Factoring in Breast Density Improves Long-Term Risk Models for Breast Cancer
Evidence suggests that the Tyrer-Cuzick model may be improved if breast density is taken into consideration.
Risk assessment models that combine classic risk factors and mammographic breast density may provide long-term predictive value for women with an elevated risk of developing breast cancer, according to a study published in JAMA Oncology.
Early breast screening with mammography and preventive selective estrogen receptor therapy in women with elevated risk for breast cancer provide clinical benefit, but may be improved if guided by effective risk-assessment models. Recent evidence suggests that the Tyrer-Cuzick model, a previously developed risk-model based on classic risk factors, may be improved if breast density is taken into consideration.
For this cohort study, researchers accessed the breast imaging registry from Kaiser Permanente Washington to assess the outcomes of 132,139 women aged 40 to 73 years without breast cancer who underwent screening between January 1996 and December 2013. Patients completed a self-reported questionnaire at baseline to identify risk factors such as family history of breast/ovarian cancer and age affected, age, weight, and menopausal status; the incidence of invasive breast cancer was estimated with and without incorporating breast density. Follow-up was conducted every 6 months after entry mammography until the earliest diagnosis of breast cancer.
After a median follow-up of 5.2 years, breast cancer was diagnosed in a total of 2699 women, which was in line with the expected number the Tyrer-Cuzick model estimates with and without the addition of breast density.
Without breast density, the Tyrer-Cuzick model estimated that 2554 women were at high risk, of whom 147 developed invasive breast cancer. With breast density incorporated, the model estimated that 4645 women were at high risk, of whom 273 developed invasive breast cancer.
The top 10% of patients with the highest risk per the Tyrer-Cuzick risk model had a 2.2-fold incidence of breast cancer compared with the middle 80% when not factoring in breast density; when factoring in breast density, there was a 2.5-fold increase.
Regardless of whether or not density was factored in, there was little evidence for a decrease in relative risk calibration throughout follow-up.
The authors concluded that “breast cancer risk assessment combining classic risk factors with mammographic density may provide useful data for 10 years or more and could be used to guide long-term, systematic, risk-adapted screening and prevention strategies.”
Brentnall AR, Cuzick J, Buist DSM, Aiello Bowels EJ. Long-term accuracy of breast cancer risk assessment combining classic risk factors and breast density [published online April 5, 2018].JAMA Oncol. doi: 10.1001/jamaoncol.2018.0174