Health Rep. 2026 May 20;37(5):15-25. doi: 10.25318/82-003-x202600500002-eng.
ABSTRACT
BACKGROUND: Breast cancer is the most commonly diagnosed cancer among women in Canada. Breast density substantially influences breast cancer risk and mammography performance. However, OncoSim-Breast, a Canadian microsimulation model representing breast cancer control, including cancer onset, screening, and survival, has not previously explicitly accounted for breast density. This study describes the incorporation of density-specific parameters into the OncoSim-Breast model.
DATA AND METHODS: Breast density-specific inputs were integrated into OncoSim-Breast using data from five Canadian provinces. Three key parameters – prevalence, relative risk of breast cancer, and digital mammography performance (sensitivity and specificity) – were estimated by age group and breast density category, following the American College of Radiology’s Breast Imaging Reporting and Data System (BI-RADS) classification (categories A to D). Calibration experiments and internal validations were conducted to ensure the updated OncoSim-Breast model aligned with observed data from the Canadian Cancer Registry.
RESULTS: The prevalence of dense breasts declined with age: BI-RADS categories C and D accounted for 58% of women younger than 50 years and 26% of those aged 70 and older. Digital mammography sensitivity also decreased with increasing density: among women younger than 50 years, sensitivity was 88% for Category A and 69% for Category D. The updated OncoSim-Breast model accurately replicated age-specific incidence, age-adjusted incidence, and stage distribution based on historical data from the Canadian Cancer Registry (2010 to 2019).
INTERPRETATION: Incorporating breast density-specific parameters substantially improved the accuracy and policy relevance of OncoSim-Breast. The updated model provides a validated tool to inform screening policy decisions for Canadian women, allowing consideration for the effect of the variability of breast density among women.
PMID:42166779 | DOI:10.25318/82-003-x202600500002-eng
