cancer. However, fatigue has not been widely examined in caregivers of patients with cancer. In this study, 131 caregivers of patients diagnosed with advanced stage cancer and actively receiving radiotherapy reported experiencing the most difficulties with fatigue (mean 46.9; on a 0-100 scale, with a 10-point difference having clinical meaning) at baseline and at a 6-month follow-up (mean 48.3). This is in sharp contrast to other domains of quality of life and functioning being rated in the 60s, 70s and 80s by the caregivers of patients with cancer. Given the level of fatigue reported by the caregivers of patients with cancer, if confirmed by other investigators in larger and more diverse samples, interventions targeting caregiver fatigue should be explored.

Assessment of the accuracy of the Gail model in women with atypical hyperplasia.

PURPOSE: An accurate estimate of a woman's breast cancer risk is essential for optimal patient counseling and management. Women with biopsy-confirmed atypical hyperplasia of the breast (atypia) are at high risk for breast cancer. The Gail model is widely used in these women, but has not been validated in them. PATIENTS AND METHODS: Women with atypia were identified from the Mayo Benign Breast Disease (BBD) cohort (1967 to 1991). Their risk factors for breast cancer were obtained, and the Gail model was used to predict 5-year-and follow-up-specific risks for each woman. The predicted and observed numbers of breast cancers were compared, and the concordance between individual risk levels and outcomes was computed. RESULTS: Of the 9,376 women in the BBD cohort, 331 women had atypia (3.5%). At a mean follow-up of 13.7 years, 58 of 331 (17.5%) patients had developed invasive breast cancer, 1.66 times more than the 34.9 predicted by the Gail model (95% CI, 1.29 to 2.15; P < .001). For individual women, the concordance between predicted and observed outcomes was low, with a concordance statistic of 0.50 (95% CI, 0.44 to 0.55). CONCLUSION: The Gail model significantly underestimates the risk of breast cancer in women with atypia. Its ability to discriminate women with atypia into those who did and did not develop breast cancer is limited. Health care professionals should be cautious when using the Gail model to counsel individual patients with atypia.

Patient, clinician, and population perspectives on determining the clinical significance of quality-of-life scores.

Despite the success of screening and treatment of major cancers in the United States, cancer remains a chronic condition dominated by symptoms and treatment-related adverse effects. Because of these often taxing symptoms and adverse effects, numerous studies have been conducted to document the effects of cancer diagnosis and treatment on the quality of life (QOL) of patients. But there has been limited investigation of the clinical significance of QOL scores. This article examines the clinical significance of QOL scores from 3 key perspectives: patients, clinicians, and the general population. The patient's perspective includes an evaluation of the size of difference in scores that individual patients can detect and regard as important. The clinician perspective relies on whether the clinician believes the patient's condition has stayed the same vs whether changes have occurred (decline or improvement). The population perspective represents a democratic process in which the input or votes of a community of people are used to determine if health state A is clinically significantly different from health state B. While many clinicians and researchers advocate for QOL to be defined from the patient's perspective, the reality is that QOL is often defined by clinicians in terms of observable events. Even when measures are used in which the patient identifies how his or her life has been affected, it is often the clinician who interprets the clinical importance of this information. The clinician's perspective has value in framing an experience within the context of what is usual for a group of individuals, and the population perspective provides inputs as to how society may use limited resources. However, we conclude that a more prominent role for the patient's QOL perspective is needed.

Quality of life measurements: a soft outcome--or is it?

In oncology research, quality of life (QOL) has been identified as the second most important outcome, with survival being the most important. The integration of QOL assessments into clinical practice and research presents some unique challenges. QOL outcomes are sometimes perceived to be soft, as opposed to the type of outcomes that provide hard end points or factual data and can be easily defined quantitatively. The softness of QOL outcomes relative to survival and tumor response is cited as a particular barrier to implementation and interpretation of results. This article reviews the importance of QOL to clinical practice, discusses the perceived softness of QOL, and compares the roles of symptoms and QOL scores as they relate to disease progression and tumor response. Providing sound QOL data to healthcare professionals and patients is essential to enable truly informed decision-making.