乳腺癌
医学
内科学
肿瘤科
家族史
置信区间
体质指数
癌症
浸润性小叶癌
逻辑回归
乳腺摄影术
乳房成像
妇科
浸润性导管癌
作者
Brandy L. Edwards,Kristen A. Atkins,George J. Stukenborg,Wendy M. Novicoff,Krista N. Larson,Wendy F. Cohn,Jennifer A. Harvey,Anneke T. Schroen
标识
DOI:10.1158/1055-9965.epi-16-0881
摘要
Abstract Background: Mammographic density (MD) is associated with increased breast cancer risk, yet limited data exist on an association between MD and breast cancer molecular subtypes. Methods: Women ages 18 years and older with breast cancer and available mammograms between 2003 and 2012 were enrolled in a larger study on MD. MD was classified by the Breast Imaging Reporting and Data System (BI-RADS) classification and by volumetric breast percent density (Volpara Solutions). Subtype was assigned by hormone receptor status, tumor grade, and mitotic score (MS). Subtypes included: Luminal-A (ER/PR+ and grade = 1; ER/PR+ and grade = 2 and MS = 1; ER+/PR− and grade = 1; n = 233); Luminal-B (ER+ and grade = 3 or MS = 3; ER+/PR− and grade = 2; ER/PR+ and grade = 2 and MS = 2; n = 79); Her-2-neu+ (H2P; n = 59); triple-negative (ER/PR−, Her-2−; n = 86). Precancer factors including age, race, body mass index (kg/m2), family history of breast cancer, and history of lobular carcinoma in situ were analyzed. Results: A total of 604 patients had invasive cancer; 457 had sufficient information for analysis. Women with H2P tumors were younger (P = 0.011) and had the highest volumetric percent density (P = 0.002) among subgroups. Multinomial logistic regression (LA = reference) demonstrated that although quantitative MD does not significantly differentiate between all subtypes (P = 0.123), the association between MD and H2P tumors is significant (OR = 1.06; confidence interval, 1.01–1.12). This association was not seen using BI-RADS classification in bivariable analysis but was statistically significant (P = 0.047) when controlling for other precancer factors. Conclusions: Increased MD is more strongly associated with H2P tumors when compared with LA. Impact: Delineating risk factors specific to breast cancer subtype may promote development of individualized risk prediction models and screening strategies. Cancer Epidemiol Biomarkers Prev; 26(10); 1487–92. ©2017 AACR.
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