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000178510 1001_ $$aArchambault, Alexi N$$b0
000178510 245__ $$aRisk Stratification for Early-Onset Colorectal Cancer Using a Combination of Genetic and Environmental Risk Scores: An International Multi-Center Study.
000178510 260__ $$aOxford$$bOxford Univ. Press$$c2022
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000178510 500__ $$a 2022 Apr 11;114(4):528-539
000178510 520__ $$aIncidence of colorectal cancer (CRC) among individuals aged less than 50 years has been increasing. As screening guidelines lower the recommended age of screening initiation, concerns including the burden on screening capacity and costs have been recognized, suggesting that an individualized approach may be warranted. We developed risk prediction models for early-onset CRC that incorporate an environmental risk score (ERS), including 16 lifestyle and environmental factors, and a polygenic risk score (PRS), of 141 variants.Relying on risk score weights for ERS and PRS derived from studies of CRC at all ages, we evaluated risks for early-onset CRC in 3,486 cases and 3,890 controls aged less than 50 years. Relative and absolute risks for early-onset CRC were assessed according to values of the ERS and PRS. The discriminatory performance of these scores was estimated using the covariate-adjusted area under the receiver operating characteristic curve.Increasing values of ERS and PRS were associated with increasing relative risks for early-onset CRC (odds ratio per standard deviation of ERS = 1.14, 95% confidence interval [CI] = 1.08, 1.20; odds ratio per standard deviation of PRS = 1.59, 95% CI = 1.51, 1.68), both contributing to case-control discrimination (area under the curve = 0.631, 95% CI = 0.615, 0.647). Based on absolute risks, we can expect 26 excess cases per 10,000 men and 21 per 10,000 women, among those scoring at the 90th percentile for both risk scores.Personal risk scores have the potential to identify individuals at differential relative and absolute risk for early-onset CRC. Improved discrimination may aid in targeted CRC screening of younger, high-risk individuals, potentially improving outcomes.
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000178510 7001_ $$aJeon, Jihyoun$$b1
000178510 7001_ $$aLin, Yi$$b2
000178510 7001_ $$aThomas, Minta$$b3
000178510 7001_ $$aHarrison, Tabitha A$$b4
000178510 7001_ $$aBishop, D Timothy$$b5
000178510 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b6$$udkfz
000178510 7001_ $$aCasey, Graham$$b7
000178510 7001_ $$aChan, Andrew T$$b8
000178510 7001_ $$0P:(DE-He78)c259d6cc99edf5c7bc7ce22c7f87c253$$aChang-Claude, Jenny$$b9$$udkfz
000178510 7001_ $$aFigueiredo, Jane C$$b10
000178510 7001_ $$aGallinger, Steven$$b11
000178510 7001_ $$aGruber, Stephen B$$b12
000178510 7001_ $$aGunter, Marc J$$b13
000178510 7001_ $$0P:(DE-He78)0311ebf3415e41860b4e2c56fbae6919$$aGuo, Feng$$b14$$udkfz
000178510 7001_ $$0P:(DE-He78)6c5d058b7552d071a7fa4c5e943fff0f$$aHoffmeister, Michael$$b15$$udkfz
000178510 7001_ $$aJenkins, Mark A$$b16
000178510 7001_ $$aKeku, Temitope O$$b17
000178510 7001_ $$aLe Marchand, Loïc$$b18
000178510 7001_ $$aLi, Li$$b19
000178510 7001_ $$aMoreno, Victor$$b20
000178510 7001_ $$aNewcomb, Polly A$$b21
000178510 7001_ $$aPai, Rish$$b22
000178510 7001_ $$aParfrey, Patrick S$$b23
000178510 7001_ $$aRennert, Gad$$b24
000178510 7001_ $$aSakoda, Lori C$$b25
000178510 7001_ $$aLee, Jeffrey K$$b26
000178510 7001_ $$aSlattery, Martha L$$b27
000178510 7001_ $$aSong, Mingyang$$b28
000178510 7001_ $$aKo Win, Aung$$b29
000178510 7001_ $$aWoods, Michael O$$b30
000178510 7001_ $$aMurphy, Neil$$b31
000178510 7001_ $$aCampbell, Peter T$$b32
000178510 7001_ $$aSu, Yu-Ru$$b33
000178510 7001_ $$aLansdorp-Vogelaar, Iris$$b34
000178510 7001_ $$aPeterse, Elisabeth Fp$$b35
000178510 7001_ $$aCao, Yin$$b36
000178510 7001_ $$aZeleniuch-Jacquotte, Anne$$b37
000178510 7001_ $$aLiang, Peter S$$b38
000178510 7001_ $$aDu, Mengmeng$$b39
000178510 7001_ $$aCorley, Douglas A$$b40
000178510 7001_ $$aHsu, Li$$b41
000178510 7001_ $$aPeters, Ulrike$$b42
000178510 7001_ $$aHayes, Richard B$$b43
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