Selection of effect size from binary data in Meta-analysis
FU Wen-jie
WU Jun-yi
XU Yang-peng
ZHANG Qian
ZHANG Huan
WU Di
ZHANG Chao
Abstract：Objective To investigate the selection of the best effect size from binary data in Meta-analysis based on case study.Methods Through systematic retrospective of 551 reviews and 114 Meta-analysis documents, 4 effective indexes were analyzed and compared including odds ratio (OR), risk difference (RD), relative risk of benefit [RR (B)] and relative risk of harmful [RR (H)].Results The evidence from 551 reviews showed thatRR and OR had better efficacy than RD in the aspect of outcome superiority. Meanwhile,OR had an inclination to overestimate the pooled results, even leaded to a qualitative inconsistency in the Meta-analysis. The results of 114 Meta-analysis documents showed that for intervention aimed at preventing reverse events, the highest incidence rate of baseline risk would induce the greatest absolute benefit effect, and RR (H) was optimized at this moment.Conclusion The multiple factors should be considered including cause of baseline risk variation, effect size interpretability and mathematical properties in the selection of effect size. For some special cases, the characteristics of clinical trials should also be taken as one of factors in selecting effect size.
Keywords：Meta-analysisEffect sizeBaseline riskBinary categorical data
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 7-11,22 )