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Meta分析的基本概念:临床医生入门指南。

Basic concepts in meta-analysis: A primer for clinicians.

作者信息

Khoshdel A, Attia J, Carney S L

机构信息

Department of Nephrology, Faculty of Health, John Hunter Hospital, NSW, Australia.

出版信息

Int J Clin Pract. 2006 Oct;60(10):1287-94. doi: 10.1111/j.1742-1241.2006.01078.x.

DOI:10.1111/j.1742-1241.2006.01078.x
PMID:16981972
Abstract

With the expanding volume of medical literature, meta-analysis, a form of systematic review, has become indispensable for clinicians for evidence-based decision making. While the number of meta-analyses has substantially increased during recent years, there are still controversial issues regarding their methodology, interpretation and clinical application. In this review, the basic concepts of meta-analysis have been discussed from a clinician's perspective in order to facilitate its understanding, appraising and applicability in clinical practice. Although randomised controlled trials are the usual source for meta-analysis, observational studies are also being increasingly considered for meta-analysis. Like every other research design, meta-analysis starts with formulating a question, followed by searching for related data, based on predefined criteria and strategies. Inclusion of studies must be carried out with careful consideration of their quality and assessment of homogeneity using graphical means as well as statistical tools such as Q statistics, I(2) statistics and meta-regression. The pooled effect size is commonly calculated using either a 'fixed effect model' or 'random effect model'. Publication bias and other source of bias should be investigated and the impact of potential confounders should be eliminated as required. Given the above-mentioned considerations, meta-analysis can provide a more precise estimate of an effect size to be used in clinical decision making.

摘要

随着医学文献数量的不断增加,荟萃分析作为系统评价的一种形式,已成为临床医生基于证据进行决策时不可或缺的工具。尽管近年来荟萃分析的数量大幅增加,但在其方法学、解释和临床应用方面仍存在争议性问题。在本综述中,从临床医生的角度讨论了荟萃分析的基本概念,以促进其在临床实践中的理解、评估和应用。虽然随机对照试验通常是荟萃分析的数据源,但观察性研究也越来越多地被纳入荟萃分析。与其他研究设计一样,荟萃分析始于提出问题,然后根据预定义的标准和策略搜索相关数据。纳入研究时必须仔细考虑其质量,并使用图形方法以及Q统计量、I²统计量和荟萃回归等统计工具评估同质性。合并效应量通常使用“固定效应模型”或“随机效应模型”计算。应调查发表偏倚和其他偏倚来源,并根据需要消除潜在混杂因素的影响。考虑到上述因素,荟萃分析可以为临床决策中使用的效应量提供更精确的估计。

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