Hormonal risk factors for breast cancer: identification, chemoprevention, and other intervention strategies.

Abstract

Breast cancer remains a leading cause of female morbidity and mortality worldwide. Many hormonal and genetic risk factors have been identified and have led to the development of mathematical models that can be used in the clinic to give a woman an estimate of her individual risk of developing breast cancer. These models can also be used to identify women who might benefit from breast-cancer chemoprevention with tamoxifen or be suitable for entry into trials with new agents. In this review, we discuss the relative merits of the Gail and Claus risk models. The Claus model is based mainly on family history, whereas the Gail model also includes simple markers of oestrogen exposure. We explore more sophisticated measures of lifetime oestrogen exposure that can be used to improve the discriminatory ability of these models. We also appraise the four trials of breast-cancer chemoprevention, including the trial that has led to licensing of tamoxifen for this indication in the USA. Finally, we discuss other agents and interventions that could be used in the future to improve the efficacy and tolerability of breast-cancer risk reduction.