TY - JOUR
T1 - Strengthening the reporting of genetic risk prediction studies (GRIPS)
T2 - Explanation and elaboration
AU - Janssens, A. Cecile J.W.
AU - Ioannidis, John P.A.
AU - Bedrosian, Sara
AU - Boffetta, Paolo
AU - Dolan, Siobhan M.
AU - Dowling, Nicole
AU - Fortier, Isabel
AU - Freedman, Andrew N.
AU - Grimshaw, Jeremy M.
AU - Gulcher, Jeffrey
AU - Gwinn, Marta
AU - Hlatky, Mark A.
AU - Janes, Holly
AU - Kraft, Peter
AU - Melillo, Stephanie
AU - O'Donnell, Christopher J.
AU - Pencina, Michael J.
AU - Ransohoff, David
AU - Schully, Sheri D.
AU - Seminara, Daniela
AU - Winn, Deborah M.
AU - Wright, Caroline F.
AU - Van Duijn, Cornelia M.
AU - Little, Julian
AU - Khoury, Muin J.
N1 - Funding Information:
Examples: ‘This study was supported by grants from the National Heart, Lung and Blood Institute and National Cancer Institute, National Institutes of Health; the Donald W. Reynolds Foundation; and the Leducq Foundation. Additional support for DNA extraction, reagents and data analysis was provided by Roche Diagnostics and Amgen. Genotyping of the 9p21.3 variant was performed by Celera. The funding sources had no role in the design, conduct, or reporting of this study or the decision to submit the manuscript for publication’.56
PY - 2011/5
Y1 - 2011/5
N2 - 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 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 previous 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.
AB - 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 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 previous 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.
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U2 - 10.1038/ejhg.2011.27
DO - 10.1038/ejhg.2011.27
M3 - Article
C2 - 21407270
AN - SCOPUS:79955781073
SN - 1018-4813
VL - 19
SP - 493
JO - European Journal of Human Genetics
JF - European Journal of Human Genetics
IS - 5
ER -
