Submission Form for Peer-Reviewed Cancer Risk Prediction Models

The Epidemiology and Genomics Research Program (EGRP) strives to keep our list of peer-reviewed cancer risk prediction models as comprehensive and up-to-date as possible. If you have information about a model you would like to be considered for inclusion on this list, submit as much information as possible through the form below. For questions, contact Andrew N. Freedman, Ph.D.


Type of Model:

Based on following definition:
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.

Based on following definition:
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.

Based on following definition:
These models were constructed based on a group of individuals with certain conditions or diseases predisposing them to develop cancer.

Type of Cancer: *