Nguyen Tuong L, Aung Ye K, Evans Christopher F, Dite Gillian S, Stone Jennifer, MacInnis Robert J, Dowty James G, Bickerstaffe Adrian, Aujard Kelly, Rommens Johanna M, Song Yun-Mi, Sung Joohon, Jenkins Mark A, Southey Melissa C, Giles Graham G, Apicella Carmel, Hopper John L
Centre for Epidemiology and Biostatistics, University of Melbourne, Carlton, VIC, Australia.
Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, WA, Australia.
Int J Epidemiol. 2017 Apr 1;46(2):652-661. doi: 10.1093/ije/dyw212.
Mammographic density defined by the conventional pixel brightness threshold, and adjusted for age and body mass index (BMI), is a well-established risk factor for breast cancer. We asked if higher thresholds better separate women with and without breast cancer.
We studied Australian women, 354 with breast cancer over-sampled for early-onset and family history, and 944 unaffected controls frequency-matched for age at mammogram. We measured mammographic dense area and percent density using the CUMULUS software at the conventional threshold, which we call Cumulus , and at two increasingly higher thresholds, which we call Altocumulus and Cirrocumulus , respectively. All measures were Box-Cox transformed and adjusted for age and BMI. We estimated the odds per adjusted standard deviation (OPERA) using logistic regression and the area under the receiver operating characteristic curve (AUC).
Altocumulus and Cirrocumulus were correlated with Cumulus (r ∼ 0.8 and 0.6 , respectively) . For dense area, the OPERA was 1.62, 1.74 and 1.73 for Cumulus, Altocumulus and Cirrocumulus , respectively (all P < 0.001). After adjusting for Altocumulus and Cirrocumulus , Cumulus was not significant ( P > 0.6). The OPERAs for percent density were less but gave similar findings. The mean of the standardized adjusted Altocumulus and Cirrocumulus dense area measures was the best predictor; OPERA = 1.87 [95% confidence interval (CI): 1.64-2.14] and AUC = 0.68 (0.65-0.71).
The areas of higher mammographically dense regions are associated with almost 30% stronger breast cancer risk gradient, explain the risk association of the conventional measure and might be more aetiologically important. This has substantial implications for clinical translation and molecular, genetic and epidemiological research.
通过传统像素亮度阈值定义并根据年龄和体重指数(BMI)进行调整的乳腺X线密度是乳腺癌公认的危险因素。我们探讨了更高的阈值是否能更好地区分患乳腺癌和未患乳腺癌的女性。
我们研究了澳大利亚女性,其中354例患有乳腺癌,对早发和家族史进行了过度抽样,944例未受影响的对照在乳腺X线检查时按年龄进行频率匹配。我们使用CUMULUS软件在传统阈值(我们称为Cumulus)以及两个逐渐升高的阈值(我们分别称为Altocumulus和Cirrocumulus)下测量乳腺X线致密面积和密度百分比。所有测量值均进行Box-Cox变换,并根据年龄和BMI进行调整。我们使用逻辑回归和受试者操作特征曲线下面积(AUC)估计每调整标准差的比值(OPERA)。
Altocumulus和Cirrocumulus与Cumulus相关(r分别约为0.8和0.6)。对于致密面积,Cumulus、Altocumulus和Cirrocumulus的OPERA分别为1.62、1.74和1.73(均P < 0.001)。在调整Altocumulus和Cirrocumulus后,Cumulus不显著(P > 0.6)。密度百分比的OPERA较小但结果相似。标准化调整后的Altocumulus和Cirrocumulus致密面积测量值的平均值是最佳预测指标;OPERA = 1.87 [95%置信区间(CI):1.64 - 2.14],AUC = 0.68((0.65 - 0.71))。
乳腺X线高密度区域与乳腺癌风险梯度增强近30%相关,解释了传统测量方法的风险关联,可能在病因学上更重要。这对临床转化以及分子、遗传和流行病学研究具有重大意义。