A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors.


Journal

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
ISSN: 1538-7755
Titre abrégé: Cancer Epidemiol Biomarkers Prev
Pays: United States
ID NLM: 9200608

Informations de publication

Date de publication:
03 2020
Historique:
received: 23 08 2019
revised: 29 10 2019
accepted: 07 01 2020
pubmed: 15 1 2020
medline: 27 4 2021
entrez: 15 1 2020
Statut: ppublish

Résumé

Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention. A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases ( The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74-1.45) for men and 0.86 (0.64-1.20) for women, and for clinic-based relatives were 1.15 (0.87-1.58) for men and 1.04 (0.76-1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60-0.78) for men and 0.70 (0.62-0.77) for women, and for clinic-based relatives were 0.77 (0.69-0.84) for men and 0.68 (0.60-0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) for men and 0.10 (0.04-0.16) for women, and for clinic-based relatives were 0.11 (0.05-0.17) for men and 0.11 (0.06-0.17) for women. Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model. Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

Identifiants

pubmed: 31932410
pii: 1055-9965.EPI-19-0929
doi: 10.1158/1055-9965.EPI-19-0929
pmc: PMC7060114
mid: NIHMS1549629
doi:

Substances chimiques

Biomarkers, Tumor 0

Types de publication

Journal Article Multicenter Study Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

549-557

Subventions

Organisme : NIEHS NIH HHS
ID : P30 ES010126
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA074799
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA074794
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA167551
Pays : United States
Organisme : NCI NIH HHS
ID : N01PC35142
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA236558
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA097735
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA074783
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA074799
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA074800
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA074800
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA074783
Pays : United States
Organisme : NCI NIH HHS
ID : N01 CN067009
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA170122
Pays : United States
Organisme : NCI NIH HHS
ID : U24 CA097735
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA074794
Pays : United States
Organisme : NCI NIH HHS
ID : K05 CA152715
Pays : United States
Organisme : NCI NIH HHS
ID : UM1 CA167551
Pays : United States

Informations de copyright

©2020 American Association for Cancer Research.

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Auteurs

Yingye Zheng (Y)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington.

Xinwei Hua (X)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.
Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington.

Aung K Win (AK)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Genetic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia.

Robert J MacInnis (RJ)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.
Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia.

Steven Gallinger (S)

Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada.

Loic Le Marchand (LL)

Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.

Noralane M Lindor (NM)

Department of Health Science Research, Mayo Clinic Arizona, Scottsdale, Arizona.

John A Baron (JA)

Department of Medicine, University of North Carolina School of Medicine, and Department of Epidemiology, Gillings School of Global Public Health, Chapel Hill, North Carolina.

John L Hopper (JL)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.

James G Dowty (JG)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.

Antonis C Antoniou (AC)

Cancer Research UK, Genetic Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Jiayin Zheng (J)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington.

Mark A Jenkins (MA)

Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.

Polly A Newcomb (PA)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington. pnewcomb@fredhutch.org.
Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington.

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