Designing and analysing multi-arm multi-stage clinical trials with one or more endpoints

在药物开发的早期阶段，在一组不同的治疗方法中，往往不确定哪种最有希望。为了确保在这种情况下最好地利用资源，重要的是要决定哪些治疗方法（如果有的话）应该提前进行进一步测试。解决这一问题的有效方法是多组临床试验，其中几种有效治疗与普通对照组进行比较。通过在一个试验中比较几种治疗，所需的样本量和持续时间往往比单独评估每种治疗的样本量和持续时间要小得多。为了提高效率，最好在一系列中期分析中对试验进行监测，以便在迅速确立疗效的情况下尽早停止试验，并尽早消除无效的治疗方法。在验证性研究中，这些设计也很有用，因为已经证明使用两个剂量而不是一个剂量可以显着提高研究的成功概率。该提案旨在开发统计方法，以调查如何最好地设计和分析这些所谓的多臂多阶段试验。这项工作将利用三个最近完成或正在进行的三个重要医学领域的研究：艾滋病毒/艾滋病、白血病和转移性前列腺癌。多学科研究团队包括来自利兹临床试验研究单位、利物浦大学和MRC临床试验单位的经验丰富的临床专家和临床试验人员，以及来自不来梅大学和华威医学院的具有临床试验统计方法经验的统计学家。

In the early stages of drug development there is often uncertainty about the most promising among a set of different treatments. In order 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. An efficient solution to this problem are multi-arm clinical trials in which several active treatments are compared to a common control group. By comparing several treatments within one trial the sample size and duration required tends to be markedly smaller than if each treatment would have been evaluated separately. For added efficiency it is desirable to monitor the trial at a series of interim analyses in order to allow early stopping if efficacy is quickly established and similarly to eliminate ineffective treatments early. In confirmatory studies these designs are also useful as it has been shown that using two doses instead of a single dose can markedly improve the study's success probability. This proposal aims to develop statistical methods to investigate how these, so called multi-arm multi-stage trials, can best be designed and analysed. The work will utilize three recently finished or currently ongoing studies in three important medical areas: HIV/AIDS, leukemia and metastatic prostate cancer. The multidisciplinary research team includes experienced clinical specialists and clinical trialists for each study from the clinical trials research unit in Leeds, the University of Liverpool and the MRC clinical trials unit as well as statisticians with experience in statistical methods for clinical trials from the University of Bremen and the Warwick medical school.