Strengthening the reporting of genetic risk prediction studies: the GRIPS statement

Authors

  • A. Cecile J. W. Janssens,

    1. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
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  • John P. A. Ioannidis,

    1. Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
    2. Biomedical Research Institute, Foundation for Research and Technology, Ioannina, Greece
    3. Department of Medicine, Tufts University School of Medicine, Boston, MA, USA
    4. Center for Genetic Epidemiology and Modeling and Tufts CTSI, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
    5. Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA
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  • Cornelia M. van Duijn,

    1. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
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  • Julian Little,

    1. Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON, Canada
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  • Muin J. Khoury,

    1. Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA, USA
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  • for the GRIPS Group

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    • Membership of the GRIPS Group is provided in the Acknowledgments.


  • This article is being simultaneously published in 2011 in PLoS Medicine, Annals of Internal Medicine, BMJ, Circulation: Cardiovascular Genetics, European Journal of Clinical Investigation, European Journal of Epidemiology, European Journal of Human Genetics, Genetics in Medicine, Genome Medicine, and Journal of Clinical Epidemiology. Reproduced by permission of the authors.

A. C. J. W. Janssens, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands. Tel.: +31-10-7044124; fax: +31-10-7044657; e-mail: a.janssens@erasmusmc.nl

Abstract

Eur J Clin Invest 2011; 41 (9): 1004–1009

Summary Points

  •  The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice.
  •  The number of studies assessing the predictive ability is steadily increasing, but the quality and completeness of reporting vary.
  •  A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines.
  •  These recommendations aim to enhance the transparency of study reporting and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
  •  A detailed Explanation and Elaboration document is published as an accompanying article [1].

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