Melanoma Risk Prediction Models
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.
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.
- Sneyd MJ, Cameron C, Cox B. Individual risk of cutaneous melanoma in New Zealand: developing a clinical prediction aid. BMC Cancer. 2014;14:359.
- Fang S, Han J, Zhang M, et al. Joint effect of multiple common SNPs predicts melanoma susceptibility. PloS One. 2013;8(12):e85642.
- Bakos L, Mastroeni S, Bonamigo RR, Melchi F, Pasquini P, Fortes C. A melanoma risk score in a Brazilian population. An Bras Dermatol. Mar-Apr 2013;88(2):226-232.
- Guther S, Ramrath K, Dyall-Smith D, Landthaler M, Stolz W. Development of a targeted risk-group model for skin cancer screening based on more than 100,000 total skin examinations. J Eur Acad Dermatol Venereol. Jan 2012;26(1):86-94
- Williams LH, Shors AR, Barlow WE, Solomon C, White E. Identifying Persons at Highest Risk of Melanoma Using Self-Assessed Risk Factors. J Clin Exp Dermatol Res. 2011;2(6).
- Fortes C, Mastroeni S, Bakos L, et al. Identifying individuals at high risk of melanoma: a simple tool. Eur J Cancer Prev. Sep 2010;19(5):393-400.
- Fears TR, Guerry D 4th, Pfeiffer RM, Sagebiel RW, Elder DE, Halpern A, Holly EA, Hartge P, Tucker MA. Identifying individuals at high risk of melanoma: a practical predictor of absolute risk. J Clin Oncol. 2006 Aug 1;24(22):3590-6.
- Cho E, Rosner BA, Feskanich D, Colditz GA. Risk factors and individual probabilities of melanoma for whites. J Clin Oncol. 2005 Apr 20;23(12):2669-75.
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.
- Wang W, Niendorf KB, Patel D, et al. Estimating CDKN2A carrier probability and personalizing cancer risk assessments in hereditary melanoma using MelaPRO. Cancer Research. Jan 15 2010;70(2):552-559.