Accurately identifying women at increased risk for breast cancer ideally leads to prevention and early disease detection.
Yet, what if a woman has had a benign breast biopsy? Or is African American, whose risk to date has been underestimated?
Two studies1,2 published online in Journal of Clinical Oncology explored what features should be assessed in a risk model to predict the probability of breast cancer in these two populations.
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Up to 2 million women in the United States who undergo a breast biopsy each year have a finding of benign breast disease (BBD). When stratified by degree of epithelial abnormality, these women are at increased risk of breast cancer, noted Amy Degnim, MD, a surgeon at the Mayo Clinic in Rochester, MN, and colleagues.1
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“Unfortunately, currently available risk prediction models do not provide accurate estimates of risk at the individual level,” they wrote. This includes the commonly used Breast Cancer Risk Assessment Tool (BCRAT).
Dr. Degnim and colleagues incorporated histologic features of biopsy tissues from women with BBD, together with demographic and clinical features, into a risk prediction model, the BBD-to-breast cancer (BBD-BC) risk assessment tool, and compared its performance to the BCRAT.
“To our knowledge, this BBD-BC model is the first breast cancer risk prediction tool that focuses specifically on the sizable pool of women with BBD. Importantly, it incorporates information assessed directly from the breast biopsy, in addition to clinical risk factors,” they stated.
Their validated model was found to classify a woman’s risk of breast cancer after a benign biopsy more accurately than the BCRAT, predicting the absolute risk of breast cancer—both invasive and in situ—at 10 years and for lifetime after benign biopsy.
“We will now have a new tool, a prediction model, to provide an individualized estimate of breast cancer risk in women who have had a benign breast biopsy,” Dr. Degnim told Cancer Therapy Advisor.
The BBD-BC model includes histologic impression, number of atypical foci, extent of lobular involution, radial scar, sclerosing adenosis/columnar cell alterations, family history, age at first live birth, years/number of children (alone, modified by histologic impression, and modified by extent of lobular involution), and extent of involution modified by sclerosing adenosis and/or columnar cell alterations.
Dr. Degnim said 20% to 25% is the range of risk when a clinician should start thinking about adding breast MRI or prescribing chemoprevention, such as tamoxifen, raloxifene, anastrozole, or exemestane, weighing the medication’s benefits against its side effect profile. “The larger a women’s risk, the more benefit from reducing those risk factors,” she said.
The BBD-BC tool is currently being developed for online use.
The second study is believed to be the first “to use prospective data to develop a breast cancer risk prediction model for black women,” according to Julie R. Palmer, ScD, of the Slone Epidemiology Center at Boston University, Boston, MA, and colleagues.
The BRCAT, although modified for use in African American women, underestimated risk among women age 30 to 69 in the Black Women’s Health Study (BWHS), “particularly among women with a later age at first birth,” they noted. This underestimation has contributed to “underrepresentation of African American women in breast cancer prevention trials.”
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The BWHS model was developed based on an analysis of 55,879 women and included family history, previous biopsy, body mass index at age 18, age at menarche, age at first birth, oral contraceptive use, bilateral oophorectomy, estrogen plus progestin use, and height.
Results showed the BWHS model to be well calibrated across a wide range of ages and risk factor strata, with its predictive ability to be better for younger women, making it “a useful tool to identify women who may benefit from screening before age 50 years,” they concluded.
References
- Pankratz VS, Degnim AC, Frank RD, et al. Model for individualized prediction of breast cancer risk after a benign breast biopsy. J Clin Oncol. 26 Jan 2015. [Epub ahead of print] pii: JCO.2014.55.4865.
- Boggs DA, Rosenberg L, Adams-Campbell LL, Palmer JR. Prospective approach to breast cancer risk prediction in African American women: the Black Women’s Health Study model. J Clin Oncol. 26 Jan 2015. [Epub ahead of print] pii: JCO.2014.57.2750.
