352489Institute of Biostatistics and Clinical Research, 9185University of Münster, Muenster, Germany.
Stat Methods Med Res. 2021 Dec;30(12):2562-2581. doi: 10.1177/09622802211043262. Epub 2021 Oct 12.
Whereas the theory of confirmatory adaptive designs is well understood for uncensored data, implementation of adaptive designs in the context of survival trials remains challenging. Commonly used adaptive survival tests are based on the independent increments structure of the log-rank statistic. This implies some relevant limitations: On the one hand, essentially only the interim log-rank statistic may be used for design modifications (such as data-dependent sample size recalculation). Furthermore, the treatment arm allocation ratio in these classical methods is assumed to be constant throughout the trial period. Here, we propose an extension of the independent increments approach to adaptive survival tests that addresses some of these limitations. We present a confirmatory adaptive two-sample log-rank test that allows rejection regions and sample size recalculation rules to be based not only on the interim log-rank statistic, but also on point-wise survival rate estimates, simultaneously. In addition, the possibility is opened to adapt the treatment arm allocation ratio after each interim analysis in a data-dependent way. The ability to include point-wise survival rate estimators in the rejection region of a test for comparing survival curves might be attractive, e.g., for seamless phase II/III designs. Data-dependent adaptation of the allocation ratio could be helpful in multi-arm trials in order to successively steer recruitment into the study arms with the greatest chances of success. The methodology is motivated by the LOGGIC Europe Trial from pediatric oncology. Distributional properties are derived using martingale techniques in the large sample limit. Small sample properties are studied by simulation.
虽然确证性适应性设计的理论对于未删失数据已经得到很好的理解，但在生存试验的背景下实施适应性设计仍然具有挑战性。常用的适应性生存检验基于对数秩统计量的独立增量结构。这意味着存在一些相关的局限性：一方面，基本上只能使用中期对数秩统计量来进行设计修改（例如，基于数据的样本量重新计算）。此外，这些经典方法中的处理臂分配比在整个试验期间被假定为常数。在这里，我们提出了一种对适应性生存检验的独立增量方法的扩展，该方法解决了其中的一些局限性。我们提出了一种确证性适应性两样本对数秩检验，允许拒绝区域和样本量重新计算规则不仅基于中期对数秩统计量，而且同时基于逐点生存率估计。此外，还可以在每次中期分析后以数据依赖的方式自适应地调整处理臂分配比。在比较生存曲线的检验中，将逐点生存率估计值纳入拒绝区域的能力可能具有吸引力，例如，用于无缝的 II/III 期设计。在多臂试验中，分配比的自适应可以帮助将招募逐步引导到成功率最高的研究臂。该方法学的动机来自儿科肿瘤学的 LOGGIC Europe 试验。在大样本极限下，使用鞅技术推导分布性质。通过模拟研究小样本性质。
