Ethnic and geographic differences in mammographic density and their association with breast cancer incidence
Ethnic and geographic differences in mammographic density and their association with breast cancer incidence
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DOI：
10.1007/s10549-006-9387-5
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发表时间：
2007-07-01
影响因子：
3.8
通讯作者：
Gram, Inger Torhild
中科院分区：
文献类型：
--
作者：
Maskarinec, Gertraud;Pagano, Ian;Gram, Inger Torhild
这项合并分析的目的是比较不同乳腺癌风险人群中致密区域和乳房X光摄影密度百分比与乳腺癌发病率的差异。数据集包括1327名年龄在40岁至80岁之间的女性：来自挪威、亚利桑那州和夏威夷的高加索人，来自夏威夷和日本的日本人，来自亚利桑那州的拉丁裔，以及来自夏威夷的夏威夷原住民。一位读者对所有乳房X光照片进行了计算机辅助的定量密度评估。多元线性回归模型评估了协变量对乳房密度的影响。斯皮尔曼相关系数(r(S))估计了七个人群的乳房密度和乳腺癌发病率之间的联系。在调整协变量后，种族，而不是地区，与乳房密度显著相关。在全模型中，19%的密度密度变化和46%的百分比密度变化可以用测量的危险因素来解释。夏威夷原住民的密度最大，日本女性的密度最小，而夏威夷原住民和日本人的百分比密度最高，挪威女性的百分比密度最低。年龄调整后平均密度与乳腺癌发病率的相关性最强(r(S)=0.93，P=0.003)，与百分比密度的相关性较弱(r(S)=0.32，P=0.48)。在选择性地删除个别数据点后，年龄调整后的致密区域与乳腺癌发病率之间的相关性仍然很强。这种乳房X光照相密度的比较表明，在群体层面上，年龄调整后的致密区域可能比百分比密度更好地反映乳腺癌的发病率。
The objective of this pooled analysis was to compare differences in dense areas and percent mammographic densities to breast cancer incidence in populations at different breast cancer risk. The data set included 1,327 women aged 40 - 80: Caucasians from Norway, Arizona, and Hawaii, Japanese from Hawaii and Japan, Latina from Arizona, and Native Hawaiians from Hawaii. One reader performed computer- assisted quantitative density assessment for all mammographic films. Multiple linear regression models evaluated the influence of the covariates on breast density. Spearman correlation coefficients ( r(s)) estimated the association between breast density and breast cancer incidence for the seven populations. After adjustment for covariates, ethnicity, but not location, was significantly associated with breast density. In the full model, 19% of the variation in the dense areas and 46% in the variation of percent densities were explained by measured risk factors. Native Hawaiians had the largest dense areas and women in Japan the smallest, whereas percent densities were highest among Native Hawaiians and Japanese in Hawaii and lowest among Norwegian women. The mean age- adjusted dense area had the strongest association with breast cancer incidence ( r(s) = 0.93, P = 0.003); the relation with percent density was considerably weaker ( r(s) = 0.32, P = 0.48). The correlation between age- adjusted dense area and breast cancer incidence remained strong after selectively removing individual data points. This comparison of mammographic densities suggests that, on a group level, age- adjusted dense areas may reflect breast cancer incidence better than percent densities.