Wang Jixian
Novartis Pharma AG, Lichtstrasse 35, 4002 Basel, Switzerland.
Biom J. 2006 Aug;48(4):679-89. doi: 10.1002/bimj.200510236.
As an approach to combining the phase II dose finding trial and phase III pivotal trials, we propose a two-stage adaptive design that selects the best among several treatments in the first stage and tests significance of the selected treatment in the second stage. The approach controls the type I error defined as the probability of selecting a treatment and claiming its significance when the selected treatment is indifferent from placebo, as considered in Bischoff and Miller (2005). Our approach uses the conditional error function and allows determining the conditional type I error function for the second stage based on information observed at the first stage in a similar way to that for an ordinary adaptive design without treatment selection. We examine properties such as expected sample size and stage-2 power of this design with a given type I error and a maximum stage-2 sample size under different hypothesis configurations. We also propose a method to find the optimal conditional error function of a simple parametric form to improve the performance of the design and have derived optimal designs under some hypothesis configurations. Application of this approach is illustrated by a hypothetical example.
作为一种将II期剂量探索试验和III期关键试验相结合的方法，我们提出了一种两阶段适应性设计，该设计在第一阶段从几种治疗方法中选择最佳方法，并在第二阶段检验所选治疗方法的显著性。如比肖夫和米勒（2005年）所述，该方法控制I型错误，I型错误定义为当所选治疗方法与安慰剂无差异时选择一种治疗方法并宣称其具有显著性的概率。我们的方法使用条件误差函数，并允许基于在第一阶段观察到的信息来确定第二阶段的条件I型错误函数，其方式与没有治疗选择的普通适应性设计类似。我们在不同的假设配置下，在给定的I型错误和最大第二阶段样本量的情况下，研究了该设计的预期样本量和第二阶段功效等性质。我们还提出了一种方法来找到简单参数形式的最优条件误差函数，以提高设计的性能，并在一些假设配置下推导出了最优设计。通过一个假设示例说明了该方法的应用。
