%0 Journal Article
%A Jeon, Jihyoun
%A Du, Mengmeng
%A Schoen, Robert E
%A Hoffmeister, Michael
%A Newcomb, Polly A
%A Berndt, Sonja I
%A Caan, Bette
%A Campbell, Peter T
%A Chan, Andrew T
%A Chang-Claude, Jenny
%A Giles, Graham G
%A Gong, Jian
%A Harrison, Tabitha A
%A Huyghe, Jeroen R
%A Jacobs, Eric J
%A Li, Li
%A Lin, Yi
%A Le Marchand, Loïc
%A Potter, John D
%A Qu, Conghui
%A Bien, Stephanie A
%A Zubair, Niha
%A Macinnis, Robert J
%A Buchanan, Daniel D
%A Hopper, John L
%A Cao, Yin
%A Nishihara, Reiko
%A Rennert, Gad
%A Slattery, Martha L
%A Thomas, Duncan C
%A Woods, Michael O
%A Prentice, Ross L
%A Gruber, Stephen B
%A Zheng, Yingye
%A Brenner, Hermann
%A Hayes, Richard B
%A White, Emily
%A Peters, Ulrike
%A Hsu, Li
%T Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors.
%J Gastroenterology
%V 154
%N 8
%@ 0016-5085
%C Stanford, Calif.
%I HighWire Press
%M DKFZ-2018-00697
%P 2152 - 2164.e19
%D 2018
%X Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening.We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry.In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:29458155
%2 pmc:PMC5985207
%R 10.1053/j.gastro.2018.02.021
%U https://inrepo02.dkfz.de/record/135960