Quality adjusted survival analysis with repeated quality of life measures

✍ Scribed by Paul P. Glasziou; Bernard F. Cole; Richard D. Gelber; Jorgen Hilden; R. John Simes

• Publisher: John Wiley and Sons
• Year: 1998
• Tongue: English
• Weight: 161 KB
• Volume: 17
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(19980615)17:11<1215::aid-sim844>3.0.co;2-y

✦ Synopsis

One way of examining trade-offs between quantity and quality of life (QOL) is to combine them into a single measure such as quality-adjusted life year (QALY). If censoring occurs, then estimation presents some difficulties. One approach, known as Q-TWiST, is to define a series of health states, use a 'partitioned' survival analysis to calculate the average time in each state, and then weight each state according to its quality of life to calculate QALYs. Such health-state models, however, are unhelpful when the transitions between health states are unclear or if they do not adequately reflect variations in quality of life. We therefore examine an alternative analysis to be used when repeated measures of quality of life are available from individual patients in a clinical trial. The method proceeds by separating quality of life and survival, that is, dQALY/dt"S(t) Q(t), where S(t) is the survival curve, estimated from the standard Kaplan-Meier method, and Q(t) is the quality of life function, derived from individual repeated measures of quality of life. We derive single health-state (QALY) and multiple health-state (Q-TWiST) models and illustrate the approach by comparing different durations of adjuvant chemotherapy for breast cancer. 1998 John Wiley & Sons, Ltd.