Meta-analysis: Key features, potentials and misunderstandings

Abstract

A meta-analysis consists of a systematic approach to combine different studies in one design. Preferably, a protocol is written and published spelling out the research question, eligibility criteria, risk of bias assessment, and statistical approach. Included studies are likely to display some diversity regarding populations, calendar period, or treatment settings. Such diversity should be considered when deciding whether to combine (some) studies in a formal meta-analysis. Statistically, the fixed effect model assumes that all studies estimate the same underlying true effect. This assumption is relaxed in a random effects model and given the expected study diversity a random effects approach will often be more realistic. In the absence of statistical heterogeneity, fixed and random effects models give identical estimates. Meta-analyses are especially useful to provide a broader scope of the literature; they should carefully explore sources of between study heterogeneity and may show a treatment effect or an exposure–outcome association where individual studies are not powered. However, its validity largely depends on the validity of included studies.