Enrolling patients to the standard of care (SOC) arm in randomized clinical trials, especially for rare diseases, can be very challenging due to the lack of resources, restricted patient population availability, and ethical considerations. As the therapeutic effect for the SOC is often well documented in historical trials, we propose a Bayesian platform trial design with hybrid control based on the multisource exchangeability modelling (MEM) framework to harness historical control data. The MEM approach provides a computationally efficient method to formally evaluate the exchangeability of study outcomes between different data sources and allows us to make better informed data borrowing decisions based on the exchangeability between historical and concurrent data. We conduct extensive simulation studies to evaluate the proposed hybrid design. We demonstrate the proposed design leads to significant sample size reduction for the internal control arm and borrows more information compared to competing Bayesian approaches when historical and internal data are compatible.

中文翻译：

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基于多源可交换性建模的混合控制贝叶斯平台试验设计

由于缺乏资源、患者群体有限以及伦理方面的考虑，将患者纳入标准护理 (SOC) 组进行随机临床试验（尤其是罕见疾病）可能非常具有挑战性。由于 SOC 的治疗效果通常在历史试验中得到充分记录，因此我们提出了一种基于多源可交换性建模 (MEM) 框架的混合控制贝叶斯平台试验设计，以利用历史控制数据。 MEM 方法提供了一种计算有效的方法来正式评估不同数据源之间研究结果的可交换性，并使我们能够根据历史数据和并发数据之间的可交换性做出更明智的数据借用决策。我们进行了广泛的模拟研究来评估所提出的混合设计。我们证明，当历史数据和内部数据兼容时，所提出的设计可以显着减少内部控制组的样本量，并且与竞争的贝叶斯方法相比，可以借用更多信息。