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Abstract: Clinicians are being confronted with increasing amounts of health-related quality of life (HRQOL) data. Thus, there is a need for a greater understanding of the analysis and interpretation of HRQOL so that the data can be reported in an appropriate manner. The approach of the Clinical Trials Group of the National Cancer Institute of Canada emphasises the clinical meaning of the results, while avoiding complex statistical modelling. It consists of four steps: calculating the questionnaire completion rates, calculating the baseline scores, determining the individual change in scores over time for the domains specified in the trial hypothesis, and culminates in determining the proportions of patients who have reported clinically meaningful changes in scores since baseline. A rationale supporting each step is given. This approach is presented as a simple and practical aid to the analysis, interpretation and reporting of HRQOL results. [Copyright &y& Elsevier]

Introduction: The National Cancer Institute of Canada (NCIC) Clinical Trials Group (CTG) Quality of Life (QOL) Committee was initiated in 1986. Purpose: The purpose of this review is to describe the evolution of the Committee's work and to highlight key developments such as the formulation of a policy regarding health-related quality-of-life (HRQOL) assessment, the provision of guidelines to ensure completion of HRQOL data within the protocol requirements, the rationale behind the choice of HRQOL instruments, the timing of assessments and the development of data analytic methods. These developments are illustrated with examples from CTG studies. Recommendations: There is a lack of concordance between conventional toxicity data and HRQOL data and comparative studies designed to elucidate these differences are to be encouraged. Also, more studies are required to compare different analytic strategies and to determine how much missing data is acceptable, particularly in oncology studies where attrition is inevitable. [ABSTRACT FROM AUTHOR]

In this article, we provide a brief historical review of the development of patient-reported outcome measurement, analysis, and reporting in clinical trials of the National Cancer Institute of Canada Clinical Trials Group (NCIC CTG). In doing so, we examine selected lessons learned in furthering the quality of these data and their application to clinical practice. We conclude that sequential institution of key policies within the NCIC CTG and the development of a collective philosophy within the group has enabled the routine incorporation of health-related quality of life into clinical trial protocols according to robust scientific principles; that collection of quality data is possible in a variety of circumstances (although not universally so); that patient-reported data on subjective experiences is likely to be more reliable and valid than conventional toxicity information; and that simple analyses that report group trends as well as individual patient response rates are preferred.

Objectives: To propose a taxonomy of psychometrically based, health-related quality-of-life instruments related to three levels of decision-making of health care: the macro, meso and micro levels. The choice of appropriate health-related quality-of-life instruments for each level of desired decision making in various clinical settings is illustrated. A secondary objective was to describe solutions for some of the difficulties inherent in the interpretation of the results of health-related quality-of-life assessment., Design: The three main levels of clinical decision making are listed and the instruments used most frequently in cancer clinical trials are reviewed from the medical literature., Proposals: Generic and utility-based instruments are likely to be the most valuable at the macro level of decision making, whereas condition-specific, disease-specific, and situation-specific instruments are most useful for decision making at the meso and micro levels. A determination of the proportions of patients who have reached a meaningful change in health-related quality-of-life scores (eg, > or =10 for scales of 1-100) over a standard period is a rational approach to interpreting the significance of changes in scores., Conclusions: Awareness of the level of decision making that is involved in the clinical assessment of health-related quality of life can be helpful in choosing instruments that are appropriate for various clinical settings. Some of the difficulties in interpreting the meaning of changes in health-related quality-of-life scores can be overcome by comparing the proportions of patients who have achieved a preset magnitude of change.