We systematically investigated how 11 overlapping meta-analyses on the association between CYP2C19 loss-of-function alleles and clinical efficacy of clopidogrel could yield contradictory outcomes. The results of the meta-analyses differed because more recent meta-analyses included more primary studies and some had not included conference abstracts. Conclusions differed because between-study heterogeneity and publication bias were handled differently across meta-analyses. All meta-analyses on the clinical end point observed significant heterogeneity and several reported evidence for publication bias, but only one out of eight statistically significant meta-analyses concluded that therefore the association was unproven and one other refrained from quantifying a pooled estimate because of heterogeneity. For the end point stent thrombosis, all meta-analyses reported statistically significant associations with CYP2C19 loss-of-function alleles with no statistically significant evidence for heterogeneity, but only three had investigated publication bias and also found evidence for it. One study therefore concluded that there was no evidence for an association, and one other doubted the association because of a high level of heterogeneity. In summary, meta-analyses on the association between CYP2C19 loss-of-function alleles and clinical efficacy of clopidogrel differed widely with regard to assessment and interpretation of heterogeneity and publication bias. The substantial heterogeneity and publication bias implies that personalized antiplatelet management based on genotyping is not supported by the currently available evidence.

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doi.org/10.1038/gim.2014.76, hdl.handle.net/1765/82413
Genetics in Medicine
Erasmus MC: University Medical Center Rotterdam

Osnabrugge, R., Head, S., Zijlstra, F., ten Berg, J., Hunink, M., Kappetein, A. P., & Janssens, C. (2015). A systematic review and critical assessment of 11 discordant meta-analyses on reduced-function CYP2C19 genotype and risk of adverse clinical outcomes in clopidogrel users. Genetics in Medicine (Vol. 17, pp. 3–11). doi:10.1038/gim.2014.76