A Systematic Appraisal of Field Synopses in Genetic Epidemiology: A... - PubMed - NCBI
Am J Epidemiol. 2015 Jan 1;181(1):1-16. doi: 10.1093/aje/kwu249. Epub 2014 Dec 11.
A Systematic Appraisal of Field Synopses in Genetic Epidemiology: A HuGE Review.
Abstract
Evidence from genetic association studies is accumulating rapidly. Field synopses have recently arisen as an unbiased way of systematically synthesizing this evidence. We performed a systematic review and appraisal of published field synopses in genetic epidemiology and assessed their main findings and methodological characteristics. We identified 61 eligible field synopses, published between January 1, 2007, and October 31, 2013, on 52 outcomes reporting 734 significant associations at the P < 0.05 level. The median odds ratio for these associations was 1.25 (interquartile range, 1.15-1.43). Egger's test was the most common method (n = 30 synopses) of assessing publication bias. Only 12 synopses (20%) used the Venice criteria to evaluate the epidemiologic credibility of their findings (n = 449 variants). Eleven synopses (18%) were accompanied by an online database that has been regularly updated. These synopses received more citations (P = 0.01) and needed a larger research team (P = 0.02) than synopses without an online database. Overall, field synopses are becoming a valuable tool for the identification of common genetic variants, especially when researchers follow relevant methodological guidelines. Our work provides a summary of the current status of the field synopses published to date and may help interested readers efficiently identify the online resources containing the relevant genetic evidence. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
KEYWORDS:
epidemiologic methods; field synopsis; genetic associations; genetic epidemiology; genome, human; meta-analysis
- PMID:
- 25504025
- [PubMed - in process]
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