title: The quality of meta-analyses of genetic association studies: a review with recommendations.
abstract: Although there has been a rapid rise in the publication of meta-analyses of genetic association studies, little is known about their methodological quality. The authors reviewed the quality of 120 randomly selected genetic meta-analyses published between 2005 and 2007. Data extracted included issues of general relevance and other issues specific to genetic epidemiology. Quality was markedly poorer in the 26% of the meta-analyses that accompanied a report on a primary study. Such meta-analyses were predominantly published in specialist journals, and their quality was positively associated with the impact factor of the journal. Among the meta-analyses that did not accompany a primary study, Human Genome Epidemiology reviews tended to score better than the others, although the comparison was limited by relatively small numbers. Comparison of the overall quality with that of genetic meta-analyses published before 2000 showed improvement in both conduct and reporting. However, the quality of the handling of specific genetic issues remains disappointingly low. For a few key general quality issues, the authors compared their findings with findings in other fields of medicine and found that general quality was similar. On the basis of this review, the authors provide practical recommendations for the conduct and reporting of genetic meta-analyses.
authors.affiliation: Institute of Genetic Medicine, EURAC Research, Viale Druso 1, 39100 Bolzano, Italy. cosetta.minelli@eurac.edu
authors.forename: Cosetta
authors.initials: C
authors.lastname: Minelli
authors.forename: John R
authors.initials: JR
authors.lastname: Thompson
authors.forename: Keith R
authors.initials: KR
authors.lastname: Abrams
authors.forename: Ammarin
authors.initials: A
authors.lastname: Thakkinstian
authors.forename: John
authors.initials: J
authors.lastname: Attia
mesh_terms: D056726:Genetic Association Studies / Q000592:standards* / Q000706:statistics & numerical data / Q000639:trends; D006801:Humans; D055811:Journal Impact Factor; D015201:Meta-Analysis as Topic