Impact of Population-Based Pathogenic Variant Testing on Risk-Based Breast Screening Recommendations

In 2025, the Women Informed to Screen Depending on Measures of Risk (WISDOM) study demonstrated the safety of risk-based breast cancer screening compared with annual mammography. This risk-based screening algorithm assigns screenings based on the results of panel-based testing for pathogenic variants (PVs) in nine breast cancer genes, along with a clinical risk model and polygenic risk scores (PRS). These scores help predict breast cancer risk based on the combined effects of common genetic variants.  

While risk-based screening has emerged as a viable alternative to annual mammography, more research is needed to guide implementation. Dr. Yiwey Shieh, Nanette Laitman Clinical Scholar in Healthcare Policy and Research/Prevention-Women's Health, and assistant professor of population health sciences and medicine, and colleagues assessed the proportion of women with PVs in breast cancer genes who would receive high-risk screening using models based on clinical risk alone versus clinical risk plus polygenic risk. Given that WISDOM took the unprecedented step of testing for PVs in all participants undergoing risk-based screening, rather than based on specific criteria, the goal of this analysis was to understand how different types of risk assessments, such as PV testing or risk models, contribute to identifying women with extremely high risk of breast cancer in the general population.  

Published in JAMA Oncology, results from the study show that without information from PV testing, most WISDOM participants with PVs in breast cancer genes would not have been recommended for high-risk screening in the form of breast MRI alternating with mammography every six months, based on clinical risk or clinical plus polygenic risk. This suggests that reliance on clinical risk models or clinical plus polygenic risk models alone would fail to identify many PV carriers who, under current guideline-based recommendations, would be assigned to high-risk screening. As such, the study underscores the importance of PV testing in parallel with clinical and polygenic risk models as critical components of risk-based screening algorithms. Moreover, the study informs operationalization and coverage of unrestricted PV testing for breast cancer genes.