In 2012, Pocock and colleagues proposed the win ratio (WR) statistics for the analysis of controlled clinical trials with a composite endpoint. This approach takes into account clinical priorities among multiple components of the composite. Subjects in the test group are compared with subjects in the control group in all possible pairwise comparisons. The WR is calculated as the number of “winners” divided by the number of “losers” in the test group. The WR statistic is intuitive; however, it is not clear how it should be applied when the number of ties is substantial. To handle the ties, Dong et al. recently introduced the win odds (WO) statistics, which assigns 50% of the ties to both the numerator and the denominator of the WR statistic. In this work, we discuss the WO in the design of a Non-Inferiority (NI) trial with a composite endpoint, as ties in NI trials may reflect comparable treatment effect and the number of ties may be substantial. We extend the large sample inference for the WR to the WO and demonstrate the utility of the WO in the design of NI trials through simulations.

2012 年，Pocock 及其同事提出了胜率 (WR) 统计数据，用于分析具有复合终点的对照临床试验。这种方法考虑了复合材料的多个组成部分之间的临床优先级。在所有可能的成对比较中，将测试组中的受试者与对照组中的受试者进行比较。WR 的计算方法是测试组中“获胜者”的数量除以“失败者”的数量。WR 统计数据很直观；然而，当联系的数量很大时，它应该如何应用并不清楚。为了处理这些关系，董等人。最近推出了获胜赔率 (WO) 统计数据，该统计数据将 50% 的关系分配给 WR 统计数据的分子和分母。在这项工作中，我们讨论了具有复合终点的非劣效性 (NI) 试验设计中的 WO，因为 NI 试验中的联系可能反映了可比的治疗效果，而且联系的数量可能很大。我们将 WR 的大样本推断扩展到 WO，并通过模拟证明了 WO 在 NI 试验设计中的效用。