Model Predicts Risk of Invasive Breast Cancer

A model that predicts the absolute risk of invasive breast cancer was recently developed in an effort to improve prevention.

A study published in JAMA Oncology used previously collected data to help develop a more empirical model. The model contained 92 susceptibility single nucleotide polymorphisms (SNPs), as well as other epidemiologic factors including anthropometric, family history, lifestyle, and menstrual/reproductive factors.

The model revealed that when all risk factors were included, the range of average absolute risk was 4.4% to 23.5% for women at the bottom and top of risk, respectively.

Women who were at the highest level of risk because of non-modifiable risk factors, low body mass index (BMI), not smoking or drinking, and not using menopausal hormone therapy, were found to have risks similar to an average woman in the general population. Researchers believe that as many as 28.9% of all breast cancers could be prevented if every Caucasian woman in the United States was at the lowest risk for the modifiable risk factors.

“Our results illustrate the potential value of risk stratification to improve breast cancer prevention, particularly to aid decisions on risk factor modification at the individual level,” the study authors wrote. “The effect of such models for improving the cost-benefit ratio of population-based prevention programs will depend on the implementation cost of risk assessment.”

Limitations to the study included the inability to evaluate several known risk factors for breast cancer that had data that was unavailable.