title: 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.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, 3015 GE, Rotterdam, The Netherlands.
authors.forename: Adriana I
authors.initials: AI
authors.lastname: Iglesias
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, 3015 GE, Rotterdam, The Netherlands.
authors.forename: Raluca
authors.initials: R
authors.lastname: Mihaescu
authors.affiliation: 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.
authors.forename: John P A
authors.initials: JP
authors.lastname: Ioannidis
authors.affiliation: 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.
authors.forename: Muin J
authors.initials: MJ
authors.lastname: Khoury
authors.affiliation: Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada.
authors.forename: Julian
authors.initials: J
authors.lastname: Little
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, 3015 GE, Rotterdam, The Netherlands.
authors.forename: Cornelia M
authors.initials: CM
authors.lastname: van Duijn
authors.affiliation: Department of Epidemiology, Emory University, Atlanta, GA 30322, USA. Electronic address: cecile.janssens@emory.edu.
authors.forename: A Cecile J W
authors.initials: AC
authors.lastname: Janssens
mesh_terms: D036281:Genetic Research; D006801:Humans; D011643:Publishing / Q000592:standards*; D018570:Risk Assessment
keywords: Epidemiology; GRIPS; Genetic; Reporting guideline; Review; Risk prediction