Suggestions for the presentation of quality of life data from clinical trials.

Abstract

Quality of life (QOL) data is complex since it is both multidimensional and longitudinal. This complexity is compounded with its unbalanced nature through missing observations as a consequence of patient non-compliance with assessment schedules, and, for example, in cancer clinical trials data absence due to patient attrition often through death. QOL data poses difficulties for presentation and analysis and hence interpretation. This paper illustrates, using data from a randomized trial of the United Kingdom Medical Research Council Lung Cancer Working Party, a step-by-step approach to presentation of QOL data. This begins with a description of compliance and its relationship with patient attrition caused by death, to a final summary profile to indicate change over time. We recognize that no single summary statistic is likely to be able to encapsulate all the subtleties of QOL data. We stress the importance of examining data graphically before performing detailed analysis and also to facilitate interpretation in the final clinical report. Although a description of analytical methods is not the purpose of this paper, we draw attention to the need for imputing missing values and to the (multi-level) modelling approach to summarizing the data, both essential adjuncts to the less formal methods described here.