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Systematic Review and Meta-analysis: Sometimes Bigger Is Indeed Better

Clinicians encounter an ever increasing and frequently overwhelming amount of information, even in a narrow scope or area of interest. Given this enormous amount of scientific information published every year, systematic reviews and meta-analyses have become indispensable methods for the evaluation of medical treatments and the delivery of evidence-based best practice. The present basic statistical tutorial thus focuses on the fundamentals of a systematic review and meta-analysis, against the backdrop of practicing evidence-based medicine. Even if properly performed, a single study is no more than tentative evidence, which needs to be confirmed by additional, independent research. A systematic review summarizes the existing, published research on a particular topic, in a well-described, methodical, rigorous, and reproducible (hence “systematic”) manner. A systematic review typically includes a greater range of patients than any single study, thus strengthening the external validity or generalizability of its findings and the utility to the clinician seeking to practice evidence-based medicine. A systematic review often forms the basis for a concomitant meta-analysis, in which the results from the identified series of separate studies are aggregated and statistical pooling is performed. This allows for a single best estimate of the effect or association. A conjoint systematic review and meta-analysis can provide an estimate of therapeutic efficacy, prognosis, or diagnostic test accuracy. By aggregating and pooling the data derived from a systemic review, a well-done meta-analysis essentially increases the precision and the certainty of the statistical inference. The resulting single best estimate of effect or association facilitates clinical decision making and practicing evidence-based medicine. A well-designed systematic review and meta-analysis can provide valuable information for researchers, policymakers, and clinicians. However, there are many critical caveats in performing and interpreting them, and thus, like the individual research studies on which they are based, there are many ways in which meta-analyses can yield misleading information. Creators, reviewers, and consumers alike of systematic reviews and meta-analyses would thus be well-served to observe and mitigate their associated caveats and potential pitfalls.