Twenty-five years of breast cancer risk models and their applications.

I would like to thank the editors for the invitation to comment on “Projecting Individualized Probabilities of Developing Breast Cancer for White Females Who Are Being Examined Annually” (1) and to recognize coauthors of that article, Louise A. Brinton, David P. Byar, Donald K. Corle, Sylvan B. Green, Catherine Schairer, and John J. Mulvihill, who contributed key insights and analyses. Several features may explain the frequent citations to this paper. 1) It focused on a clinically crucial quantity, absolute risk, namely the probability that a woman with specific risk factors will develop breast cancer over a defined age interval, with allowance for competing risks. 2) Breast cancer is a common cancer for which preventive interventions have been developed. Risk models are most useful in connection with interventions because the absolute risk of breast cancer can be compared with that of other health outcomes in the presence and absence of intervention. 3) The model is simple: only age and answers to five questions about reproductive, family, and medical history are needed. 4) The model (sometimes called the “Gail model”) has been taken up by practitioners and is available at http://www.cancer.gov/ bcrisktool/ as the National Cancer Institute’s (NCI’s) Breast Cancer Risk Assessment Tool (BCRAT). Currently this site is visited over three million times a year. I shall elaborate on the first two points, mention alternative models, and discuss prospects for improving risk models and other applications of absolute risk.