  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.
