Challenges and recommendations for advancing the state-of-the-science of quality of life assessment in symptom management trials

Abstract

Major findings are presented from a workshop on Quality of Life Assessment in Cancer Symptom Management Trials, sponsored by the National Cancer Institute. Data-driven research reports focused on 3 topics, 1) the rationale and utility of health-related quality of life (HRQOL) assessment, 2) conceptual models, and 3) measurement and design issues. Recommendations for including HRQOL assessment cited the potential value of: capturing additional treatment effects (eg, fatigue + depression); describing the patient experience; predicting patient prognosis; identifying potential adverse effects; observing interactions among symptoms; calculating quality adjusted survival and cost-effectiveness; and generating new hypotheses. Recommendations for developing more fully developed conceptual models focused on maintaining clear distinctions among symptoms, function, summary measures of HRQOL, and global HRQOL assessments; identifying symptom clusters; pursuing hypotheses about whether clustering is better explained as symptom-related or as patient-related (genetic predispositions); and gaining a better understanding of the dynamic and reciprocal influences of symptoms on each other. With respect to measurement and design issues, because different HRQOL measures cover different domains with various degrees of sensitivity, there is a need to select measures that are carefully tailored to the study's hypotheses. Finally, there is a growing appreciation that trials must be powered to test for effects on secondary endpoints.