Win Ratio with Multiple Thresholds for Composite Endpoints

Abstract: Composite endpoints consisting of both terminal and non-terminal events, such as death and hospitalization, are frequently used as primary endpoints in cardiovascular clinical trials. The Win Ratio method (WR) employs a hierarchical structure to combine fatal and non-fatal events by giving death information an absolute priority, which can adversely affect power if the treatment effect is mainly on the non-fatal outcomes. We hereby propose the Win Ratio with Multiple Thresholds (WR-MT) that releases the strict hierarchical structure of the standard WR by adding stages with non-zero thresholds. A weighted adaptive approach is also developed to determine the thresholds in WR-MT. This method preserves the statistical properties of the standard WR but can sometimes increase the chance to detect treatment effects on non-fatal events. We show that WR-MT has a particularly favorable performance than standard WR when the second layer has stronger signals and otherwise comparable performance in our simulations that vary the follow-up time, the correlation between events, and the treatment effect sizes. A case study based on the Digitalis Investigation Group clinical trial data is presented to further illustrate our proposed method. An R package "WRMT" that implements the proposed methodology has been developed.