Redundant meta-analyses are common in genetic epidemiology.

Efficiency Genetic Variation Genome, Human Genotype Humans Meta-Analysis as Topic Molecular Epidemiology / statistics & numerical data
Citation analysis Duplication Genetic epidemiology Meta-analysis Metaresearch Research efficiency

Journal

Journal of clinical epidemiology
ISSN: 1878-5921
Titre abrégé: J Clin Epidemiol
Pays: United States
ID NLM: 8801383

Informations de publication

Date de publication:
11 2020
Historique:
received: 06 11 2019
revised: 02 05 2020
accepted: 13 05 2020
pubmed: 17 6 2020
medline: 6 3 2021
entrez: 17 6 2020
Statut: ppublish

Résumé

The massive growth in the publication of meta-analyses may cause redundancy and wasted efforts. We performed a metaepidemiologic study to evaluate the extent of potential redundancy in published meta-analyses in genetic epidemiology. Using a sample of 38 index meta-analyses of genetic associations published in 2010, we retrieved additional meta-analyses that evaluated identical associations (same genetic variant and phenotype) using the Human Genome Epidemiology (HuGE) Navigator and PubMed databases. We analyzed the frequency of potential duplication and examined whether subsequent meta-analyses cited previous meta-analyses on the exact same association. Based on 38 index meta-analyses, we retrieved a total of 99 duplicate meta-analyses. Only 12 (32%) of the index meta-analyses were unambiguously unique. We found a mean of 2.6 duplicates and a median of 2 duplicates per meta-analysis. In case studies, only 29-54% of previously published meta-analyses were cited by subsequent ones. These results suggest that duplication is common in meta-analyses of genetic associations.

Identifiants

DOI: 10.1016/j.jclinepi.2020.05.035 PMID: 32540390
pubmed: 32540390
pii: S0895-4356(19)30955-2
doi: 10.1016/j.jclinepi.2020.05.035
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

40-48

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Matthew K Sigurdson (MK)

Department of Health Research and Policy, Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA. Electronic address: msigurds@stanford.edu.

Muin J Khoury (MJ)

Office of Public Health Genomics, Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA.

John P A Ioannidis (JPA)

Department of Health Research and Policy, Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA; Department of Statistics, Stanford University School of Humanities and Science, Stanford University, Stanford, CA, USA; Department of Biomedical Data Science, Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, CA, USA.

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Classifications MeSH

Recherchemedicale.com › Administration des services de santé › Organisation et administration › Rendement › Redundant meta-analyses are common in genetic...
Recherchemedicale.com › Phénomènes génétiques › Variation génétique › Redundant meta-analyses are common in genetic...
Recherchemedicale.com › Phénomènes génétiques › Structures génétiques › Génome › Génome humain › Redundant meta-analyses are common in genetic...
Recherchemedicale.com › Phénomènes génétiques › Génotype › Redundant meta-analyses are common in genetic...
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Recherchemedicale.com › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Méthodologie en recherche épidémiologique › Méta-analyse comme sujet › Redundant meta-analyses are common in genetic...
Recherchemedicale.com › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Épidémiologie moléculaire › Redundant meta-analyses are common in genetic...