Adaptive enrichment trials aim to identify and recruit participants most likely to benefit from treatment based on evolving biomarker evidence, with the goal of informing individualized treatment recommendations. Bayesian methods are well suited to these designs because they allow external information to be incorporated in a principled manner. In practice, prior studies often provide only summary-level information, with subgroup-specific estimates unavailable due to design or privacy constraints. Existing dynamic borrowing approaches therefore rely on aggregate measures, such as the average treatment effect, and implicitly assume that historical information maps directly onto model parameters. In adaptive enrichment settings aimed at identifying individualized treatment effects, however, subgroup-specific treatment parameters are not identifiable when only marginal historical effects are available. To address this gap, we propose a Bayesian adaptive enrichment design that borrows information from external studies using a normalized power prior anchored on one or more summary measures, such as the average treatment effect. { To our knowledge, no existing method addresses this gap.} Interim analyses use posterior probabilities to guide early stopping for efficacy or futility, or to continue recruitment within promising biomarker-defined subgroups. Simulation studies evaluate operating characteristics across historical bias, sample size, and prior informativeness. Together with a motivating future trial in obstructive sleep apnea, the results show efficiency gains versus non-borrowing designs, including improved power, earlier stopping, and reduced expected sample size.

翻译：适应性富集试验旨在基于不断积累的生物标志物证据，识别并招募最可能从治疗中获益的参与者，从而指导个体化治疗推荐。贝叶斯方法因能原则性地整合外部信息而特别适用于此类设计。然而在实践中，既往研究通常仅提供汇总层面的信息，受限于研究设计或隐私约束，无法获取亚组特异性估计值。现有动态借用方法因此依赖平均处理效应等聚合指标，并隐含假设历史信息可直接映射至模型参数。但在旨在识别个体化治疗效应的适应性富集场景中，当仅有边缘历史效应可用时，亚组特异性治疗参数是不可识别的。为弥补这一方法学空白，我们提出一种基于归一化幂先验的贝叶斯适应性富集设计，该先验以一个或多个汇总指标（如平均处理效应）为锚点，从外部研究中借用信息。据我们所知，现有方法尚未解决这一问题。期中分析采用后验概率指导因有效性或无效性提前终止，或继续在具有前景的生物标志物定义亚组中招募受试者。模拟研究评估了在不同历史偏倚、样本量及先验信息强度下的操作特征。结合一项待开展的阻塞性睡眠呼吸暂停试验，结果表明相较于非借用设计，该方法具有效率优势，包括统计效力提升、提前终止能力增强以及期望样本量降低。