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Conducting quantitative synthesis when comparing medical interventions: AHRQ and the Effective Health Care Program

机译:比较医疗干预措施时进行定量综合:AHRQ和有效医疗保健计划

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摘要

Objective: This article is to establish recommendations for conducting quantitative synthesis, or meta-analysis, using study-level data in comparative effectiveness reviews (CERs) for the Evidence-based Practice Center (EPC) program of the Agency for Healthcare Research and Quality. Study Design and Setting: We focused on recurrent issues in the EPC program and the recommendations were developed using group discussion and consensus based on current knowledge in the literature. Results: We first discussed considerations for deciding whether to combine studies, followed by discussions on indirect comparison and incorporation of indirect evidence. Then, we described our recommendations on choosing effect measures and statistical models, giving special attention to combining studies with rare events; and on testing and exploring heterogeneity. Finally, we briefly presented recommendations on combining studies of mixed design and on sensitivity analysis. Conclusion: Quantitative synthesis should be conducted in a transparent and consistent way. Inclusion of multiple alternative interventions in CERs increases the complexity of quantitative synthesis, whereas the basic issues in quantitative synthesis remain crucial considerations in quantitative synthesis for a CER. We will cover more issues in future versions and update and improve recommendations with the accumulation of new research to advance the goal for transparency and consistency.
机译:目的:本文旨在为在医疗研究和质量机构的循证实践中心(EPC)计划的比较有效性评论(CER)中使用研究水平的数据,建立进行定量合成或荟萃分析的建议。研究设计与设置:我们关注EPC计划中的反复出现的问题,并根据文献中的当前知识,使用小组讨论和共识提出了建议。结果:我们首先讨论了决定是否合并研究的考虑因素,然后讨论了间接比较和纳入间接证据的问题。然后,我们描述了我们关于选择效果度量和统计模型的建议,特别注意将研究与罕见事件相结合;以及测试和探索异质性。最后,我们简要介绍了将混合设计研究与敏感性分析相结合的建议。结论:定量合成应以透明和一致的方式进行。在CER中包含多种替代干预措施会增加定量合成的复杂性,而定量合成中的基本问题仍然是CER定量合成中的关键考虑因素。我们将在将来的版本中涵盖更多问题,并通过积累新的研究成果来更新和改进建议,以提高透明度和一致性的目标。

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