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Review
. 2014 Jan 29:12:15.
doi: 10.1186/1741-7015-12-15.

Global collaborative networks on meta-analyses of randomized trials published in high impact factor medical journals: a social network analysis

Ferrán Catalá-López  1 , Adolfo Alonso-Arroyo, Brian Hutton, Rafael Aleixandre-Benavent, David Moher
Affiliations
Review

Global collaborative networks on meta-analyses of randomized trials published in high impact factor medical journals: a social network analysis

Ferrán Catalá-López et al. BMC Med. .

Abstract

Background: Research collaboration contributes to the advancement of knowledge by exploiting the results of scientific efforts more efficiently, but the global patterns of collaboration on meta-analysis are unknown. The purpose of this research was to describe and characterize the global collaborative patterns in meta-analyses of randomized trials published in high impact factor medical journals over the past three decades.

Methods: This was a cross-sectional, social network analysis. We searched PubMed for relevant meta-analyses of randomized trials published up to December 2012. We selected meta-analyses (including at least randomized trials as primary evidence source) published in the top seven high impact factor general medical journals (according to Journal Citation Reports 2011): The New England Journal of Medicine, The Lancet, the BMJ, JAMA, Annals of Internal Medicine, Archives of Internal Medicine (now renamed JAMA Internal Medicine), and PLoS Medicine. Opinion articles, conceptual papers, narrative reviews, reviews without meta-analysis, reviews of reviews, and other study designs were excluded.

Results: Overall, we included 736 meta-analyses, in which 3,178 authors, 891 institutions, and 51 countries participated. The BMJ was the journal that published the greatest number of articles (39%), followed by The Lancet (18%), JAMA (15%) and the Archives of Internal Medicine (15%). The USA, the UK, and Canada headed the absolute global productivity ranking in number of papers. The 64 authors and the 39 institutions with the highest publication rates were identified. We also found 82 clusters of authors (one group with 55 members and one group with 54 members) and 19 clusters of institutions (one major group with 76 members). The most prolific authors were mainly affiliated with the University of Oxford (UK), McMaster University (Canada), and the University of Bern (Switzerland).

Conclusions: Our analysis identified networks of authors, institutions and countries publishing meta-analyses of randomized trials in high impact medical journals. This valuable information may be used to strengthen scientific capacity for collaboration and to help to promote a global agenda for future research of excellence.

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Figures

Figure 1
Figure 1
Selection of publications. Flow chart.
Figure 2
Figure 2
Co-authorship networks. Most productive cluster of authors, applying a threshold of two or more papers signed in co-authorship.
Figure 3
Figure 3
Co-authorship networks. Second most productive cluster of authors, applying a threshold of two or more papers signed in co-authorship.
Figure 4
Figure 4
Co-authorship networks. Main clusters of authors (≥ 15 members), applying a threshold of two or more papers signed in co-authorship.
Figure 5
Figure 5
Co-authorship networks. Main clusters of authors (≤ 14 members), applying a threshold of two or more papers signed in co-authorship.
Figure 6
Figure 6
Co-authorship networks. Main clusters of authors (≤ 11 members), applying a threshold of two or more papers signed in co-authorship.
Figure 7
Figure 7
Co-authorship networks. Main clusters of authors (≤ 6 members), applying a threshold of two or more papers signed in co-authorship.
Figure 8
Figure 8
Institutional networks. Most productive cluster of institutions applying a threshold of three or more papers signed in co-authorship.
Figure 9
Figure 9
Institutional networks. Other relevant clusters of institutions applying a threshold of three or more papers signed in co-authorship.
Figure 10
Figure 10
Global collaborative network between countries. Note: Node sizes are proportional to the number of papers and line thicknesses are proportional to the number of collaborations.
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