J Rheum Dis.  2015 Feb;22(1):4-9. 10.4078/jrd.2015.22.1.4.

Meta-analysis

• Lee YH

• KMID: 2222920
• DOI: http://doi.org/10.4078/jrd.2015.22.1.4

Abstract

Meta-analysis is a statistical tool for combining the results of different studies on the same topic, providing a precise estimate of the effect size and increasing statistical strength, which is particularly important when the strength of the primary study is limited because of a small sample size. Properly conducted meta-analysis provides an invaluable link between past and future studies by quantitatively synthesizing evidence while minimizing bias. Recently, because studies on meta-analysis have been published increasingly, there is a need for rheumatologists to understand meta-analysis. In order to help rheumatologists in use of a meta-analysis, the author describes the basic steps in statistical analysis of a meta-analysis: 1) search for presence of between-study heterogeneity, 2) performing statistical analysis of meta-analysis, 3) checking publication bias, 4) search for causes of heterogeneity, and 5) interpreting and presenting meta-analysis results.

Keyword

Statistical analysis

MeSH Terms

Bias (Epidemiology)
Meta-Analysis as Topic
Population Characteristics
Publication Bias
Sample Size

Figure

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  Figure 1. Forrest plot of odds ratios (ORs) and 95% confidence interval (CIs) of individual studies and pooled data for the association between the C allele of the Fc receptor-like 3-169 C/T polymorphism and rheumatoid arthritis (RA) in each ethnic group. NAN: North American Native.

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  Figure 2. Funnel plot of studies regarding the association between the Fc receptor-like 3-169 C allele and rheumatoid arthritis showed no evidence of asymmetry and Egger's regression test showed no significant p-value (Egger's regression test p-value=0.863), indicating no evidence of publication bias in the meta-analysis.

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