Applications of Personalized Estimates of Absolute Breast Cancer Risk

Abstract

Absolute risk is the probability that a given health outcome will be observed in a defined time period in the presence of competing causes of death. In this commentary I discuss some applications of models of absolute breast cancer risk that account for a woman’s particular risk factors. Such models can be useful in counseling by giving perspective on the level of risk, and as an aid to weighing risks and benefits, as in deciding whether or not to take tamoxifen to prevent breast cancer. Absolute risk models also have applications in public health, such as in designing intervention trials to prevent breast cancer and in assessing the potential reductions in absolute risk of disease that might result from reducing exposures. Other potential public health applications that require models with high discriminatory accuracy are to identify “high risk” subsets of the population that might benefit from a preventive intervention or screening, or to rank members of the population on risk to allocate preventive resources under cost constraints.