title: Determining the familial risk distribution of colorectal cancer: a data mining approach.
abstract: This study was aimed to characterize the distribution of colorectal cancer risk using family history of cancers by data mining. Family histories for 10,066 colorectal cancer cases recruited to population cancer registries of the Colon Cancer Family Registry were analyzed using a data mining framework. A novel index was developed to quantify familial cancer aggregation. Artificial neural network was used to identify distinct categories of familial risk. Standardized incidence ratios (SIRs) and corresponding 95% confidence intervals (CIs) of colorectal cancer were calculated for each category. We identified five major, and 66 minor categories of familial risk for developing colorectal cancer. The distribution the major risk categories were: (1) 7% of families (SIR = 7.11; 95% CI 6.65-7.59) had a strong family history of colorectal cancer; (2) 13% of families (SIR = 2.94; 95% CI 2.78-3.10) had a moderate family history of colorectal cancer; (3) 11% of families (SIR = 1.23; 95% CI 1.12-1.36) had a strong family history of breast cancer and a weak family history of colorectal cancer; (4) 9 % of families (SIR = 1.06; 95 % CI 0.96-1.18) had strong family history of prostate cancer and weak family history of colorectal cancer; and (5) 60% of families (SIR = 0.61; 95% CI 0.57-0.65) had a weak family history of all cancers. There is a wide variation of colorectal cancer risk that can be categorized by family history of cancer, with a strong gradient of colorectal cancer risk between the highest and lowest risk categories. The risk of colorectal cancer for people with the highest risk category of family history (7% of the population) was 12-times that for people in the lowest risk category (60%) of the population. Data mining was proven an effective approach for gaining insight into the underlying cancer aggregation patterns and for categorizing familial risk of colorectal cancer.
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.
authors.forename: Rowena
authors.initials: R
authors.lastname: Chau
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.
authors.forename: Mark A
authors.initials: MA
authors.lastname: Jenkins
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.|Colorectal Oncogenomics Group, Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Parkville, VIC, Australia.
authors.forename: Daniel D
authors.initials: DD
authors.lastname: Buchanan
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.
authors.forename: Driss
authors.initials: D
authors.lastname: Ait Ouakrim
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.|Cancer Epidemiology Centre, The Cancer Council Victoria, Melbourne, Australia.
authors.forename: Graham G
authors.initials: GG
authors.lastname: Giles
authors.affiliation: Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
authors.forename: Graham
authors.initials: G
authors.lastname: Casey
authors.affiliation: Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada.|Cancer Care Ontario, Toronto, ON, Canada.
authors.forename: Steven
authors.initials: S
authors.lastname: Gallinger
authors.affiliation: Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA.
authors.forename: Robert W
authors.initials: RW
authors.lastname: Haile
authors.affiliation: University of Hawaii Cancer Center, Honolulu, HI, USA.
authors.forename: Loic
authors.initials: L
authors.lastname: Le Marchand
authors.affiliation: Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
authors.forename: Polly A
authors.initials: PA
authors.lastname: Newcomb
authors.affiliation: Department of Health Science Research, Mayo Clinic Arizona, Scottsdale, AZ, USA.
authors.forename: Noralane M
authors.initials: NM
authors.lastname: Lindor
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia.
authors.forename: John L
authors.initials: JL
authors.lastname: Hopper
authors.affiliation: Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie Street, Parkville, VIC, 3010, Australia. awin@unimelb.edu.au.
authors.forename: Aung Ko
authors.identifier: http://orcid.org/0000-0002-2794-5261
authors.initials: AK
authors.lastname: Win
mesh_terms: D000368:Aged; D001943:Breast Neoplasms / Q000453:epidemiology; D015179:Colorectal Neoplasms / Q000453:epidemiology* / Q000235:genetics*; D004268:DNA-Binding Proteins / Q000235:genetics; D057225:Data Mining / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D000070976:Mismatch Repair Endonuclease PMS2 / Q000235:genetics; D000070957:MutL Protein Homolog 1 / Q000235:genetics; D051718:MutS Homolog 2 Protein / Q000235:genetics; D009864:Ontario / Q000453:epidemiology; D010375:Pedigree; D011471:Prostatic Neoplasms / Q000453:epidemiology; D012042:Registries; D018570:Risk Assessment; D014481:United States / Q000453:epidemiology; D014739:Victoria / Q000453:epidemiology
chemical_list: D004268:DNA-Binding Proteins; C094443:G-T mismatch-binding protein; C501486:MLH1 protein, human; C094934:PMS2 protein, human; C497172:MSH2 protein, human; D000070976:Mismatch Repair Endonuclease PMS2; D000070957:MutL Protein Homolog 1; D051718:MutS Homolog 2 Protein
keywords: Colorectal cancer; Data mining; Familial aggregation; Familial risk