Schonberg Mara A, Li Vicky W, Eliassen A Heather, Davis Roger B, LaCroix Andrea Z, McCarthy Ellen P, Rosner Bernard A, Chlebowski Rowan T, Rohan Thomas E, Hankinson Susan E, Marcantonio Edward R, Ngo Long H
Affiliations of authors:Division of General Medicine and Primary Care, Department of Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center , Boston, MA (MAS, VWL, RBD, EPM, ERM, LHN); Department of Epidemiology, Harvard School of Public Health , Boston, MA and Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard School of Public Health , Boston, MA (AHE, BAR, SEH); Division of Epidemiology, Family and Preventive Medicine, University of California San Diego , La Jolla, CA (AZL); Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center , Torrance, CA (RTC) ; Department of Epidemiology & Population Health, Albert Einstein College of Medicine , Bronx, NY (TER); Department of Biostatistics and Epidemiology, University of Massachusetts , Amherst, MA (SEH).
J Natl Cancer Inst. 2015 Nov 30;108(3). doi: 10.1093/jnci/djv348. Print 2016 Mar.
The Breast Cancer Risk Assessment Tool (BCRAT, "Gail model") is commonly used for breast cancer prediction; however, it has not been validated for women age 75 years and older.
We used Nurses' Health Study (NHS) data beginning in 2004 and Women's Health Initiative (WHI) data beginning in 2005 to compare BCRAT's performance among women age 75 years and older with that in women age 55 to 74 years in predicting five-year breast cancer incidence. BCRAT risk factors include: age, race/ethnicity, age at menarche, age at first birth, family history, history of benign breast biopsy, and atypia. We examined BCRAT's calibration by age by comparing expected/observed (E/O) ratios of breast cancer incidence. We examined discrimination by computing c-statistics for the model by age. All statistical tests were two-sided.
Seventy-three thousand seventy-two NHS and 97 081 WHI women participated. NHS participants were more likely to be non-Hispanic white (96.2% vs 84.7% in WHI, P < .001) and were less likely to develop breast cancer (1.8% vs 2.0%, P = .02). E/O ratios by age in NHS were 1.16 (95% confidence interval [CI] = 1.09 to 1.23, age 57-74 years) and 1.31 (95% CI = 1.18 to 1.45, age ≥ 75 years, P = .02), and in WHI 1.03 (95% CI = 0.97 to 1.09, age 55-74 years) and 1.10 (95% CI = 1.00 to 1.21, age ≥ 75 years, P = .21). E/O ratio 95% confidence intervals crossed one among women age 75 years and older when samples were limited to women who underwent mammography and were without significant illness. C-statistics ranged between 0.56 and 0.58 in both cohorts regardless of age.
BCRAT accurately predicted breast cancer for women age 75 years and older who underwent mammography and were without significant illness but had modest discrimination. Models that consider individual competing risks of non-breast cancer death may improve breast cancer risk prediction for older women.
乳腺癌风险评估工具（BCRAT，“盖尔模型”）常用于乳腺癌预测；然而，它尚未在75岁及以上女性中得到验证。
我们使用了始于2004年的护士健康研究（NHS）数据和始于2005年的妇女健康倡议（WHI）数据，比较BCRAT在预测5年乳腺癌发病率方面，在75岁及以上女性与55至74岁女性中的表现。BCRAT风险因素包括：年龄、种族/族裔、初潮年龄、首次生育年龄、家族史、良性乳腺活检史和非典型增生。我们通过比较乳腺癌发病率的预期/观察（E/O）比值，按年龄检查BCRAT的校准情况。我们通过计算该模型按年龄的c统计量来检查区分度。所有统计检验均为双侧检验。
73072名NHS女性和97081名WHI女性参与了研究。NHS参与者更可能是非西班牙裔白人（96.2%对WHI中的84.7%，P<.001），且患乳腺癌的可能性较小（1.8%对2.0%，P=.02）。NHS中按年龄的E/O比值在57 - 74岁时为1.16（95%置信区间[CI]=1.09至1.23），在年龄≥75岁时为1.31（95%CI = 1.18至1.45，P=.02）；在WHI中，55 - 74岁时为1.03（95%CI = 0.97至1.09），在年龄≥75岁时为1.10（95%CI = 1.00至1.21，P=.21）。当样本限于接受乳腺钼靶检查且无重大疾病的女性时，75岁及以上女性的E/O比值95%置信区间有交叉。两个队列中，无论年龄，c统计量都在0.56至0.58之间。
BCRAT能准确预测接受乳腺钼靶检查且无重大疾病的75岁及以上女性的乳腺癌，但区分度一般。考虑非乳腺癌死亡个体竞争风险的模型可能会改善老年女性的乳腺癌风险预测。
