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Abstract：
Aim: The presence of two or more publications that report on overlapping patient cohorts poses a challenge for quantitatively synthesizing real-world evidence (RWE) studies. Thus, we evaluated eight approaches for handling such related publications in network meta-analyses (NMA) of RWE studies. Methods: Bayesian NMAs were conducted to estimate the annualized relapse rate (ARR) of disease-modifying therapies in multiple sclerosis. The NMA explored the impact of hierarchically selecting one pivotal study from related publications versus including all of them while adjusting for correlations. Results: When selecting one pivotal study from related publications, the ARR ratios were mostly similar regardless of the pivotal study selected. When including all related publications, there were shifts in the point estimates and the statistical significance. Conclusion: An a priori hierarchy should guide the selection among related publications in NMAs of RWE. Sensitivity analyses modifying the hierarchy should be considered for networks with few or small studies.
摘要：
目的：报告重叠患者队列的两个或多个出版物的存在对定量综合现实世界证据（RWE）研究提出了挑战。因此，我们在RWE研究的网络荟萃分析(NMA)中评估了处理此类相关出版物的8种方法.方法：进行贝叶斯NMA以估计多发性硬化症中疾病改善疗法的年度复发率（ARR）。NMA探索了从相关出版物中分层选择一项关键研究的影响，而不是在调整相关性的同时包括所有研究。结果：从相关出版物中选择一项关键研究时，无论所选择的关键研究如何,ARR比率大多相似.当包括所有相关出版物时，点估计有变化,且有统计学意义.结论：先验层次结构应指导RWENMA相关出版物的选择。对于研究较少或较小的网络，应考虑修改层次结构的敏感性分析。
