Systematic reviews and meta-analyses of randomized trials: principles and pitfalls

• Published in: European heart journal Vol. 35; no. 47; pp. 3336 - 3345
• Main Authors: da Costa, Bruno R., Jüni, Peter
• Format: Journal Article
• Language: English
• Published: England 14.12.2014
• Subjects: Data Interpretation, Statistical; Meta-Analysis as Topic; Publications - statistics & numerical data; Random Allocation; Randomized Controlled Trials as Topic - methods; Randomized Controlled Trials as Topic - standards; Randomized Controlled Trials as Topic - statistics & numerical data; Regression Analysis; Review Literature as Topic; Statistics as Topic - methods
• ISSN: 0195-668X; 1522-9645; 1522-9645
• DOI: 10.1093/eurheartj/ehu424

Systematic reviews and meta-analyses allow for a more transparent and objective appraisal of the evidence. They may decrease the number of false-negative results and prevent delays in the introduction of effective interventions into clinical practice. However, as for any other tool, their misuse can result in severely misleading results. In this article,we discuss the main steps that should be taken when conducting systematic reviews and meta-analyses, namely the preparation of a review protocol, identification of eligible trials, and data extraction, pooling of treatment effects across trials, investigation of potential reasons for differences in treatment effects across trials, and complete reporting of the review methods and findings.We also discuss common pitfalls that should be avoided, including the use of quality assessment tools to derive summary quality scores, pooling of data across trials as if they belonged to a single large trial, and inappropriate uses of meta-regression that could result in misleading estimates of treatment effects because of regression to the mean or the ecological fallacy. If conducted and reported properly, systematic reviews and meta-analyses will increase our understanding of the strengths and weaknesses of the available evidence, which may eventually facilitate clinical decision making.