A new study concludes that if white women who carry common gene variants linked to breast cancer maintained key lifestyle factors, almost 30 percent of cases could be avoided. Researchers who published the study Thursday said the majority of those cases avoided would be among women at an increased risk because of family history and gene variations.

“Those genetics risks are not set in stone,” senior researcher Nilanjan Chatterjee, a professor at Johns Hopkins Bloomberg School of Public Health in Baltimore, told UPI.com.

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Chatterjee and his team of researchers developed a model to predict a woman’s risk of breast cancer that compiled genetic information as well as family history of breast cancer, age menstruation began and lifestyle habit. They also estimated the effects of 68 individual gene variants which the women were not tested for.

The model found that an average 30-year-old white woman has an 11 percent chance of developing breast cancer by age 80, but those who abided by certain lifestyle factors could see the greatest decrease in risk.

Researchers found that white women who maintained a healthy weight avoided smoking, limited alcohol intake and did not use hormone therapy after menopause significantly cut their risk of developing breast cancer, UPI.com reported.

“Lifestyle factors may be even more important for women at higher genetic risk than for those at low genetic risk,” Chatterjee told UPI.com.

The study did not include women with the BRCA gene mutations, but did focus on 92 gene variants that are more commonly found in women. The results were based on more than 40,000 women who tested positive for 24 gene variants previously linked to an increased risk of breast cancer.

“The bottom line is, this study provides evidence that, on a population level, a certain number of breast cancer cases would be prevented if women did these things,” William Dupont, study co-author and a professor at Vanderbilt University School of Medicine in Nashville, Tenn., told UPI.com.

Both Dupont and Chatterjee cautioned that the model should not be used to predict a patient’s risk of developing cancer, especially because most women are not aware of their gene variations. However, Catterjee said that as the cost of genetic analysis goes down, the model could become a viable option in determining best candidates for breast cancer screening.

The study was published in JAMA Oncology.