Suppr超能文献

网络荟萃分析中的概念和技术挑战。

Conceptual and technical challenges in network meta-analysis.

机构信息

Department of Public Health and Community Medicine, University of Verona, Policlinico G.B. Rossi, Piazzale L.A. Scuro 10, 37134 Verona, Italy.

出版信息

Ann Intern Med. 2013 Jul 16;159(2):130-7. doi: 10.7326/0003-4819-159-2-201307160-00008.

Abstract

The increase in treatment options creates an urgent need for comparative effectiveness research. Randomized, controlled trials comparing several treatments are usually not feasible, so other methodological approaches are needed. Meta-analyses provide summary estimates of treatment effects by combining data from many studies. However, an important drawback is that standard meta-analyses can compare only 2 interventions at a time. A new meta-analytic technique, called network meta-analysis (or multiple treatments meta-analysis or mixed-treatment comparison), allows assessment of the relative effectiveness of several interventions, synthesizing evidence across a network of randomized trials. Despite the growing prevalence and influence of network meta-analysis in many fields of medicine, several issues need to be addressed when constructing one to avoid conclusions that are inaccurate, invalid, or not clearly justified. This article explores the scope and limitations of network meta-analysis and offers advice on dealing with heterogeneity, inconsistency, and potential sources of bias in the available evidence to increase awareness among physicians about some of the challenges in interpretation.

摘要

治疗选择的增加迫切需要进行比较效果研究。比较几种治疗方法的随机对照试验通常是不可行的,因此需要其他方法。荟萃分析通过合并来自多项研究的数据来提供治疗效果的综合估计。然而,一个重要的缺点是标准的荟萃分析一次只能比较两种干预措施。一种新的荟萃分析技术,称为网络荟萃分析(或多种治疗荟萃分析或混合治疗比较),允许评估几种干预措施的相对效果,通过随机试验网络综合证据。尽管网络荟萃分析在医学的许多领域越来越流行和有影响力,但在构建网络荟萃分析时需要解决几个问题,以避免不准确、无效或没有明确依据的结论。本文探讨了网络荟萃分析的范围和局限性,并就处理异质性、不一致性和现有证据中潜在的偏倚来源提供了建议,以提高医生对解释方面一些挑战的认识。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验