AI 中文总结
该研究将高效响应自适应随机化设计扩展至多臂试验的优先复合终点，通过结合序贯Hájek投影与鞅技术，在模拟中较单一终点设计更高效分配至优效治疗，且保持I类错误与效能。
AI 中文摘要
高效随机自适应设计可实现任意预先指定目标的分配比例的最小可能方差，已从两臂扩展至多臂，但两种版本均针对单一响应。确证性试验越来越依赖多个优先终点，通常是疗效优先于安全性，这些终点无法简化为单一汇总指标而不丢失信息。本文将该高效随机自适应设计扩展至由广义成对比较的净治疗获益驱动的目标，允许任意数量的臂和混合类型的终点，包括删失的时间-事件结局。结合针对净获益的序贯Hájek投影与原设计所用的鞅技术，建立了分配比例的强一致性、重对数律及渐近正态性，且该设计在跟踪净获益平滑函数的设计类别中达到半参数效率界。在针对三臂III期黑色素瘤试验校准的模拟中，与单一终点驱动的设计相比，所提设计更高效地将分配集中于更优治疗，同时保持I类错误和检验效能。对该试验的重新设计展示了其实际益处，并结合当前确证性试验自适应设计的监管思路对该方法进行了讨论。
英文摘要
The efficient randomized-adaptive design attains the minimal possible variance of the allocation proportion for any pre-specified target and has been extended from two to several treatment arms, but both versions target a single response. Confirmatory trials increasingly rely on several prioritized endpoints, typically efficacy followed by safety, that cannot be reduced to one summary without losing information. The efficient randomized-adaptive design is extended here to targets driven by the net treatment benefit of generalized pairwise comparisons, allowing any number of arms and endpoints of mixed type, including censored time-to-event outcomes. Strong consistency, a law of the iterated logarithm, and asymptotic normality of the allocation proportions are established by combining a sequential Hájek projection for the net benefit with the martingale technique used for the original design, and the design is shown to attain the semiparametric efficiency bound within the class of designs that track a smooth function of the net benefit. In simulations calibrated to a three-arm phase III melanoma trial, the proposed design concentrates allocation on the superior treatment more efficiently than designs driven by a single endpoint, while preserving type I error and power. A redesign of the trial illustrates the practical benefit, and the approach is discussed in relation to current regulatory thinking on adaptive designs for confirmatory trials.
Comments46 pages, 3 figures, 6 Tables
