荟萃分析
严格标准化平均差
置信区间
平均差
研究异质性
医学
内科学
合并方差
元回归
标准差
样本量测定
出版偏见
随机效应模型
诊断优势比
统计
梅德林
数学
作者
Jan O. Friedrich,Neill K. J. Adhikari,Joseph Beyene
标识
DOI:10.1016/j.jclinepi.2010.09.016
摘要
Meta-analyses of continuous outcomes typically use mean differences (MDs) or standardized mean differences (SMDs) (MD in pooled standard deviation units). Ratio of means (RoM) is an alternative effect measure that performs comparably in simulation. We compared treatment effects and heterogeneity for RoM, MD, and SMD using empiric data.From the Cochrane Database (2008, issue 1), we included systematic reviews reporting continuous outcomes, selected the meta-analysis with the most (and ≥five) trials, and calculated MD (where possible), SMD, and RoM. For each pair of effect measures, we compared P-values separately for treatment effect and heterogeneity and assessed asymmetry of discordant pairs (statistically significant result for only one of two measures).Two hundred thirty-two of 5,053 reviews were included. Measures demonstrated similar treatment effects, with ≤6% discordant pairs and no asymmetry. A 0.5 SMD increase corresponded to 22 (95% confidence interval: 19, 24)% increase using RoM. There was less heterogeneity in RoM vs. MD (n=143, P=0.007), SMD vs. RoM (n=232, P=0.005), and SMD vs. MD (n=143, P=0.004). Comparing discordant pairs, fewer meta-analyses showed significant heterogeneity with SMD vs. RoM (P=0.04), consistent with the known bias of SMD.Empiric data from diverse meta-analyses demonstrate similar treatment effects and no large differences in heterogeneity of RoM compared with difference-based methods.
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