In learning-phase clinical trials in drug development, adaptive designs can be efficient and highly informative when used appropriately. In this article, we extend the multiple comparison procedures with modeling techniques (MCP-Mod) procedure with generalized multiple contrast tests (GMCTs) to two-stage adaptive designs for establishing proof-of-concept. The results of an interim analysis of first-stage data are used to adapt the candidate dose-response models and the dosages studied in the second stage. GMCTs are used in both stages to obtain stage-wise p-values, which are then combined to determine an overall p-value. An alternative approach is also considered that combines the t-statistics across stages, employing the conditional rejection probability (CRP) principle to preserve the Type I error probability. Simulation studies demonstrate that the adaptive designs are advantageous compared to the corresponding tests in a non-adaptive design if the selection of the candidate set of dose-response models is not well informed by evidence from preclinical and early-phase studies.
翻译:在药物开发的学习阶段临床试验中,适应性设计在适当使用时可能是高效的,而且信息量很高。在本条中,我们将与模型技术(MCP-Mod)程序(MCP-Mod)的多重比较程序与通用的多对比测试(GMCTs)程序(MMCTs)的多重比较程序扩大到两阶段的适应性设计,以建立概念验证。第一阶段数据的临时分析结果用于调整候选剂量反应模型和第二阶段研究的剂量。GMCT在两个阶段都用于获得分阶段的P-价值,然后将其合并来确定总体P-价值。还考虑一种替代方法,即采用有条件拒绝概率原则(CRP)来保持类型I的误差概率,采用有条件拒绝概率原则(CRP)来保持类型I的误差概率。模拟研究表明,如果选择一组候选剂量反应模型时没有从初步和早期阶段研究中获得充分的证据,那么适应性设计与非适应性设计的相应测试相比,适应性设计是有利的。