Evaluating mammographic density’s contribution to improve a breast cancer risk model with questionnaire-based and polygenic factors.

This study assessed the added value of incorporating BI-RADS mammographic breast density into a breast cancer risk model that combines questionnaire-based factors and a 313-variant polygenic risk score (PRS).

Using the iCARE tool, the authors validated the model in three European-ancestry prospective cohorts, totaling 1,468 cases and 19,104 controls, stratified by age.

The inclusion of breast density modestly improved risk discrimination, with the AUC increasing from approximately 65.5% to 66–67%, depending on the age group.

Key findings include:

• In US women aged 50–70: Adding density identified a higher proportion of women at elevated 5-year risk and captured more future cases compared to models without density.
• In the Swedish cohort: Similar, though more modest, improvements were observed.

Overall, integrating breast density with genetic and questionnaire-based factors enhances breast cancer risk stratification and may improve clinical risk assessment for tailored screening and prevention in women of European ancestry.