NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
Biom J. 2024 Sep;66(6):e202300334. doi: 10.1002/bimj.202300334.
Adaptive platform trials allow treatments to be added or dropped during the study, meaning that the control arm may be active for longer than the experimental arms. This leads to nonconcurrent controls, which provide nonrandomized information that may increase efficiency but may introduce bias from temporal confounding and other factors. Various methods have been proposed to control confounding from nonconcurrent controls, based on adjusting for time period. We demonstrate that time adjustment is insufficient to prevent bias in some circumstances where nonconcurrent controls are present in adaptive platform trials, and we propose a more general analytical framework that accounts for nonconcurrent controls in such circumstances. We begin by defining nonconcurrent controls using the concept of a concurrently randomized cohort, which is a subgroup of participants all subject to the same randomized design. We then use cohort adjustment rather than time adjustment. Due to flexibilities in platform trials, more than one randomized design may be in force at any time, meaning that cohort-adjusted and time-adjusted analyses may be quite different. Using simulation studies, we demonstrate that time-adjusted analyses may be biased while cohort-adjusted analyses remove this bias. We also demonstrate that the cohort-adjusted analysis may be interpreted as a synthesis of randomized and indirect comparisons analogous to mixed treatment comparisons in network meta-analysis. This allows the use of network meta-analysis methodology to separate the randomized and nonrandomized components and to assess their consistency. Whenever nonconcurrent controls are used in platform trials, the separate randomized and indirect contributions to the treatment effect should be presented.
适应性平台试验允许在研究过程中添加或删除治疗方法，这意味着对照组可能比实验组活跃更长时间。这导致了非同期对照，提供了非随机信息，可能提高效率，但可能会因时间混杂和其他因素引入偏倚。已经提出了各种基于时间段调整的方法来控制非同期对照的混杂。我们证明，在某些情况下，时间调整不足以防止适应性平台试验中存在非同期对照时的偏倚，并且我们提出了一种更通用的分析框架，用于在这种情况下考虑非同期对照。我们首先使用同时随机化队列的概念来定义非同期对照，同时随机化队列是所有参与者都受到相同随机设计影响的一个亚组。然后，我们使用队列调整而不是时间调整。由于平台试验的灵活性，在任何时候可能有不止一种随机设计生效，这意味着队列调整和时间调整分析可能有很大的不同。通过模拟研究，我们证明时间调整分析可能存在偏倚，而队列调整分析可以消除这种偏倚。我们还证明，队列调整分析可以被解释为类似于混合治疗比较的网络荟萃分析中的随机和间接比较的综合。这允许使用网络荟萃分析方法来分离随机和非随机成分，并评估它们的一致性。只要在平台试验中使用非同期对照，就应该呈现治疗效果的单独随机和间接贡献。
