Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: Part 1
Interpreting Indirect Treatment Comparisons and Network Meta-Analysis for Health-Care Decision Making: Report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: Part 1
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DOI：
10.1016/j.jval.2011.04.002
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发表时间：
2011-06-01
期刊：
影响因子：
4.5
通讯作者：
Cappelleri, Joseph C.
中科院分区：
文献类型：
--
作者：
Jansen, Jeroen P.;Fleurence, Rachael;Cappelleri, Joseph C.
循证保健决策需要对所有相关的竞争性干预措施进行比较。在缺乏直接比较所有相关治疗的随机对照试验的情况下，间接治疗比较和网络荟萃分析为明智地选择最佳治疗提供了有用的证据。混合治疗比较是网络荟萃分析的一种特殊情况，它结合了联合收割机的直接和间接证据进行特定的成对比较，从而比传统的荟萃分析综合了更大份额的可用证据。ISPOR间接治疗比较良好研究实践工作组的这份报告提供了间接治疗比较和网络荟萃分析的解释指南，以帮助政策制定者和卫生保健专业人员使用其结果进行决策。我们首先概述了随机对照试验网络如何允许竞争干预措施的多个治疗比较。接下来，介绍了现有证据的综合，重点是术语，假设，有效性和统计方法，然后是关于批判性审查和解释间接治疗比较或网络荟萃分析的建议，以告知决策。最后，我们讨论了如果没有直接或间接的随机对照试验的治疗比较，并且仍然需要做出卫生保健决定，该怎么办。
Evidence-based health-care decision making requires comparisons of all relevant competing interventions. In the absence of randomized, controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best choice(s) of treatment. Mixed treatment comparisons, a special case of network meta-analysis, combine direct and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than a traditional meta-analysis. This report from the ISPOR Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on the interpretation of indirect treatment comparisons and network meta-analysis to assist policymakers and health-care professionals in using its findings for decision making. We start with an overview of how networks of randomized, controlled trials allow multiple treatment comparisons of competing interventions. Next, an introduction to the synthesis of the available evidence with a focus on terminology, assumptions, validity, and statistical methods is provided, followed by advice on critically reviewing and interpreting an indirect treatment comparison or network meta-analysis to inform decision making. We finish with a discussion of what to do if there are no direct or indirect treatment comparisons of randomized, controlled trials possible and a health-care decision still needs to be made.