Efficient statistical analysis of trial designs: win ratio and related approaches for composite outcomes

In randomized controlled clinical trials, composite outcomes are often used to study treatment effects. This approach is popular because it increases the number of observed events, enhancing statistical power while reducing the required patient sample size. However, composite outcomes do not provide insight into the effect of individual endpoints. This becomes particularly relevant when mortality is combined with less critical but clinically relevant endpoints or when the clinical importance of individual endpoints varies significantly. As a result, interpreting composite outcomes can be challenging.

This narrative review introduces the win ratio (WR), a method for prioritizing individual endpoints within a composite outcome. The WR offers an alternative to composite outcomes by considering the clinical importance of each component and prioritizing the most critical endpoint, such as death, over less significant events.

Despite the popularity of the WR among cardiovascular trialists, this approach has not been extensively used in other areas of clinical research. We contend, that perioperative and periprocedural researchers could consider the WR and related approaches when the outcomes of interest are not of similar clinical importance. To this end, understanding the benefits and limitations of the WR will be essential to exploit its benefits, while avoiding potential misuses of the technique.