Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration.
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.
Janssens, ACJW; Ioannidis, JPA; Bedrosian, S; Boffetta, P; Dolan, SM; Dowling, N; Fortier, I; Freedman, AN; Grimshaw, JM; Gulcher, J; Gwinn, M; Hlatky, MA; Janes, H; Kraft, P; Melillo, S; O'Donnell, CJ; Pencina, MJ; Ransohoff, D; Schully, SD; Seminara, D; Winn, DM; Wright, CF; van Duijn, CM; Little, J; Khoury, MJ
Volume / Issue
Start / End Page
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)