Meta-analysis: Principles and procedures

BMJ 1997; 315 doi: http://dx.doi.org/10.1136/bmj.315.7121.1533 (Published 6 December 1997)
Cite this as: BMJ 1997;315:1533

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  1. Matthias Egger, reader in social medicine and epidemiology (egger@bristol.ac.uk)a,
  2. George Davey Smith, professor of clinical epidemiologya,
  3. Andrew N Phillips, professor of epidemiology and biostatisticsb

    This is the second in a series of seven articles examining the procedures in conducting reliable meta-analysis in medical research

  1. a Department of Social Medicine, University of Bristol, Bristol BS8 2PR
  2. b Department of Primary Care and Population Sciences, Royal Free Hospital School of Medicine, London NW3 2PF
  1. Correspondence to: Dr Eggerm

    Introduction

    Meta-analysis is a statistical procedure that integrates the results of several independent studies considered to be “combinable.”1 Well conducted meta-analyses allow a more objective appraisal of the evidence than traditional narrative reviews, provide a more precise estimate of a treatment effect, and may explain heterogeneity between the results of individual studies.2 Ill conducted meta-analyses, on the other hand, may be biased owing to exclusion of relevant studies or inclusion of inadequate studies.3 Misleading analyses can generally be avoided if a few basic principles are observed. In this article we discuss these principles, along with the practical steps in performing meta-analysis.

    Observational study of evidence

    Meta-analysis should be viewed as an observational study of the evidence. The steps involved are similar to any other research undertaking: formulation of the problem to be addressed, collection and analysis of the data, and reporting of the results. Researchers should write in advance a detailed research protocol that clearly states the objectives, the hypotheses to be tested, the subgroups of interest, and the proposed methods and criteria for identifying and selecting relevant studies and extracting and analysing information.

    As with criteria for including and excluding patients in clinical studies, eligibility criteria have to be defined for the data to be included. Criteria relate to the quality of trials and to the combinability of treatments, patients, outcomes, and lengths of follow up. Quality and design features of a study can influence the results.4 5 Ideally, researchers should consider including only controlled trials with proper randomisation of patients that report on all initially included patients according to the intention to treat principle and with an objective, preferably blinded, outcome assessment.6 Assessing the quality of a study …

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