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  5. Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration

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Article
en
2011

Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration

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en
2011
Vol 26 (4)
Vol. 26
DOI: 10.1007/s10654-011-9551-z

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John P A Ioannidis
John P A Ioannidis

Stanford University

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A. Cecile J.W. Janssens
John P A Ioannidis
Sara Bedrosian
+22 more

Abstract

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 they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. 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, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.

How to cite this publication

A. Cecile J.W. Janssens, John P A Ioannidis, Sara Bedrosian, Paolo Boffetta, Siobhan M. Dolan, Nicole F. Dowling, Isabel Fortier, Andrew N. Freedman, Jeremy Grimshaw, Jeffrey R. Gulcher, Marta Gwinn, Mark A. Hlatky, Holly Janes, Peter Kraft, Stephanie Melillo, Christopher J. O’Donnell, Michael Pencina, David F. Ransohoff, Sheri D. Schully, Daniela Seminara, Deborah M. Winn, Caroline F. Wright, Cornelia M. van Duijn, Julian Little, Muin J. Khoury (2011). Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. , 26(4), DOI: https://doi.org/10.1007/s10654-011-9551-z.

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Publication Details

Type

Article

Year

2011

Authors

25

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1007/s10654-011-9551-z

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