An empirical comparison of meta-analyses of published gene-disease associations versus consortium analyses

Cecile Janssens, AM Gonzalez Zuloeta Ladd, S (Sandra) Lopez Leon, JPA Ioannidis, Ben Oostra, MJ Khoury, Cornelia Duijn

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)

Abstract

Purpose: Consortia of investigators currently compile sufficiently large sample sizes to investigate the effects of low-risk susceptibility genetic variants. It is not clear how the results obtained by consortia compare-with those derived from meta-analyses of published studies. Methods: We performed meta-analyses of published data for 16 genetic polymorphisms investigated by the Breast Cancer Association Consortium, and compared sample sizes, heterogeneity, and effect sizes. PubMed, Web of Science, and Human Gerome Epidemiology Network databases were searched for breast cancer case-control association studies. Results: We found that theta-analyses of published data and consortium analyses were based on substantially different data. Published data by nonconsortium teams amounted on average to 26.9% of all available data (range 3.0 -50.0%). Both approaches showed statistically significant decreased breast cancer risks for CASP8 D302H. The mesa-analyses of published data demonstrated statistically significant results for five other genes and the consortium analyses for two other genes, but the strength of this evidence, evaluated on the basis of the Venice criteria, was not strong. Conclusions: Because both approaches identified the same gene out of 16 candidates, the methods can be complimentary. The expense and complexity of consortium-based studies should be considered vis-a-vis the potential methodological limitations of synthesis of published studies. Genet Med 2009:11(3):153-162.
Original languageUndefined/Unknown
Pages (from-to)153-162
Number of pages10
JournalGenetics in Medicine
Volume11
Issue number3
DOIs
Publication statusPublished - 2009

Research programs

  • EMC MGC-02-96-01
  • EMC NIHES-01-64-03
  • EMC NIHES-02-65-01

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