The George Institute, Sydney, Australia.
Stat Med. 2011 Jun 15;30(13):1541-54. doi: 10.1002/sim.4179. Epub 2011 Mar 22.
This article has been motivated by an ongoing international adaptive confirmatory trial. At the interim analysis of this two-stage trial, none, one or two active treatment regimens are selected for further study in the second stage. A combination test approach is used in this practical setting with an extension of the theory to unbalanced randomization. We show that a combination test with suitable weights can still preserve the overall Type I error rate provided that the test statistic is chosen appropriately and the unpooled Z-test for proportions is not used. The accuracy of stagewise p-values is also discussed in a more general framework. Monte Carlo simulations confirm the validity of the approach retained and evaluate the necessary sample size. Additional issues addressed during the design of the trial are also examined such as multiplicity due to testing hypotheses on key secondary endpoints, a non-inferiority comparison to an active treatment and covariate adjusted analyses for various types of outcome.
这篇文章的灵感来自于一项正在进行的国际适应性确证试验。在这项两阶段试验的中期分析中，将选择一种、两种或三种活性治疗方案进入第二阶段的进一步研究。在这种实际情况下使用组合检验方法，并将理论扩展到不平衡随机化。我们表明，只要选择合适的检验统计量且不使用未合并的比例 Z 检验，具有适当权重的组合检验仍可保持总体Ⅰ类错误率。还在更一般的框架中讨论了分阶段 p 值的准确性。蒙特卡罗模拟验证了所保留方法的有效性，并评估了所需的样本量。还检查了试验设计过程中的其他问题，例如对关键次要终点假设检验的多重性、与活性治疗的非劣效性比较以及各种类型结局的协变量调整分析。
