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Updated: Aug 9, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Risk prediction models for familial breast cancer
Antonis C Antoniou1, Douglas F Easton
11CR-UK Genetic Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, UK. antonis@srl.cam.ac.uk
Abstract:
A positive family history of breast cancer, reflecting genetic susceptibility, is one of the strongest risk factors for the disease. A number of breast cancer susceptibility genes have been identified to date, with the most important being BRCA1 and BRCA2. Risk prediction models can be used to identify individuals likely to carry BRCA1 and BRCA2 mutations and individuals at high risk of developing the disease. This information can then be used to target genetic testing, screening and interventions more effectively. In this article, the authors review the risk models that have been developed for familial breast cancer and discuss their applicability, strengths and weaknesses, and present examples of classifying women into risk categories according to the predictions by the various models. The review concludes with a discussion of the ways in which risk models could be improved in the immediate- and long-term future.