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Open Access Highly Accessed Correspondence

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

A Cecile JW Janssens1*, John PA Ioannidis23456, Cornelia M van Duijn1, Julian Little7, Muin J Khoury8 and the GRIPS Group

Author Affiliations

1 Department of Epidemiology, Erasmus University Medical Center, PO Box 2040, Rotterdam 3000 CA, The Netherlands

2 Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, Ioannina 45110, Greece

3 Biomedical Research Institute, Foundation for Research and Technology-Hellas, University Campus, Ioannina 45110, Greece

4 Department of Medicine, Tufts University School of Medicine, 750 Washington St, Boston, MA 02111, USA

5 Center for Genetic Epidemiology and Modeling and Tufts CTSI, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, 750 Washington St, Boston, MA 02111, USA

6 Stanford Prevention Research Center, Stanford University School of Medicine, 251 Campus Drive, Stanford, CA 94305, USA

7 Department of Epidemiology and Community Medicine, University of Ottawa, 451 Smyth Rd, Ottawa, Ontario K1H 8M5, Canada

8 Office of Public Health Genomics, Centers for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, GA 30333, USA

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Genome Medicine 2011, 3:16  doi:10.1186/gm230

Published: 15 March 2011

Abstract

The rapid and continuing progress in gene discovery for complex diseases is fueling 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 varies. 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 (the GRIPS statement), 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 at http://www.plosmedicine.org webcite.