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Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort.

Authors :
Su, Y-R
Sakoda, LC
Jeon, J
Thomas, M
Lin, Y
Schneider, JL
Udaltsova, N
Lee, JK
Lansdorp-Vogelaar, I
Peterse, EFP
Zauber, AG
Zheng, J
Zheng, Y
Hauser, E
Baron, JA
Barry, EL
Bishop, DT
Brenner, H
Buchanan, DD
Burnett-Hartman, A
Campbell, PT
Casey, G
Castellví-Bel, S
Chan, AT
Chang-Claude, J
Figueiredo, JC
Gallinger, SJ
Giles, GG
Gruber, SB
Gsur, A
Gunter, MJ
Hampe, J
Hampel, H
Harrison, TA
Hoffmeister, M
Hua, X
Huyghe, JR
Jenkins, MA
Keku, TO
Marchand, LL
Li, L
Lindblom, A
Moreno, V
Newcomb, PA
Pharoah, PDP
Platz, EA
Potter, JD
Qu, C
Rennert, G
Schoen, RE
Slattery, ML
Song, M
van Duijnhoven, FJB
Van Guelpen, B
Vodicka, P
Wolk, A
Woods, MO
Wu, AH
Hayes, RB
Peters, U
Corley, DA
Hsu, L
Su, Y-R
Sakoda, LC
Jeon, J
Thomas, M
Lin, Y
Schneider, JL
Udaltsova, N
Lee, JK
Lansdorp-Vogelaar, I
Peterse, EFP
Zauber, AG
Zheng, J
Zheng, Y
Hauser, E
Baron, JA
Barry, EL
Bishop, DT
Brenner, H
Buchanan, DD
Burnett-Hartman, A
Campbell, PT
Casey, G
Castellví-Bel, S
Chan, AT
Chang-Claude, J
Figueiredo, JC
Gallinger, SJ
Giles, GG
Gruber, SB
Gsur, A
Gunter, MJ
Hampe, J
Hampel, H
Harrison, TA
Hoffmeister, M
Hua, X
Huyghe, JR
Jenkins, MA
Keku, TO
Marchand, LL
Li, L
Lindblom, A
Moreno, V
Newcomb, PA
Pharoah, PDP
Platz, EA
Potter, JD
Qu, C
Rennert, G
Schoen, RE
Slattery, ML
Song, M
van Duijnhoven, FJB
Van Guelpen, B
Vodicka, P
Wolk, A
Woods, MO
Wu, AH
Hayes, RB
Peters, U
Corley, DA
Hsu, L
Publication Year :
2023

Abstract

BACKGROUND: Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance. METHODS: The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group). RESULTS: In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity. CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort. IMPACT: The proposed model has potential utility in risk-stratified colorectal cancer prevention.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1426974695
Document Type :
Electronic Resource