Zhou Wenru, Kroehl Miranda, Meier Maxene, Kaizer Alexander
Department of Biostatistics and Informatics University of Colorado, United States of America.
Charter Communication, United States of America.
Contemp Clin Trials Commun. 2024 Nov 4;42:101388. doi: 10.1016/j.conctc.2024.101388. eCollection 2024 Dec.
This paper proposes a platform trial for conducting A/B tests with multiple arms and interim monitoring to investigate the impact of several factors on the expected sample size and probability of early stopping. We examined the performance of three stopping boundaries: O'Brien Fleming (OBF) stopping for either futility or difference (both), Pocock stopping for futility only, and fixed sample size design. We simulated twelve scenarios of different orders of arms based on various effect sizes, as well as considered 1 or 3 interim looks. The overall findings are summarizing in a flowchart to provide intuitive guidance for the design of the platform based on the simulation. We found that it is better to use OBF stopping for both if there is any effective variant and the trial is sufficiently powered to detect the expected effect size. If the study is underpowered to detect a difference, we recommend fixed sample size design to gather as much information as possible, however if the expected sample size is important to minimize, we recommend using Pocock boundaries with futility monitoring. Our results aimed at helping high-tech companies conduct their own studies without requiring extensive knowledge of clinical trial design and statistical methodology.
本文提出了一个平台试验，用于进行多臂A/B测试和中期监测，以研究几个因素对预期样本量和早期终止概率的影响。我们考察了三种停止边界的性能：奥布赖恩-弗莱明（OBF）无效或差异停止（两者皆有）、仅用于无效的波科克停止以及固定样本量设计。我们基于各种效应大小模拟了12种不同臂序的场景，并考虑了1次或3次中期观察。总体结果总结在一个流程图中，以便根据模拟为平台设计提供直观指导。我们发现，如果存在任何有效变体且试验有足够的检验效能来检测预期效应大小，那么同时使用OBF停止更好。如果研究检验效能不足无法检测到差异，我们建议采用固定样本量设计以尽可能收集更多信息，然而，如果最小化预期样本量很重要，我们建议使用带有无效性监测的波科克边界。我们的结果旨在帮助高科技公司在无需广泛了解临床试验设计和统计方法的情况下开展自身研究。
