A new, simpler model for predicting breast cancer risk in postmenopausal women appears to be as accurate as a more complicated method currently used to decide if women would benefit from medication to reduce their risk of getting cancer, according to research published in the Journal of the National Cancer Institute.
A team of researchers led by Rowan T. Chlebowski, a lead investigator at the Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center (LA BioMed), sought a simpler method for measuring breast cancer risk so women and their doctors could easily determine when the women would be likely to benefit from tamoxifen treatment for reducing their chances of getting breast cancer.
"For the first time, a postmenopausal woman can use a simple model and determine by herself if she is at increased risk of getting breast cancer," said Dr. Chlebowski. "She could then raise this issue with her health care provider because interventions to reduce her risk of breast cancer are now available."
Using data from the Women's Health Initiative, a 15-year research program involving 161,808 postmenopausal women and funded by the National Institutes of Health, the researchers found postmenopausal women were at an "increased risk" of developing breast cancer if they were: 55 years of age or older and had either had a breast biopsy at any time, regardless of findings, or had a first-degree relative (mother, sister or daughter) who had breast cancer diagnosed at any age.
"Increased risk" is defined as about a 2 percent risk of developing breast cancer over the next five years. The researchers sought a quicker and easier way to determine risk because those who are at "increased risk" may benefit from tamoxifen treatment to reduce their chances of getting breast cancer.
Prior to this study, most physicians relied on the "Gail Model" to determine risk. But it involves so many variables that a computer is needed to determine a woman's risk of breast cancer. As a result, it wasn't used widely.
Previous surveys found only 11 percent of California primary care physicians had used the Gail Model for risk assessment in the past year. In a national survey, only 16 percent agreed that it is "easy to determine" who is eligible for breast cancer risk reduction strategies and only 25 percent had prescribed tamoxifen for risk reduction in the past year.
The Gail model underestimated 5-year breast cancer incidence by almost 20 percent, but it performed better when predicting estrogen receptor-positive breast cancer than estrogen receptor-negative breast cancer. The simpler model that used only three factors for calculating risk--age, family history of breast cancer, and previous breast biopsy--was almost as accurate as the Gail model for predicting estrogen receptor-positive breast cancer.
The simpler model "would be more accessible for routine and rapid prescreening in the prevention or routine care setting," the authors wrote in the Journal article.
The article, entitled "Predicting Risk of Breast Cancer in Postmenopausal Women by Hormone Receptor Status," appears in The Journal of the National Cancer Institute.
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