Estimation of mean quality adjusted survival time

In clinical studies, we often consider not only patients' survival time, but also their quality of life. Quality adjusted life years (QALY) is an integrated measure of medical outcome that combines a patient's quantity and quality of life. Estimation of mean QALY for a group of patients is complicated by the fact that some patients are censored. The conventional approach is to obtain the Kaplan-Meier estimate of the survival function associated with individual QALYs and then use the area under the Kaplan-Meier curve as an estimate of mean QALY. Glasziou, Simes and Gelber showed that this method is biased because censoring at the nominal time scale is informative for predicting unobserved QALYs. In this paper, we propose a methodology for consistent estimation of mean QALY. Simulation studies are conducted to investigate the relative performance of the new method and the conventional method.