Meta-analyses and Individual Patient Data (IPD) meta-analyses of genetic association studies are a powerful tool to summarize the scientific evidences, however their application present considerable potential and several pitfalls. We reviewed systematically all published meta-analyses and IPD meta-analyses of genetic association studies in the field of cancer research, searching for relevant studies on the Medline, Embase, and HuGE Reviews Archive databases until January 2009. The association between selected predictors of methodological quality and the year of publication was also evaluated. 144 meta-analyses involving 299 gene-disease associations, and 25 IPD meta-analyses on 83 gene-disease were included. Overall quality of the reports showed a substantial improvement over time, as authors have become more inclusive of primary papers published in all languages since 2005 (P-value = 0.087), as well as statistical heterogeneity and publication bias were evaluated more systematically. Only 35.4% of the meta-analyses, however, adopted a comprehensive bibliographic search strategy to identify the primary reports, 63.9% did not specify the language of the included studies, 39.8% did not test for Hardy-Weinberg Equilibrium (HWE), while 62.2 and 75.9% of the meta-analyses and IPD meta-analyses, respectively, did not declare the scientific rationale for the genetic model chosen. Additionally, the HWE assessment showed a substantial decreasing trend over time (P-value = 0.031) while publication bias was more often evaluated when statistical heterogeneity was actually present (P-value = 0.007). Although we showed a general methodological improvement over time, guidelines on conducting and reporting meta-analyses of genetic association studies are needed to enhance their methodological quality.
- Genetic association study
- Individual patient data meta-analysis
- Publication bias
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