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  • Online Resource  (4)
  • American Association for Cancer Research (AACR)  (4)
  • Campbell, Peter T.  (4)
  • Chang-Claude, Jenny  (4)
  • Hoffmeister, Michael  (4)
  • Slattery, Martha L.  (4)
  • 2015-2019  (4)
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  • Online Resource  (4)
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  • American Association for Cancer Research (AACR)  (4)
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  • 2015-2019  (4)
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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2587-2587
    Abstract: Colorectal cancer (CRC) is the second leading cause of cancer deaths in the United States, despite the fact that it is one of the most preventable and treatable cancers when detected early via screening. The current screening guidelines for CRC are based on age, family history of CRC, and previous screening results. However, multiple environmental and lifestyle risk factors have been established or suspected for CRC, as have many common genetic susceptibility loci. It is critical to utilize this information to better stratify individuals into low- and high-risk groups for optimized and personalized screening and intervention recommendations. Using data from two large consortia (8421 CRC cases and 9767 controls): the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colorectal Transdisciplinary study (CORECT), we developed risk prediction models for men and women based on family history, environmental and lifestyle risk factors, and known CRC susceptibility loci identified through genome-wide association studies. We constructed an environmental risk score (E-score) as a weighted sum of 19 established or potential environmental and lifestyle risk factors for CRC with weights obtained from a multivariate logistic regression analysis. Compared to the model that includes only family history, the E-score significantly improves the discriminatory accuracy for both men (AUC = 0.62 vs. 0.53, p-value & lt; 1e-5) and women (AUC = 0.60 vs. 0.52, p-value & lt; 1e-5). Similarly, we also constructed a genetic risk score (G-score) using 50 common variants associated with CRC risk, and the G-score also significantly improves the discriminatory accuracy for both men (AUC = 0.60 vs. 0.53, p-value & lt; 1e-5) and women (AUC = 0.59 vs. 0.52, p-value & lt; 1e-5) over the family history-only model. Compared to the model with family history and E-score, the inclusion of the G-score in the model further improves the discriminatory accuracy for both men (AUC = 0.65 vs. 0.62, p-value = 0.0152) and women (AUC = 0.63 vs. 0.60, p-value = 0.0005). Our risk prediction models are the first to incorporate both comprehensive environmental and lifestyle risk factors, and known CRC common genetic variants. The E- and G-scores are independent risk predictors for CRC, and models that incorporate both scores improve the discriminatory accuracy significantly compared to family history-only models. Using risk-factor distributions available from nationally representative data (e.g., NHANES), we will provide absolute-risk estimates of CRC using both the E- and G-scores. We expect our comprehensive models incorporating both environmental and genetic risk factors to provide more accurate estimation of CRC, which will be useful for recommending individually tailored screening and intervention strategies to prevent this common cancer. Citation Format: Jihyoun Jeon, Sonja I. Berndt, Hermann Brenner, Peter T. Campbell, Andrew T. Chan, Jenny Chang-Claude, Mengmeng Du, Graham Giles, Jian Gong, Stephen B. Gruber, Tabitha A. Harrison, Michael Hoffmeister, Loic LeMarchand, Li Li, John D. Potter, Gad Rennert, Robert E. Schoen, Martha L. Slattery, Emily White, Michael O. Woods, Ulrike Peters, Li Hsu. Comprehensive colorectal cancer risk prediction to inform personalized screening and intervention. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2587.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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    detail.hit.zdb_id: 410466-3
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  • 2
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 26, No. 5_Supplement ( 2017-05-01), p. B17-B17
    Abstract: This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR17) of the Conference Proceedings. Citation Format: Jihyoun Jeon, Sonja I. Berndt, Hermann Brenner, Peter T. Campbell, Andrew T. Chan, Jenny Chang-Claude, Mengmeng Du, Graham Giles, Jian Gong, Stephen B. Gruber, Tabitha A. Harrison, Michael Hoffmeister, Loic LeMarchand, Li Li, John D. Potter, Gad Rennert, Robert E. Schoen, Martha L. Slattery, Emily White, Michael O. Woods, Ulrike Peters, Li Hsu. Comprehensive colorectal cancer risk prediction to inform personalized screening and intervention. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B17.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
    detail.hit.zdb_id: 2036781-8
    detail.hit.zdb_id: 1153420-5
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  • 3
    In: Cancer Epidemiology, Biomarkers & Prevention, American Association for Cancer Research (AACR), Vol. 26, No. 5_Supplement ( 2017-05-01), p. PR17-PR17
    Abstract: Background and Aims: Colorectal cancer (CRC) is one of the most preventable and treatable cancers when detected early via screening. The current screening guidelines for CRC recommend exams only based on age, family history, and previous screening results. Multiple environmental and lifestyle risk factors, however, have been established or suspected for CRC, as have many common genetic susceptibility loci. It is critical to utilize this information to better stratify individuals into low- and high-risk groups for optimized and personalized screening and intervention recommendations. Methods: Using data from two large consortia (8421 CRC cases and 9767 controls): the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colorectal Transdisciplinary study (CORECT), we developed risk prediction models for men and women based on family history, environmental and lifestyle risk factors, and known CRC susceptibility loci identified through genome-wide association