Highlight
Personalized Risk Stratification
Screening strategies based on 5-year absolute risk of invasive breast cancer demonstrated superior performance compared to traditional age-based biennial screening.
Reduced Harms
Risk-based approaches were associated with an 8% to 23% reduction in false-positive recalls, significantly lowering the burden of over-screening.
Enhanced Efficacy
The most effective risk-based models averted up to 6% more deaths than standard age-based protocols (B40-74).
Introduction and Clinical Context
For decades, breast cancer screening guidelines in the United States have primarily relied on chronological age as the primary determinant for initiation and frequency. While the U.S. Preventive Services Task Force (USPSTF) and other bodies have refined these age-based benchmarks—most recently lowering the starting age to 40 for biennial screening—this ‘one-size-fits-all’ approach does not account for the significant heterogeneity in individual risk. Clinical medicine is rapidly shifting toward precision prevention, where interventions are calibrated based on absolute risk rather than demographic averages. The challenge has been to provide robust evidence that a risk-stratified approach can maintain or improve mortality benefits while mitigating the well-documented harms of screening, such as false-positive results and subsequent unnecessary biopsies.
Study Design and Methodology
This decision analytical modeling study utilized data from the Cancer Intervention and Surveillance Modeling Network (CISNET). Researchers employed two independent, established models to simulate a cohort of US women born in 1980, followed from age 40 through their lifetime. The study, conducted between April 2023 and April 2025, compared 50 different screening strategies: 3 traditional age-based strategies and 47 risk-based strategies.The risk-based interventions utilized digital breast tomosynthesis (DBT) and were guided by the Breast Cancer Surveillance Consortium (BCSC) version 3 calculator. This validated tool estimates a woman’s 5-year absolute risk of invasive breast cancer by incorporating factors such as age, race/ethnicity, family history of breast cancer, history of breast biopsy, and breast density. For the purposes of the model, women were categorized into four risk tiers: low, average, intermediate, and high. The primary outcomes measured were the lifetime number of breast cancer deaths averted and the number of false-positive screening recalls per 1000 women.
Key Findings: Risk-Based vs. Age-Based Outcomes
The study’s results suggest a paradigm shift in how we conceptualize population-level screening. Nine specific risk-based strategies were found to be superior or non-inferior to the standard biennial age-based screening from ages 40 to 74 (B40-74).
Mortality Reduction and Life-Years Gained
The mean number of breast cancer deaths averted in the B40-74 age-based group was 6.8 per 1000 women. In contrast, risk-based strategies achieved a range of 6.8 to 7.5 deaths averted. One particularly effective hybrid strategy involved:
- Biennial screening for low-risk women (ages 55-74), average-risk women (ages 50-59), intermediate-risk women (ages 45-54), and high-risk women (ages 40-49).
- Annual screening for average-risk women (ages 60-74), intermediate-risk women (ages 55-74), and high-risk women (ages 50-74).
This specific approach was associated with a 6% increase in deaths averted compared to the standard B40-74 protocol.
Significant Mitigation of Screening Harms
Perhaps the most compelling argument for risk-based screening is the reduction in false positives. The B40-74 strategy resulted in an average of 1365 false-positive recalls per 1000 women. The risk-based strategies reduced this number to between 1050 and 1257. This represents an 8% to 23% reduction in the clinical and psychological burden of false-positive results. By concentrating screening efforts on those with the highest absolute risk, the healthcare system can avoid the ‘noise’ generated by over-screening low-risk populations.
Expert Commentary and Clinical Interpretation
The findings from Alagoz et al. provide a rigorous quantitative foundation for personalizing breast cancer screening. In clinical practice, the transition from age-based to risk-based screening requires a shift in how clinicians communicate with patients. Instead of simply telling a patient they are ‘due for a mammogram because they turned 40,’ the conversation evolves into a discussion about their 5-year absolute risk score.The BCSC v3 calculator is a critical tool in this transition. By integrating breast density and family history, it provides a more nuanced view of risk than age alone. The CISNET modeling confirms that when we use these data-driven insights to adjust the frequency of screening (e.g., annual vs. biennial), we optimize the benefit-to-harm ratio. However, implementation challenges remain. These include the logistical burden of calculating risk scores for every patient, the need for integrated electronic health record (EHR) tools, and ensuring equitable access to high-quality risk assessment across diverse populations.
Limitations and Considerations
While the decision analytical model is robust, it is a simulation based on specific cohort data (women born in 1980). The models assume 100% adherence to screening intervals, which rarely occurs in real-world clinical settings. Furthermore, while DBT was the primary modality studied, the introduction of newer technologies or supplemental screening (like MRI for very high-risk individuals) might further alter the cost-benefit landscape. The study also focuses on invasive breast cancer; the implications for ductal carcinoma in situ (DCIS) management within a risk-based framework warrant further investigation.
Conclusion
The study by Alagoz and colleagues marks a significant milestone in the evolution of preventive oncology. Population-level risk-based screening using 5-year invasive breast cancer risk offers a clear advantage over traditional age-based approaches by increasing the number of deaths averted while simultaneously reducing the incidence of false-positive recalls. As the medical community continues to embrace personalized medicine, these findings suggest that the future of breast cancer screening lies in individual risk profiles, ensuring that the right women receive the right intensity of screening at the right time.
References
1. Alagoz O, Lu Y, Gil Quessep E, et al. Five-Year Absolute Risk-Based and Age-Based Breast Cancer Screening in the US. JAMA Netw Open. 2026;9(1):e2552944. doi:10.1001/jamanetworkopen.2025.52944.2. Breast Cancer Surveillance Consortium (BCSC) Risk Calculator, Version 3. Available at: https://www.bcsc-research.org/.3. Mandelblatt JS, et al. Collaborative Modeling of the Benefits and Harms of Associated With Different Compression Mammography Screening Strategies. Ann Intern Med. 2016;164(4):215-225.