AI 中文总结
针对分层复合终点的严格胜比检验效能不足问题，提出连续加权胜比方法，通过平滑权重放宽分层限制，经模拟验证可在治疗效应集中于低优先级终点时提升检验效能。
AI 中文摘要
分层复合终点常用于各组分结局临床重要性不同的临床试验中。胜比根据预先设定的临床优先级顺序比较治疗组间的患者，具有直观的解释性。然而，严格的分层规则仅在所有较高优先级终点为持平或无信息时才使用较低优先级终点，当治疗效应主要通过较低优先级结局体现时，这可能会降低检验效能。近期基于阈值的扩展方法放宽了该分层限制，允许当较高优先级终点处于预先设定的边际范围内时，较低优先级结局可做出贡献。我们提出一种用于分层复合终点的连续加权胜比，该方法用平滑权重替代终点水平间的硬性转换，使得当较高优先级终点接近持平时，较低优先级终点可逐步做出贡献。所得估计量为两样本U统计量，我们通过Hoeffding投影推导其大样本分布，并提供一致的插件方差估计量，还通过局部备择假设和局部效率描述了调节参数的作用。所提出的类别包含严格胜比和硬阈值规则作为特例或极限情况。模拟研究表明，当治疗效应集中于较低优先级终点时，放宽严格分层可提升检验效能；但当最高优先级终点承载主要治疗信号时，可能会降低检验效能。
英文摘要
Hierarchical composite endpoints are commonly used in clinical trials when component out- comes differ in clinical importance. The win ratio compares patients across treatment groups according to a pre-specified order of clinical priority and has an intuitive interpretation. A strict hierarchical rule, however, uses a lower-priority endpoint only when all higher-priority endpoints are tied or non-informative. This may reduce power when the treatment effect is mainly ex- pressed through lower-priority outcomes. Recent threshold-based extensions relax this hierar- chy by allowing lower-priority outcomes to contribute when higher-priority outcomes are within pre-specified margins. We propose a continuous-weighted win ratio for hierarchical composite endpoints. The method replaces hard transitions between endpoint levels with smooth weights, so that a lower-priority endpoint can contribute gradually when the higher-priority endpoint is close to tied. The resulting estimator is a two-sample U-statistic. We derive its large-sample distribution using the Hoeffding projection and provide a consistent plug-in variance estimator. We also describe the role of the tuning parameter through local alternatives and local efficiency. The proposed class includes the strict win ratio and hard-threshold rules as special or limit- ing cases. Simulation studies show that relaxing the strict hierarchy can improve power when treatment effects are concentrated on lower-priority endpoints, but may reduce power when the highest-priority endpoint carries the main treatment signal.
