Researchers have developed a new statistical model to estimate the absolute risk of breast cancer to help improve public health strategies and prevention.
In the study, published May 26 in JAMA Oncology, Nilanjan Chatterjee, PhD, of Johns Hopkins University and coauthors used study data to develop a more empirical model to predict absolute risk of invasive breast cancer. The model examined risk using included 92 susceptibility single nucleotide polymorphisms and a variety of epidemiologic factors, such as family history, anthropometric factors, menstrual/reproductive factors and lifestyle factors.
The model suggests a 30-year-old white woman in the U.S. has an 11.3 percent risk, on average, of developing invasive breast cancer by the age of 80. When the model included all risk factors, the range of average absolute risk was 4.4 percent to 23.5 percent for women, according to the results.
Overall, the authors estimate that as many as 28.9 percent of all breast cancers could be prevented if all white women in the U.S. population were at the lowest risk from these 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 effect of such models for improving the cost-benefit ratio of population-based prevention programs will depend on the implementation cost of risk assessment,” the authors conclude.
The study noted those women with low body mass index (BMI) and who did not drink, smoke or use menopausal hormone therapy had reduced absolute risk of breast cancer.