Meta分析中效应尺度指标的选择

The Selection of a Summary Statistic for Use in Meta-analysis

Meta分析中效应尺度指标的选择对其结果的解释和应用非常重要。本文首先简要介绍了常见的几种Meta分析合并统计量的基本概念。Meta分析中选择合并统计量常需要考虑以下因素:流行病学设计类型,资料(数据)类型,效应一致性,数学特性和可解释性。对连续性变量,当对同一干预措施效应的测量方法或单位完全相同时,宜选择WMD;当对同一干预措施效应采用不同的测量方法或单位,或不同研究间均数差异过大时,宜选择SMD作为合并统计量。对二分类变量,随机对照试验的Meta分析推荐首选RR为合并统计量。当干预(暴露)组和对照组的事件发生率均非常低时,可以采用OR估计RR。Meta分析中无一个可应用于所有情形的最佳合并统计量。

The selection of summary statistics to use in a meta-analysis is very important for the interpretation and application of its results. This paper introduces some basic concepts of summary statistics in meta-analysis. The selection of a summary statistic for a meta-analysis depends on the following factors： design of the studies being combined, type of data, consistency among the included studies, mathematical properties and ease of interpretation. For continuous data, the weighted mean difference （WMD） is recommended when all trials use the same scale to report their outcomes, while standardized mean difference （SMD） is more appropriate when trials use different scales to report their outcomes, or the means of their outcomes differ greatly. For dichotomous data, rate ratio or relative risk （RR） is strongly recommended to be the summary statistics for meta-analyses of randomized trials. The use of odds ratio （OR） as the summary statistic is similar to that of RR, if the event being studied in both the intervention （exposure） and the control group is rare. There is no single measurement that is uniformly best for all meta-analyses.