Shrinking Coarsened Win Ratio and Testing of Composite Endpoint

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) proposed by Pocock et al. (2012) [1] employs a hierarchical structure to combine fatal and non-fatal events by giving death information an absolute priority, which adversely affects power if the treatment effect is mainly on the non-fatal outcomes. We hereby propose the Shrinking Coarsened Win Ratio method (SCWR) that releases the strict hierarchical structure of the standard WR by adding stages with coarsened thresholds shrinking to zero. A weighted adaptive approach is developed to determine the thresholds in SCWR. This method preserves the good statistical properties of the standard WR and has a greater capacity to detect treatment effects on non-fatal events. We show that SCWR has an overall more favorable performance than WR in our simulation that addresses the influence of follow-up time, the association between events, and the treatment effect levels, as well as a case study based on the Digitalis Investigation Group clinical trial data.