组合疗法在治疗领域，如肿瘤学和传染病等，越来越得到应用，其潜在优势包括减轻药物抗性和毒性。一组组合研究可能相关，例如，如果它们至少有一个共同治疗并用于同一指示，那么它们就是相关的。在这种情况下，通过在相关组合研究之间共享信息可以获得价值。我们提供了一个框架，允许基于单个组合研究的结果更新一组相关组合疗法的研究成功概率。这样，我们可以在未来研究的决策过程中将组合疗法的直接和间接数据纳入考虑。我们还提出了一个强化方法，考虑到一组组合疗法的先前假设可能是不正确的相关结构。我们展示了如何在实践中使用此框架，并突出显示研究成功概率在临床研究计划中的用处。

Combination therapies are becoming increasingly used in a range of therapeutic areas such as oncology and infectious diseases, providing potential benefits such as minimising drug resistance and toxicity. Sets of combination studies may be related, for example, if they have at least one treatment in common and are used in the same indication. In this setting, value can be gained by sharing information between related combination studies. We present a framework that allows the study success probabilities of a set of related combination therapies to be updated based on the outcome of a single combination study. This allows us to incorporate both direct and indirect data on a combination therapy in the decision-making process for future studies. We also provide a robustification that accounts for the fact that the prior assumptions on the correlation structure of the set of combination therapies may be incorrect. We show how this framework can be used in practice and highlight the use of the study success probabilities in the planning of clinical studies.