Design and Analysis of Clinical Trials with Restricted Mean Survival Time

Abstract

Restricted mean survival time (RMST), a summary of survival time up to a pre-specified clinically relevant truncation time, is increasingly recognized as a measure for treatment effect in recent biomedical studies with time-to-event endpoints. The difference or ratio of RMST between two groups (e.g., treatment versus control) measures the relative treatment effect concerning a gain or loss of survival time. The RMST offers greater flexibility than the hazard ratio (HR), which is often estimated from the Cox proportional hazards model under the proportional hazards (PH) assumption. Due to delayed treatment effects or other biomedical reasons, the PH assumption is often violated in oncology and cardiovascular trials, leading to biased estimation and misleading interpretations of treatment effects. Compared to HR, RMST requires no PH assumption and offers a more straightforward interpretation of treatment effects. In this dissertation, we propose novel RMST-based methodologies for clinical trials with time-to-event endpoints in three research areas including 1) individual participant data network meta-analysis, 2) inference in multi-regional clinical trials, and 3) biomarker-guided adaptive and enrichment design.