While the medical field has made great strides in calculating and communicating a woman’s risk of developing breast cancer, one limitation remains at the center of our traditional approach: risk is not static. Hormonal changes, family history, genetic discoveries, biopsies, and lifestyle factors can all modify risk over time. As that risk evolves, screening strategies must evolve with it. Rather than relying on long-term, population-based risk estimates and protocols, we should move toward shorter-term, risk-based strategies that incorporate ongoing reassessment and truly individualized care.
For me, this issue is personal. I carry a BRCA1 gene mutation and have seen in my own family how knowledge of risk and early detection can impact outcomes over generations. My family’s cancer journey continues to shape my philosophy on risk-based screening. Our goal should not just be more testing. It should be the right testing for the right patient at the right time.
The Challenge with Traditional Screening Protocols
Historically, assessment tools like the Tyrer-Cuzick (IBIS) model have been used primarily to calculate an individual’s lifetime risk of developing breast cancer, taking into consideration factors like age, race/ethnicity, reproductive history, family history and breast density. Those who exceed the 20% lifetime risk threshold for developing breast cancer are then placed in a more aggressive screening protocol.
I believe lifetime risk models leave too much room for uncertainty. They can overestimate risk in younger women and underestimate risk in older women, among other limitations.
The WISDOM Trial: A Shift in How We Screen for Breast Cancer
Research supports my views. Recently, the WISDOM (Women Informed to Screen Depending On Measures of Risk) study tested whether a more personalized, five-year risk assessment approach could safely replace routine population-based screening for breast cancer. The results of this prospective, randomized clinical trial were published in JAMA and confirmed four key findings that should shape how we think about breast cancer risk assessment and screening moving forward:
Personalized, risk-based screening did not lead to more advanced cancer diagnoses (Stage 2B or higher), demonstrating that it can be a safe alternative to routine annual screening.
Women overwhelmingly embraced the personalized approach. When given a choice, nearly 90% selected risk-based screening, underscoring the growing demand for more individualized care.
Researchers found that nearly one in 38 women carried a pathogenic breast cancer mutation. About 30% of those women had no family history of the disease and likely would not have been identified under current clinical guidelines. This finding highlights the potential value of broader genetic testing.
Biopsies and other intensive diagnostic procedures could be more effectively concentrated among women at highest risk, while reducing unnecessary interventions for those at average risk.
The Role of AI in Enhancing Breast Cancer Risk Prediction
When it comes to screening, a promising new direction is artificial intelligence. AI-based analysis of mammograms offers the potential to improve risk prediction and advance more precise, individualized breast cancer risk assessment.
In May 2025, Clairity Breast became the first AI mammography-based risk assessment tool to receive De Novo authorization from the FDA. In a cohort study published in JAMA Network Open, Clairity’s deep-learning risk model Mirai outperformed breast density in estimating risk of future breast cancer and stratified false-negative screening results.
More recently, an abstract presented at the 2026 American Society of Clinical Oncology Annual Meeting delved into the clinical implications of incorporating this new AI technology and how it may impact clinical care, comparing it to traditional clinical risk models like Tyrer-Cuzick. The AI model demonstrated the potential to reduce the intensity of short-term breast cancer screening for most patients in a high-risk clinic. In all, these AI-based platforms are outperforming any of our standard clinical risk models.
Moving Beyond Imaging: Building Stronger Education and Comprehensive High-Risk Care
And yet, identifying risk is only the first step. Clinicians also need to understand what that risk means and translate the information they have received into meaningful prevention strategies.
Unfortunately, many clinicians today feel unequipped to counsel patients on breast density implications, genetic testing, and proper MRI usage, as well as behavior modification and prevention medications. We know lifestyle factors can contribute significantly to breast cancer risk. Exercise, nutrition, alcohol use and obesity all remain under-addressed, and they need to be part of the conversation.
The demand for additional support is there. In the WISDOM trial, uptake for preventive interventions was 96% for the breast health decision tool or a breast health specialist consult, and most patients who were polled afterward made changes — whether medication or lifestyle. That is huge.
However, there are very few clinicians formally trained in high-risk breast medicine, and no standard specialty pathway exists.
Ushering in a New Era in Personalized Breast Cancer Prevention
For decades, screening recommendations have been driven largely by age and lifetime risk estimates. Today, advances in genetics, risk modeling and artificial intelligence are giving us the ability to evaluate risk with far greater precision and to adapt screening strategies as that risk evolves.
Yet technology alone is not the answer. As clinicians, our responsibility extends beyond identifying risk. We must help patients understand it, contextualize it and act on it. That means discussing genetic testing when appropriate, addressing modifiable lifestyle factors, considering preventive therapies, and ensuring patients receive the level of screening that matches their individual needs.
