The win ratio is increasingly used in randomized trials due to its intuitive clinical interpretation, ability to incorporate the relative importance of composite endpoints, and its capacity for combining different types of outcomes (e.g. time-to-event, binary, counts, etc.) to be combined. There are open questions, however, about how to implement adaptive design approaches when the primary endpoint is a win ratio, including in group sequential designs. A key requirement allowing for straightforward application of classical group sequential methods is the independence of incremental interim test statistics. This paper derives the covariance structure of incremental U-statistics that evaluate the win ratio under its asymptotic distribution. The derived covariance shows that the independent increments assumption holds for the asymptotic distribution of U-statistics that test the win ratio. Simulations confirm that traditional $α$-spending preserves Type I error across interim looks. A retrospective look at the IN.PACT SFA clinical trial data illustrates the potential for stopping early in a group sequential design using the win ratio. We have demonstrated that straightforward use of Lan-De\uppercase{M}ets $α$-spending is possible for randomized trials involving the win ratio under certain common conditions. Thus, existing software capable of computing traditional group sequential boundaries can be employed.

翻译：胜率因其直观的临床解释能力、能够纳入复合终点的相对重要性，以及整合不同类型结局（如时间‑事件、二分类、计数等）的能力，在随机化试验中的应用日益广泛。然而，当主要终点为胜率时，包括在组序贯设计中，如何实施适应性设计方法仍存在开放性问题。能够直接应用经典组序贯方法的一个关键要求是增量期中检验统计量的独立性。本文推导了在渐近分布下评估胜率的增量U‑统计量的协方差结构。所得协方差表明，对于检验胜率的U‑统计量的渐近分布，独立增量假设成立。模拟结果证实，传统的$α$消耗函数能在多次期中分析中维持I类错误。对IN.PACT SFA临床试验数据的回顾性分析展示了在组序贯设计中使用胜率实现早期终止的可能性。我们证明，在某些常见条件下，涉及胜率的随机化试验可以直接使用Lan‑De\uppercase{M}ets $α$消耗函数。因此，能够计算传统组序贯边界的现有软件均可被采用。