Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): explanation and elaboration
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 completene...
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creator | Janssens, A. Cecile J.W Ioannidis, John P.A Bedrosian, Sara Boffetta, Paolo Dolan, Siobhan M Dowling, Nicole Fortier, Isabel Freedman, Andrew N Grimshaw, Jeremy M Gulcher, Jeffrey Gwinn, Marta Hlatky, Mark A Janes, Holly Kraft, Peter Melillo, Stephanie O’Donnell, Christopher J Pencina, Michael J Ransohoff, David Schully, Sheri D Seminara, Daniela Winn, Deborah M Wright, Caroline F van Duijn, Cornelia M Little, Julian Khoury, Muin J |
description | 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. |
doi_str_mv | 10.1016/j.jclinepi.2011.02.003 |
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Cecile J.W ; Ioannidis, John P.A ; Bedrosian, Sara ; Boffetta, Paolo ; Dolan, Siobhan M ; Dowling, Nicole ; Fortier, Isabel ; Freedman, Andrew N ; Grimshaw, Jeremy M ; Gulcher, Jeffrey ; Gwinn, Marta ; Hlatky, Mark A ; Janes, Holly ; Kraft, Peter ; Melillo, Stephanie ; O’Donnell, Christopher J ; Pencina, Michael J ; Ransohoff, David ; Schully, Sheri D ; Seminara, Daniela ; Winn, Deborah M ; Wright, Caroline F ; van Duijn, Cornelia M ; Little, Julian ; Khoury, Muin J</creator><creatorcontrib>Janssens, A. Cecile J.W ; Ioannidis, John P.A ; Bedrosian, Sara ; Boffetta, Paolo ; Dolan, Siobhan M ; Dowling, Nicole ; Fortier, Isabel ; Freedman, Andrew N ; Grimshaw, Jeremy M ; Gulcher, Jeffrey ; Gwinn, Marta ; Hlatky, Mark A ; Janes, Holly ; Kraft, Peter ; Melillo, Stephanie ; O’Donnell, Christopher J ; Pencina, Michael J ; Ransohoff, David ; Schully, Sheri D ; Seminara, Daniela ; Winn, Deborah M ; Wright, Caroline F ; van Duijn, Cornelia M ; Little, Julian ; Khoury, Muin J</creatorcontrib><description>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. 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Cecile J.W</creatorcontrib><creatorcontrib>Ioannidis, John P.A</creatorcontrib><creatorcontrib>Bedrosian, Sara</creatorcontrib><creatorcontrib>Boffetta, Paolo</creatorcontrib><creatorcontrib>Dolan, Siobhan M</creatorcontrib><creatorcontrib>Dowling, Nicole</creatorcontrib><creatorcontrib>Fortier, Isabel</creatorcontrib><creatorcontrib>Freedman, Andrew N</creatorcontrib><creatorcontrib>Grimshaw, Jeremy M</creatorcontrib><creatorcontrib>Gulcher, Jeffrey</creatorcontrib><creatorcontrib>Gwinn, Marta</creatorcontrib><creatorcontrib>Hlatky, Mark A</creatorcontrib><creatorcontrib>Janes, Holly</creatorcontrib><creatorcontrib>Kraft, Peter</creatorcontrib><creatorcontrib>Melillo, Stephanie</creatorcontrib><creatorcontrib>O’Donnell, Christopher J</creatorcontrib><creatorcontrib>Pencina, Michael J</creatorcontrib><creatorcontrib>Ransohoff, David</creatorcontrib><creatorcontrib>Schully, Sheri D</creatorcontrib><creatorcontrib>Seminara, Daniela</creatorcontrib><creatorcontrib>Winn, Deborah M</creatorcontrib><creatorcontrib>Wright, Caroline F</creatorcontrib><creatorcontrib>van Duijn, Cornelia M</creatorcontrib><creatorcontrib>Little, Julian</creatorcontrib><creatorcontrib>Khoury, Muin J</creatorcontrib><title>Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): explanation and elaboration</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>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. 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subjects | Checklist Epidemiology Genetic Research Genetics Genome-Wide Association Study - standards Genomics - methods Health risk assessment Humans Internal Medicine Macular degeneration Medical research Models, Genetic Publishing - standards Studies |
title | Strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS): explanation and elaboration |
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