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Get Free AccessThe 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.
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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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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