Analytic difficulties in applying quality of life outcomes to clinical trials of therapy for HIV disease

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Abstract
Despite considerable enthusiasm for the concept, quality-of-life or health status outcomes are seldom employed in clinical trials. The failure of common analytic procedures to meet key requirements may have contributed to this limited acceptance. In particular, (1) results of clinical trials must be expressed in terms that clinicians, regulators, administrators, and patients find useful, (2) reasonable means of summarizing outcomes should be available a priori, (3) scale units should have real world meaning, (4) unwarranted assumptions regarding scale properties should be avoided, and (5) adequate methods for handling attrition due to death or drop-out are necessary. Our group has developed approaches to these problems. We summarize overall outcome using a weighted sum of scores for scales covering several domains and weights derived from regressions of scale scores on a reference variable. Our multistate survival analysis. an extension of standard survival analysis attempts to circumvent some of the difficulties with attrition and poor scale properties of health status/quality of life measures. Multistate survival analysis has two components, a description of survival-in-state, and significance test based on transitions-from-state. In survival-in-state analysis, we generalize the usual survival analysis to consider the proportions of participants with a health or quality status which is at least equal to that indicated by specified ordered states. In transition-from-states analysis, we generalize the Mantel-Haenszel procedure to simultaneously consider upward and downward transitions from previous health or quality state to improved or worsened states. These approaches incorporate mortality without requiring specification of a score value for death, allow reasonable handling of attrition, give results denominated in proportions or time units rather than score values, and allow assessment of net changes in status for individual participants between evaluations.