Placebo effect‐adjusted assessment of quality of life in placebo‐controlled clinical trials

Abstract

Quality of life (QoL) has become an accepted and widely used endpoint in clinical trials. The analytical tools used for QoL evaluations in clinical trials differ from those used for the more traditional endpoints, such as response to disease, overall survival or progression-free survival. Since QoL assessments are generally performed on self-administered questionnaires, QoL endpoints are more prone to a placebo effect than traditional clinical endpoints. The placebo effect is a well-documented phenomenon in clinical trials, which has led to dramatic consequences on the clinical development of new therapeutic agents. In order to account for the placebo effect, a multivariate latent variable model is proposed, which allows for misclassification in the QoL item responses. The approach is flexible in the sense that it can be used for the analysis of a wide variety of multi-dimensional QoL instruments. For statistical inference, maximum likelihood estimates and their standard errors are obtained using a Monte Carlo EM algorithm. The approach is illustrated with analysis of data from a cardiovascular phase III clinical trial.