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Commentary: Meta-analysis of Individual Participants' Data in Genetic Epidemiology
Author(s) -
John P. A. Ioannidis
Publication year - 2002
Publication title -
american journal of epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.33
H-Index - 256
eISSN - 1476-6256
pISSN - 0002-9262
DOI - 10.1093/aje/kwf031
Subject(s) - standardization , computer science , meta analysis , genetic epidemiology , data science , linkage disequilibrium , event (particle physics) , data mining , medicine , risk analysis (engineering) , epidemiology , biology , genetics , pathology , physics , quantum mechanics , genotype , haplotype , gene , operating system
The authors summarize their experience in the conduct of meta-analysis of individual participants' data (MIPD) with time-to-event analyses in the field of genetic epidemiology. The MIPD offers many advantages compared with a meta-analysis of the published literature. These include standardization of case definitions, outcomes, and covariates; inclusion of updated information; the ability to fully test the assumptions of time-to-event models; better control of confounding; standardization of analyses of genetic loci that are in linkage disequilibrium; evaluation of alternative genetic models and multiple genes; consistent treatment of subpopulations; assessment of sampling bias; and the establishment of an international collaboration with the capability to prospectively update the meta-analyses and synthesize new information on multiple genetic loci and outcomes. The disadvantages of a MIPD compared with a meta-analysis of the published literature are that a much greater commitment of time and resources is required to collect primary data and to coordinate a large collaborative project. An MIPD may collect additional, unpublished data, but it is possible that not all published data may be contributed at the individual level. For questions that justify the required intensive effort, the MIPD method is a useful tool to help clarify the role of candidate genes in complex human diseases.

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