studies. We constructed an environmental risk score (E-score) as a weighted sum of 19 established or potential environmental and lifestyle risk factors for CRC with weights obtained from a multivariate logistic regression analysis. Similarly, we also constructed a genetic risk score (G-score) using 64 common variants associated with CRC risk. We evaluated the discriminatory accuracy of risk prediction models by calculating the area under the Receiver Operating Characteristic curve (AUC), correcting for potential overestimating by using the training data set. Our models also estimate absolute risk of developing CRC given various risk profiles, and provide recommended ages for the first endoscopic screening exam. Results: Both the E-score and the G-score are independent predictors of CRC risk, and models that incorporate both scores improve the discriminatory accuracy significantly compared to family history-only models. Compared to the model that includes only family history, the E-score significantly improves the discriminatory accuracy for both men (AUC = 0.62 vs. 0.53, p-value & lt; 1e-5 ) and women (AUC = 0.60 vs. 0.52, p-value & lt; 1e-5 ). The G-score also significantly improves the discriminatory accuracy for both men (AUC = 0.60 vs. 0.53, p-value & lt; 1e-5 ) and women (AUC = 0.60 vs. 0.52, p-value & lt; 1e-5 ) over the family history-only model. Compared to the model with family history and E-score, the inclusion of the G-score in the model further improves the discriminatory accuracy for both men (AUC = 0.65 vs. 0.62, p-value = 0.0152) and women (AUC = 0.63 vs. 0.60, p-value = 0.0005). Based on the 10-year risk estimates of developing CRC, the difference in recommended age to start screening for the top 90% and the bottom 10% of risk score ranges from 12 to 14 years depending on sex and status of CRC family history. Conclusions: Our risk prediction models incorporating both comprehensive environmental and lifestyle risk factors, and known CRC common genetic variants provide more accurate estimation of CRC risk. These models will be useful for recommending individually tailored screening and intervention strategies to prevent this common cancer. This abstract is also being presented as Poster B17. Citation Format: Jihyoun Jeon, Sonja I. Berndt, Hermann Brenner, Peter T. Campbell, Andrew T. Chan, Jenny Chang-Claude, Mengmeng Du, Graham Giles, Jian Gong, Stephen B. Gruber, Tabitha A. Harrison, Michael Hoffmeister, Loic LeMarchand, Li Li, John D. Potter, Gad Rennert, Robert E. Schoen, Martha L. Slattery, Emily White, Michael O. Woods, Ulrike Peters, Li Hsu. Comprehensive colorectal cancer risk prediction to inform personalized screening and intervention. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr PR17.
    Type of Medium: Online Resource
    ISSN: 1055-9965 , 1538-7755
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 630-630
    Abstract: Background: Smoking has been associated with colorectal cancer (CRC) risk; but limited evidence has shown the association between smoking and molecular subtypes of CRC. Methods: We analyzed 9,422 CRC cases and 9,950 controls from 10 observational studies. Multinomial logistic regression analysis was performed to assess the association between sex-study-specific quartiles of pack years of smoking and risk of CRC molecular subtypes, using non-smokers as reference group, adjusting for age, sex, and study. Known oncogenic mutations in four somatic colorectal tumor markers were assessed individually and in combination, including BRAF mutations, KRAS mutations, CpG island methylator phenotype (CIMP), and microsatellite instability (MSI) status. Case-only analysis was also performed to estimate heterogeneity in risk of molecular subtypes of CRC. Results: Compared with controls, higher pack years of smoking were statistically significantly associated with increased CRC risk when stratified, individually, by all four markers, and the associations got stronger with higher quartiles pack years (p-trend & lt;0.001). Associations between smoking and CRC risk also differed significantly among molecular subtypes. Compared to nonsmokers, the risk of BRAFmut CRC was 83% higher for smokers within the highest quartile of pack-years (OR=1.83; 95% CI: 1.50, 2.25), and 29% higher for BRAFwt CRC (OR=1.29; 95% CI: 1.17, 1.43; Ratio of ORs (ROR)=1.45; 95% CI: 1.18, 1.17; p=3.45x10-4). Similarly, heavy pack-years of smoking was associated with almost two times higher risk of CIMP-high CRC (OR=1.93; 95% CI: 1.60, 2.31), but only 33% higher risk of CIMP-low/negative CRC (OR=1.33; 95% CI: 1.19, 1.48; ROR=1.49; 95% CI: 1.24, 1.79; p=1.72x10-5). The association between smoking and CRC was also stronger in MSI-high tumors (ORMSI-H=1.65; 95% CI: 1.36, 2.00; ORMSI-L/MSS=1.37; 95% CI: 1.23, 1.52; ROR=1.22; 95% CI: 1.00, 1.48; p=0.046). In contrast, the association between smoking and CRC risk was stronger for KRASwt (OR=1.43; 95% CI: 1.27, 1.60), than KRASmut tumors (OR=1.18; 95% CI: 1.02, 1.37; ROR=0.83; 95% CI: 0.71, 0.97; p =0.016). When combining tumor markers, smoking was found to be significantly associated with higher risk of colorectal tumors from the serrated pathway. Conclusion: In this largest study with a total of 19,372 subjects, we found that heavier pack years of smoking was associated with increased risk of all CRC molecular subtypes. Smokers with heavier pack-years of smoking had particularly higher risk of CRC subtypes with BRAF mutation and CIMP-high, suggesting smoking may be particularly involved in the development of these subtypes of colorectal tumor. Citation Format: Xiaoliang Wang, Efrat Amitay, Barbara L. Banbury, Hermann Brenner, Daniel D. Buchanan, Peter T. Campbell, Jenny Chang-Claude, Steven J. Gallinger, Graham G. Giles, Tabitha A. Harrison, John L. Hopper, Mark A. Jenkins, Yi Lin, Reiko Nishihara, Polly A. Newcomb, Shuji Ogino, Lori C. Sakoda, Robert E. Schoen, Martha L. Slattery, Steven N. Thibodeau, Bethany Van Guelpen, Michael O. Woods, Li Hsu, Michael Hoffmeister, Ulrike Peters. Smoking is associated with risks of molecular subtypes of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 630.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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