Some recommendations for multi-arm multi-stage trials.
Some recommendations for multi-arm multi-stage trials.
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DOI：
10.1177/0962280212465498
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发表时间：
2016-04
影响因子：
2.3
通讯作者：
Jaki T
中科院分区：
文献类型：
--
作者：
Wason J;Magirr D;Law M;Jaki T
多组多阶段设计可以通过在一项试验中评估多个实验组与一个共同对照来提高药物开发过程的效率。与一系列分别测试每个实验组和对照组的试验相比，这减少了所需的患者数量。通过允许多个阶段，如果实验治疗不太可能显著优于对照，则可以从研究中提前排除。以TAILoR试验为例，我们探讨了与多组多阶段试验相关的广泛的统计学问题，包括比较多组多阶段试验的不同方法;与其他试验组相比，选择对照组的分配比例;在多组多阶段试验中增加额外试验组的后果，以及在必要时如何控制I类错误率;以及修改多组多阶段设计的停止边界以考虑治疗结果中的未知变化。多组多阶段试验代表着巨大的财务投资，因此仔细考虑其设计对于确保效率和成功机会很重要。
Multi-arm multi-stage designs can improve the efficiency of the drug-development process by evaluating multiple experimental arms against a common control within one trial. This reduces the number of patients required compared to a series of trials testing each experimental arm separately against control. By allowing for multiple stages experimental treatments can be eliminated early from the study if they are unlikely to be significantly better than control. Using the TAILoR trial as a motivating example, we explore a broad range of statistical issues related to multi-arm multi-stage trials including a comparison of different ways to power a multi-arm multi-stage trial; choosing the allocation ratio to the control group compared to other experimental arms; the consequences of adding additional experimental arms during a multi-arm multi-stage trial, and how one might control the type-I error rate when this is necessary; and modifying the stopping boundaries of a multi-arm multi-stage design to account for unknown variance in the treatment outcome. Multi-arm multi-stage trials represent a large financial investment, and so considering their design carefully is important to ensure efficiency and that they have a good chance of succeeding.