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Development of a Breast Cancer Risk Prediction Model for Black Women in the United States


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As reported in the Journal of Clinical Oncology, Julie R. Palmer, ScD, and colleagues have developed and validated a risk prediction model for invasive breast cancer in Black women in the United States.

Study Details

For the development of the model, breast cancer relative and attributable risks were estimated from data from Black women in three U.S. population–based case-control studies (3,468 breast cancer cases and 3,578 controls aged 30 to 69 years) and combined with Surveillance, Epidemiology and End results data on age- and race-specific incidence rates, with incorporation of competing mortality. The model was validated using data from 51,798 participants in the Black Women’s Health Study, including 1,515 with invasive breast cancer. A separate model was developed for prediction of estrogen receptor (ER)-specific risks.


Discriminatory accuracy of the new model was similar to that of the most frequently used questionnaire-based breast cancer risk prediction models in White women, suggesting that effective risk stratification for Black women is now possible.
— Julie R. Palmer, ScD

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Key Findings

Among variables included in the prediction models, a first-degree family history of breast cancer, breast biopsy, ≥ 5 years of oral contraceptive use, earlier age at menarche, and lack of breastfeeding were associated with increased risk of all invasive cancer; bilateral oophorectomy was associated with reduced risk. Family history of prostate cancer, lower body mass index (BMI) at age 18 years, BMI > 30 kg/m2 in postmenopausal women, later age at first birth, and nulliparity were associated with increased risk of ER-positive—but not ER-negative—breast cancer. Higher parity was associated with increased risk of ER-negative breast cancer.

In the validation cohort, for all invasive cancers, the expected/observed ratio was 1.01 (95% confidence interval [CI] = 0.95–1.07), with good calibration observed across age strata, individual risk factors, and risk quintiles. Age-adjusted C-statistics were 0.58 (95% CI = 0.56–0.59) overall and 0.63 (95% CI = 0.58–0.68) among women aged < 40 years.

For the ER-specific risk model, the expected/observed ratio was 1.06 (95% CI = 1.00–1.13), with good calibration across age strata, individual risk factors, and risk quintiles. The overall age-adjusted C-statistic was 0.58 (95% CI = 0.56–0.59); C-statistics were 0.59 for ER-positive cancer and 0.56 for ER-negative cancer.

Analysis of 5-year predicted absolute risk of breast cancer according to risk quintile showed that women aged < 40 years had the greatest estimated relative risk (highest vs lowest quintile = 4.56, 95% CI = 2.02–10.3).

The investigators concluded, “Discriminatory accuracy of the new model was similar to that of the most frequently used questionnaire-based breast cancer risk prediction models in White women, suggesting that effective risk stratification for Black women is now possible. This model may be especially valuable for risk stratification of young Black women, who are below the ages at which breast cancer screening is typically begun.”

Dr. Palmer, of the Slone Epidemiology Center and Department of Medicine, Boston University School of Medicine, is the corresponding author for the Journal of Clinical Oncology article.

Disclosure: The study was supported by grants from the National Institutes of Health, Susan G. Komen Foundation, and Karin Grunebaum Foundation. For full disclosures of the study authors, visit ascopubs.org.

The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
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