Last update:
08-Jan-2010

Systematic review and meta-analysis should be considered as two different interdependent procedures that aim to calculate a summary effect indicating the relationship between the determinant under study and the outcome. The basis of a systematic review is a comprehensive literature review to identify all the similar and relevant studies that satisfy a pre-defined set of inclusion and exclusion criteria. The basic steps in a systematic review include (a) a clear statement of the scientific hypothesis to be tested, (b) a clearly defined statement of inclusion and exclusion criteria for admission of studies into the review, and (c) a methodology for locating studies that should be included in the meta-analysis. The end result of a systematic review is a list of studies each of which provides a weighted value for the calculation of the summary result. Meta-analysis is the mathematical process of combining the separate studies that have been chosen in the systematic review to produce one overall study and to calculate a summary effect. For example, if there are three separate studies, with 30, 50 and 100 participants, respectively, their combination would generate a total study with 180 participants. The assumption of the meta-analysis is that this combined study will provide a more reliable and precise overall result than any of the smaller individual studies. The basic steps in a meta- analysis include (a) estimation of publication bias, (b) estimation of heterogeneity among the studies, and (c) a mathematical process to combine the results of the separate studies. Estimation of publication bias is achieved with the funnel plot, the rank correlation coefficient (Kendall's or Spearman's) or the sensitivity analysis. L' Abbe plot and DerSimonian-Laird's Q test are used to estimate the heterogeneity among studies. The combined result of the meta- analysis and the results of the individual studies are displayed graphically using the forest plot. Systematic review and meta-analysis offer the best choice for researchers in making rational decisions about public health issues.

Key words: Fixed-effects model, Meta-analysis, Publication bias, Random-effects model, Systematic review.