Several options are now becoming available for preventive therapy in women at increased risk for breast cancer. A major challenge is to determine which women are at sufficiently high risk to warrant treatment, and who will benefit from such treatment. Standard risk factors have been combined in several models to develop a risk score, and the spread in 10-year risk associated with these models will be examined. Two new features which offer improved prognostic discrimination are breast density and SNP profiles. The former can be routinely read visually, but there is a substantial inter-reader variability, and a goal is to develop automated testing which is reproducible and highly prognostic for risk. SNP profiles consist of panels (now over 70) of low risk but common genes that individually are not useful, but as a panel may add useful information. A discussion of the relative amount of information in classic models, mammographic density, and SNP scores will be presented along with initial estimates of their combined utility. Lastly we look at markers which may be able to predict response to endocrine prophylactic treatment. Currently change in breast density offers the most promise in this arena.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr ES02-2.