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Inclusion of New Risk Factors Can Improve Prediction of Invasive Breast Cancer


UCSF researchers update Breast Cancer Surveillance Consortium model to account for BMI and other familial risk factors

Breast cancer is the most commonly diagnosed cancer in women – with the exception of skin cancer – accounting for 31 percent of all new female cancer diagnoses in 2022.  Yet, determining who is most at risk of breast cancer is still a challenge for the medical community. Physicians use risk assessment models to determine when to start screening, frequency of screening and need for primary prevention.

The Breast Cancer Surveillance Consortium (BCSC) risk assessment calculator is a validated assessment tool for guiding decisions about prevention and screening. The current model uses information about a woman’s age, race and ethnicity, first-degree family history of breast cancer, breast density, and benign breast biopsy results to estimate a woman’s 5- and 10-year absolute risk of developing invasive breast cancer.

In a study published November 17, 2023 in the Journal of Clinical Oncology, UC San Francisco researchers analyzed data from over five million screening and diagnostic mammograms to develop an updated BCSC model for invasive breast cancer to include additional risk factors including body mass index (BMI), second degree relatives with a family history of breast cancer, and age at first live birth to improve model prediction.

“The new BCSC model updates an already well calibrated and validated breast cancer risk assessment tool to include additional important risk factors,” said Jeffrey Tice, MD, UCSF professor of Medicine, specializing in breast cancer risk assessment. “The inclusion of BMI was associated with the largest improvement in estimated risk for individual women.”

The researchers analyzed data from 1,455,493 women aged 35-79 without a history of breast cancer. During an average follow-up period of 7.3 years, 30,266 women were diagnosed with invasive breast cancer. The new BCSC model (v3) improved prediction of the 5-year risk compared with the BCSC (v2) model. The new model showed the most improvement among Asians, Whites and Blacks. Among women with a BMI of 30.0-34.9 kg/m2 (obese level I), the true-positive rate in women with an estimated 5-year risk of 3% or higher increased from 10.0% (v2) to 19.8% (v3), and the improvement was even greater among women with a BMI greater than or equal to 35 kg/m2 (obese II/III) – from 7.6% to 19.8%.

In addition, current guidelines for the use of medicines to lower a woman’s risk for breast cancer are based on a women’s risk for invasive cancer in the next 5 years. The BCSC model is particularly useful to help guide decision-making in this context.

"The BCSC risk model is recommended by the United States Preventive Services Task Force to identify women eligible for primary prevention with tamoxifen or an aromatase inhibitor.  Incorporating body mass index into the model more accurately identifies overweight and obese women eligible for taking medication to reduce their risk of breast cancer." said senior author Karla Kerlikowske, MD, UCSF professor in the Departments of Medicine and Epidemiology and Biostatistics and co-PI of the BCSC.

The BCSC model was the first to incorporate clinical mammographic breast density. Where breast tissue is dense, a mammogram of the tissue appears cloudy or opaque, making it more challenging to accurately detect cancer at its earliest stages and increasing breast cancer risk.

The BCSC model provides risk information specific to the woman’s breast density assessment as well as other risk factors. Her 5- and 10-year risk for invasive cancer is estimated and the risk for an average woman of her age and race/ethnicity is provided for comparison and context.

“The updated BCSC model can help provide context for discussions between patients and their providers when a woman learns that she has dense breasts on her mammogram,” said Tice.

The research team will continue to use the BCSC database to help improve screening and surveillance. Tice hopes the findings will contribute to public health efforts to promote a more efficient risk-based screening approach to reduce breast cancer disparities.


Additional authors include: Charlotte C. Gard, PhD, MBA, Diana L. Miglioretti, PhD, Brian L. Sprague, PhD, Michael C. S. Bissell, PhD, and Louise M. Henderson, PhD

Funding: Breast Cancer Surveillance Consortium program project (P01CA154292). Data collection for this work was additionally supported, in part, by funding from the National Cancer Institute (U54CA163303) and the Agency for Health Research and Quality (R01 HS018366-01A1) and a Patient-Centered Outcomes Research Institute (PCORI) Award (PCS-1504-30370).

About the Breast Cancer Surveillance Consortium: BCSC is a collaborative network of breast imaging registries conducting research to assess and improve the delivery and quality of breast cancer screening and related patient outcomes in the United States. The nationwide research network uses community-based data collection from geographically and socio-demographically diverse settings and has a long history of evaluating the benefits and harms of different screening approaches.

About UCSF Health: UCSF Health is recognized worldwide for its innovative patient care, reflecting the latest medical knowledge, advanced technologies and pioneering research. It includes the flagship UCSF Medical Center, which is a top-ranked specialty hospital, as well as UCSF Benioff Children’s Hospitals, with campuses in San Francisco and Oakland, Langley Porter Psychiatric Hospital and Clinics, UCSF Benioff Children’s Physicians and the UCSF Faculty Practice. These hospitals serve as the academic medical center of the University of California, San Francisco, which is world-renowned for its graduate-level health sciences education and biomedical research. UCSF Health has affiliations with hospitals and health organizations throughout the Bay Area. Visit Follow UCSF Health on Facebook or on Twitter.