Slone Epidemiology Center at Boston University, Boston, MA.
Boston University School of Medicine, Boston, MA.
J Clin Oncol. 2021 Dec 1;39(34):3866-3877. doi: 10.1200/JCO.21.01236. Epub 2021 Oct 8.
Breast cancer risk prediction models are used to identify high-risk women for early detection, targeted interventions, and enrollment into prevention trials. We sought to develop and evaluate a risk prediction model for breast cancer in US Black women, suitable for use in primary care settings.
Breast cancer relative risks and attributable risks were estimated using data from Black women in three US population-based case-control studies (3,468 breast cancer cases; 3,578 controls age 30-69 years) and combined with SEER age- and race-specific incidence rates, with incorporation of competing mortality, to develop an absolute risk model. The model was validated in prospective data among 51,798 participants of the Black Women's Health Study, including 1,515 who developed invasive breast cancer. A second risk prediction model was developed on the basis of estrogen receptor (ER)-specific relative risks and attributable risks. Model performance was assessed by calibration (expected/observed cases) and discriminatory accuracy (C-statistic).
The expected/observed ratio was 1.01 (95% CI, 0.95 to 1.07). Age-adjusted C-statistics were 0.58 (95% CI, 0.56 to 0.59) overall and 0.63 (95% CI, 0.58 to 0.68) among women younger than 40 years. These measures were almost identical in the model based on estrogen receptor-specific relative risks and attributable 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. 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.
乳腺癌风险预测模型用于识别高危女性，以便进行早期检测、靶向干预和参与预防试验。我们旨在为美国黑人女性开发和评估一种乳腺癌风险预测模型，适用于初级保健环境。
使用来自三项美国基于人群的病例对照研究（3468 例乳腺癌病例；3578 例年龄 30-69 岁的对照）中黑人女性的数据来估计乳腺癌的相对风险和归因风险，并结合 SEER 年龄和种族特异性发病率，同时考虑竞争死亡率，以开发绝对风险模型。该模型在 Black Women's Health Study 的 51798 名参与者的前瞻性数据中进行了验证，其中包括 1515 名患有浸润性乳腺癌的患者。基于雌激素受体（ER）特异性相对风险和归因风险开发了第二个风险预测模型。通过校准（预期/观察病例）和区分准确性（C 统计量）来评估模型性能。
预期/观察比值为 1.01（95%CI，0.95-1.07）。年龄调整后的 C 统计量总体为 0.58（95%CI，0.56-0.59），40 岁以下女性为 0.63（95%CI，0.58-0.68）。基于雌激素受体特异性相对风险和归因风险的模型中，这些指标几乎相同。
新模型的区分准确性与白人女性最常用的基于问卷的乳腺癌风险预测模型相似，这表明现在可以对黑人女性进行有效的风险分层。对于年龄低于开始乳腺癌筛查年龄的年轻黑人女性，这种模型可能特别有价值。
