Medical and Pharmaceutical Research Unit, Department of Mathematics and Statistics, Lancaster University, UK.
Stat Med. 2013 Mar 30;32(7):1150-63. doi: 10.1002/sim.5669. Epub 2012 Oct 30.
In early stages of drug development, there is often uncertainty about the most promising among a set of different treatments. To ensure the best use of resources in such situations, it is important to decide which, if any, of the treatments should be taken forward for further testing. In later development, it has been shown that evaluating more than one dose increases the chance of success substantially. In this work, we discuss how multi-arm multi-stage trials can be designed such that all promising treatments are kept in the study at the interim analyses. We first investigate the impact of deviating from the planned design and show how confidence intervals can be constructed before we consider the impact of important covariates. We show that under orthogonality, the inclusion of covariates has no effect on familywise error rate control in the strong sense. We further show that the derived methodology can be used to investigate non-normal endpoints.
在药物开发的早期阶段，对于一组不同治疗方法中最有前途的方法往往存在不确定性。为了确保在这种情况下最佳利用资源，重要的是要决定是否应该将任何一种治疗方法推进到进一步的测试中。在后期开发中，已经表明评估多个剂量会大大增加成功的机会。在这项工作中，我们讨论了如何设计多臂多阶段试验，以便在中期分析时将所有有前途的治疗方法都保留在研究中。我们首先研究了偏离计划设计的影响，并展示了如何在考虑重要协变量的影响之前构建置信区间。我们表明，在正交性下，协变量的纳入对强意义上的总体错误率控制没有影响。我们进一步表明，所得到的方法可以用于研究非正态终点。
