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J Clin Epidemiol. 2014 May;67(5):487-99. doi: 10.1016/j.jclinepi.2013.10.006. Epub 2014 Jan 8.

Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

Author information

1
Department of Epidemiology, Erasmus University Medical Center, 3015 GE, Rotterdam, The Netherlands.
2
Stanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305-5411, USA; Stanford Prevention Research Center, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305-5411, USA; Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA 94305-5411, USA.
3
Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA; Epidemiology and Genomics Research Program, National Cancer Institute, Bethesda, MD 20892, USA.
4
Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada.
5
Department of Epidemiology, Emory University, Atlanta, GA 30322, USA. Electronic address: cecile.janssens@emory.edu.

Abstract

OBJECTIVES:

Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement.

STUDY DESIGN AND SETTING:

We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted.

RESULTS:

Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model.

CONCLUSION:

Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models.

KEYWORDS:

Epidemiology; GRIPS; Genetic; Reporting guideline; Review; Risk prediction

PMID:
24411311
DOI:
10.1016/j.jclinepi.2013.10.006
[Indexed for MEDLINE]

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