Breast cancer risk estimates for individual women vary substantially depending on which risk assessment model is used, and women are likely receiving vastly different recommendations depending on the model used and the cutoff applied to define "high risk," according to a new study from UCLA. The study appears online in Journal of General Internal Medicine.
Current incidence rates indicate that about one in eight women born in the United States today will develop breast cancer at some time during her life. The risk increases with age.
As precision medicine evolves in healthcare, breast cancer risk models are increasingly used to identify women who would benefit from medicines to reduce the risk of breast cancer as well as supplemental MRI screening. Easy-to-use risk models are readily available on-line and women are often given a risk estimate on their screening mammogram reports. An important question is how accurate are those models?
In 2019, the US Preventive Services Task Force recommended that clinicians offer risk-reducing medications, such as tamoxifen, raloxifene, or aromatase inhibitors, to women who are at high risk for breast cancer in the next 5 years and at low risk for adverse medication effects.
While previously, a 5-year risk cutoff of 1.67% was established, the Task Force recommended a new, higher 5-year risk cutoff of 3%. And while current breast cancer risk assessment tools work well at a population level, little attention has been paid to how they perform at an individual level or to the variation in risk estimates for the ≥ 3.0% 5-year threshold at the level of the individual.
The current study included more than 31,115 women who were part of the Athena Breast Health Network, a statewide quality improvement initiative across the University of California medical and cancer centers. It focused on three commonly used risk assessment models: the Breast Cancer Risk Assessment Tool (BCRAT, also called the Gail model), the Breast Cancer Surveillance Consortium (BCSC), and the International Breast Intervention Study (IBIS, also called the Tyrer-Cuzick model).
Investigators found when using a threshold of ≥ 1.67%, more than 21% of women were classified as high risk for developing breast cancer in the next 5 years by one model but average risk by another model.
When using a ≥ 3.0% threshold, more than 5% of women had disagreements in risk severity between models. If all three models were used, almost half of women (46.6%) were classified as high risk by at least one model. Because most women will not be diagnosed with breast cancer within 5 years, the authors say many women would be incorrectly classified as high risk.
