A Preplanned Multi-Stage Platform Trial for Discovering Multiple Superior Treatments With Control of FWER and Power

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Peter Greenstreet, Thomas Jaki, Alun Bedding, Pavel Mozgunov
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Abstract

There is a growing interest in the implementation of platform trials, which provide the flexibility to incorporate new treatment arms during the trial and the ability to halt treatments early based on lack of benefit or observed superiority. In such trials, it can be important to ensure that error rates are controlled. This paper introduces a multi-stage design that enables the addition of new treatment arms, at any point, in a preplanned manner within a platform trial, while still maintaining control over the family-wise error rate. This paper focuses on finding the required sample size to achieve a desired level of statistical power when treatments are continued to be tested even after a superior treatment has already been found. This may be of interest if there are treatments from different sponsors which are also superior to the current control or multiple doses being tested. The calculations to determine the expected sample size is given. A motivating trial is presented in which the sample size of different configurations is studied. In addition, the approach is compared to running multiple separate trials and it is shown that in many scenarios if family-wise error rate control is needed there may not be benefit in using a platform trial when comparing the sample size of the trial.

Abstract Image

一个预先计划的多阶段平台试验,以发现具有控制功率和功率的多种优越治疗方法。
人们对平台试验的实施越来越感兴趣,平台试验提供了在试验期间纳入新治疗臂的灵活性,并且能够在缺乏益处或观察到的优势的情况下早期停止治疗。在这样的试验中,确保错误率得到控制是很重要的。本文介绍了一种多阶段设计,可以在平台试验的任何时候以预先计划的方式添加新的治疗臂,同时仍然保持对家庭错误率的控制。本文的重点是找到所需的样本量,以达到理想的统计能力水平,当治疗继续进行测试,即使在一个更好的治疗已经发现。如果来自不同赞助方的治疗方法也优于目前的对照或正在测试的多剂量,这可能会引起人们的兴趣。给出了确定预期样本量的计算方法。提出了一个激励试验,研究了不同构型的样本量。此外,将该方法与运行多个单独的试验进行比较,结果表明,在许多情况下,如果需要家庭错误率控制,那么在比较试验的样本量时,使用平台试验可能没有好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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