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Comparing Treatments Using Quality-Adjusted Survival: The Q-TWiST Method

1995; Taylor & Francis; Volume: 49; Issue: 2 Linguagem: Inglês

10.1080/00031305.1995.10476135

1537-2731

Richard D. Gelber, Bernard F. Cole, Shari Gelber, Aron Goldhirsch,

Advanced Causal Inference Techniques

Abstract The quality of life of patients is an important component of evaluation of therapies. We present an overview of a statistical method called Q-TWiST (Quality-Adjusted Time Without Symptoms and Toxicity) which incorporates quality-of-life considerations into treatment comparisons. Multivariate censored survival data are used to partition the overall survival time into periods of time spent in a set of progressive clinical health states which may differ in quality of life. Mean health state durations, restricted to the follow-up limits of the clinical trial, are derived from the data and combined with value weights to estimate quality-adjusted survival. The methodology emphasizes treatment comparisons based on threshold utility analyses that highlight trade-offs between different health state durations; it is not intended to provide a unique result combining quality and quantity of life. We also describe three recent extensions of the methodology: covariates can be included using proportional hazards and accelerated failure time regression models, restricted estimates can be projected beyond follow-up limits using parametric models, and meta-analyses can be performed incorporating quality-of-life dimensions. The basic methods are demonstrated in an analysis of data from a clinical trial comparing long versus short duration adjuvant chemotherapy regimens for the treatment of breast cancer. The clinical health states are defined by the following three outcomes: (1) end of treatment toxicity, (2) disease recurrence, and (3) death. The results allow one to evaluate the trade-off between the increased toxic effects and the increased recurrence-free interval associated with the long duration treatment.