Colorectal Cancer Risk Prediction Models
- Absolute Risk Prediction Models
- Gene Carrier Status Risk Prediction Models
- Other Online Risk Assessment Tools and Calculators
Absolute Risk Prediction Models
Absolute cancer risk is the probability that an individual with given risk factors and a given age will develop cancer over a defined period of time. Examples of these risk factors include race, age, sex, genetics, body mass index, family history of cancer, history of tobacco use, use of aspirin and nonsteroidal anti-inflammatory drugs (NSAIDS), physical activity, use of hormone replacement therapy, reproductive factors, history of cancer screening, and dietary factors.
Developing statistical models that estimate the probability of developing cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk. These types of models also will be useful for designing future chemoprevention and screening intervention trials in individuals at high risk of specific cancers in the general population.
The following risk prediction models are intended primarily for research use and have been peer-reviewed, meaning the methodology and results of these models have been evaluated by qualified scientists and clinicians and published in scientific and medical journals.
- Yarnall JM, Crouch DJ, Lewis CM. Incorporating non-genetic risk factors and behavioural modifications into risk prediction models for colorectal cancer. Cancer Epidemiol. Jan 29 2013.
- Cai QC, Yu ED, Xiao Y, et al. Derivation and Validation of a Prediction Rule for Estimating Advanced Colorectal Neoplasm Risk in Average-Risk Chinese. Am J Epidemiol. Feb 10 2012.
- Lubbe SJ, Di Bernardo MC, Broderick P, Chandler I, Houlston RS. Comprehensive evaluation of the impact of 14 genetic variants on colorectal cancer phenotype and risk. Am J Epidemiol. Jan 1 2012;175(1):1-10.
- Ma E, Sasazuki S, Iwasaki M, Sawada N, Inoue M. 10-Year risk of colorectal cancer: development and validation of a prediction model in middle-aged Japanese men. Cancer Epidemiol. Oct 2010;34(5):534-541.
- Wei EK, Colditz GA, Giovannucci EL, Fuchs CS, Rosner BA. Cumulative risk of colon cancer up to age 70 years by risk factor status using data from the Nurses' Health Study. Am J Epidemiol. Oct 1 2009;170(7):863-872.
- Freedman AN, Slattery ML, Ballard-Barbash R, Willis G, Cann BJ, Pee D, Gail MH, Pfeiffer RM. Colorectal cancer risk prediction tool for white men and women without known susceptibility. J Clin Oncol. Feb 10 2009;27(5):686-693.
- Park Y, Freedman AN, Gail MH, Pee D, Hollenbeck A, Schatzkin A, Pfeiffer RM. Validation of a colorectal cancer risk prediction model among white patients age 50 years and older. J Clin Oncol. Feb 10 2009;27(5):694-698.
- Driver JA, Gaziano JM, Gelber RP, Lee IM, Buring JE, Kurth T. Development of a risk score for colorectal cancer in men. Am J Med. 2007 Mar;120(3):257-63.
- Imperiale TF, Wagner DR, Lin CY, Larkin GN, Rogge JD, Ransohoff DF. Using risk for advanced proximal colonic neoplasia to tailor endoscopic screening for colorectal cancer. Ann Intern Med. 2003 Dec 16;139(12):959-65.
- Selvachandran SN, Hodder RJ, Ballal MS, Jones P, Cade D. Prediction of colorectal cancer by a patient consultation questionnaire and scoring system: a prospective study. Lancet. 2002 Jul 27;360(9329):278-83.
Gene Carrier Status Risk Prediction Models
These models estimate the likelihood of detecting a mutation in a cancer susceptibility gene (e.g., BRCA1 and BRCA2) in a given family or individual.
- Balmana J, Stockwell DH, Steyerberg EW, Stoffel EM, Deffenbaugh AM, Reid JE, Ward B, Scholl T, Hendrickson B, Tazelaar J, Burbidge LA, Syngal S. Prediction of MLH1 and MSH2 mutations in Lynch syndrome. JAMA. 2006 Sep 27;296(12):1469-78.
- Chen S, Wang W, Lee S, Nafa K, Lee J, Romans K, Watson P, Gruber SB, Euhus D, Kinzler KW, Jass J, Gallinger S, Lindor NM, Casey G, Ellis N, Giardiello FM, Offit K, Parmigiani G; Colon Cancer Family Registry. Prediction of germline mutations and cancer risk in the Lynch syndrome. JAMA. 2006 Sep 27;296(12):1479-87.
- Wijnen JT, Vasen HF, Khan PM, Zwinderman AH, van der Klift H, Mulder A, Tops C, Moller P, Fodde R. Clinical findings with implications for genetic testing in families with clustering of colorectal cancer. N Engl J Med. 1998 Aug 20;339(8):511-8.
Other Online Risk Assessment Tools and Calculators
The following cancer risk assessment tools and calculators may be of use for individuals interested in gaining a greater understanding of their risk of developing cancer but are not intended for research purposes. To the best of our knowledge, these tools and calculators have not been evaluated for publication in a peer-reviewed scientific journal, and we do not have information about the process used to develop and validate them.
- Cleveland Clinic Colorectal Cancer Risk Assessment Tool
- Dana Farber Prediction Model for MLH1, MSH2, and MSH6 Gene Mutations (for Lynch Syndrome)