Purpose: To provide personalized outcomes associated with screening and risk-reducing medication among women who are at high-risk of developing breast cancer (i.e., 5-year risk greater than or equal to 3%).

Methods: We used a discrete-event simulation model of breast cancer natural history to evaluate the outcomes of annual mammography and risk reducing medication among high-risk women. The model that follows millions of women from birth to death and captures the variability in distributions of each event. Each simulated woman is assigned a cohort-specific life expectancy which is used to select a date of breast cancer death. We used large observational and clinical trial data to derive input parameters for the model. We compared model outcomes for screening alone vs. screening with a 5-year course of risk reducing medication. We modeled various screening strategies including annual or biennial screening starting at ages 35, 40, 45 and stopping at ages 65 and 74 years. Model outcomes for each strategy included, the benefits of risk-reducing drugs (avoiding breast cancer) and screening (breast cancer stage, breast cancer-specific survival), and harms of screening (false positives, overdiagnosis). We also conducted sensitivity analysis to estimate the effects of uncertainty in model inputs or assumptions on results.

Results: We found that risk reducing medication could result in an additional 28% decrease in invasive breast cancer incidence, 20% decrease in stage IV diagnosis, and a 30% decrease in breast cancer death compared to screening alone starting at age 35. However, potential breast density changes due to risk reducing medication among high-risk women could result in a 19% increase in false positive screening results compared to screening alone. The results varied by the starting age of screening.

Conclusions: Simulation modeling is useful in assessing the relative benefits and harms of screening and risk reducing medication in high-risk women