Models for risk assessment and prediction in breast cancer / 中华流行病学杂志

ABSTRACT

In the areas of prevention and life skills counseling for breast cancer, risk assessment and prediction can assist clinicians to decide if chemoprevention or prophylactic surgery is needed or suggestions on improving the quality of life for their clients. Several mathematical models, namely Gail Model, Claus Model, BRCAPRO Model and Cuzick-Tyrer Model etc. have been developed to make predictions, clinically. This paper has reviewed the development, operation, advantage versus disadvantage and areas of application for the four models. Having family history of breast cancer, one subject was calculated on the risks by the four models and different results were found. Up to 45 years old, the accumulative risks from the four models and population risk were 1.9%, 11.8%, 2.5%, 5.0% and i.6%, respectively. To 75 years old, they were 20.2%,32.5%, 13.1%, 25.0% and 8.5%, respectively. The subject had a relatively high breast cancer risk during her lifetime. A new model is supposed to include a variety of important risk factors and to be validated by large scale of case-control samples. Incidence of breast cancer in China had significantly increased during the last ten years, but the research on developing assessment methods of breast cancer risk had never been reported, suggesting that the development of models for Chinese population is necessary.