Development of a combined database for meta-epidemiological research

Jelena Savović, Ross J. Harris, Lesley Wood, Rebecca Beynon, Doug Altman, Bodil Als-Nielsen, Ethan M. Balk, Jonathan Deeks, Lise Lotte Gluud, Christian Gluud, John P.A. Ioannidis, Peter Jűni, David Moher, Julie Pildal, Kenneth F. Schulz, Jonathan A.C. Sterne*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)


Collections of meta-analyses assembled in meta-epidemiological studies are used to study associations of trial characteristics with intervention effect estimates. However, methods and findings are not consistent across studies. To combine data from 10 meta-epidemiological studies into a single database, and derive a harmonized dataset without overlap between meta-analyses. The database design allowed trials to be contained in different meta-analyses, multiple meta-analyses in systematic reviews, overlapping meta-analyses between systematic reviews, and multiple references to the same trial or review. Unique identifiers were assigned to each reference and used to identify duplicate trials. Sets of meta-analyses with overlapping trials were identified and duplicates removed. Overlapping trials were used to examine agreement between assessments of trial characteristics. The combined database contained 427 reviews, 454 meta-analyses and 4874 trial results. Of these, 258 meta-analyses were unique, while for 196 at least one trial overlapped with another meta-analysis. Median kappa statistics for reliability of assessments were 0.60 for sequence generation, 0.58 for allocation concealment and 0.87 for blinding. Based on inspection of sets of overlapping meta-analyses, 91 meta-analyses containing 1344 trial results were removed. Additionally, 24 duplicated trial results were removed from 16 meta-analyses, to derive a final database containing 363 meta-analyses and 3477 unique trial results. The final database will be used to examine the combined evidence on sources of bias in randomized controlled trials. The strategy used to remove overlap between meta-analyses may be of use for future empirical research.

Original languageEnglish
Pages (from-to)212-225
Number of pages14
JournalResearch Synthesis Methods
Issue number1-3
Publication statusPublished - 2010

Bibliographical note

Funding Information:
We thank Pamela Royle and Matthias Egger for providing data and contributing to the initial stages of this project, and Pete Shiarly for his advice on database design and data management. The meta-epidemiological study contributed by Als-Nielsen et al. was partly funded by the Danish Centre for Evaluation and Health Technology Assessment (DACEHTA).

Publisher Copyright:
© 2010, John Wiley and Sons Ltd.


  • Bias
  • Data management
  • Meta-analysis
  • Meta-epidemiology
  • Systematic reviews


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