Breast Cancer Res. 2014 Apr 8;16(2):R37. doi: 10.1186/bcr3641.
Breast density has been established as a major risk factor for breast cancer. We have previously demonstrated that mammographic texture resemblance (MTR), recognizing the local texture patterns of the mammogram, is also a risk factor for breast cancer, independent of percent breast density. We examine if these findings generalize to another population.
Texture patterns were recorded in digitalized pre-diagnosis (3.7 years) film mammograms of a nested case-control study within the Dutch screening program (S1) comprising of 245 breast cancers and 250 matched controls. The patterns were recognized in the same study using cross-validation to form resemblance scores associated with breast cancer. Texture patterns from S1 were examined in an independent nested case-control study within the Mayo Mammography Health Study cohort (S2) of 226 cases and 442 matched controls: mammograms on average 8.5 years prior to diagnosis, risk factor information and percent mammographic density (PD) estimated using Cumulus were available. MTR scores estimated from S1, S2 and S1 + S2 (the latter two as cross-validations) were evaluated in S2. MTR scores were analyzed as both quartiles and continuously for association with breast cancer using odds ratios (OR) and adjusting for known risk factors including age, body mass index (BMI), and hormone usage.
The mean ages of S1 and S2 were 58.0 ± 5.7 years and 55.2 ± 10.5 years, respectively. The MTR scores on S1 showed significant capability to discriminate cancers from controls (area under the operator characteristics curve (AUC) = 0.63 ± 0.02, P <0.001), which persisted after adjustment for PD. S2 showed an AUC of 0.63, 0.61, and 0.60 based on PD, MTR scores trained on S2, and MTR scores trained on S1, respectively. When adjusted for PD, MTR scores of S2 trained on S1 showed an association with breast cancer for the highest quartile alone: OR in quartiles of controls as reference; 1.04 (0.59 to 1.81); 0.95 (0.52 to 1.74); 1.84 (1.10 to 3.07) respectively. The combined continuous model with both PD and MTR scores based on S1 had an AUC of 0.66 ± 0.03.
The local texture patterns associated with breast cancer risk in S1 were also an independent risk factor in S2. Additional textures identified in S2 did not significantly improve risk segregation. Hence, the textural patterns that indicated elevated risk persisted under differences in X-ray technology, population demographics, follow-up time and geography.
乳腺密度已被确定为乳腺癌的一个主要危险因素。我们之前已经证明,乳腺摄影纹理相似性(MTR),即识别乳腺摄影的局部纹理模式,也是乳腺癌的一个危险因素,与乳腺密度百分比无关。我们研究这些发现是否适用于另一个人群。
在荷兰筛查项目中的嵌套病例对照研究(S1)中,记录了数字化的预诊断(3.7 年)胶片乳腺摄影中的纹理模式,该研究包括 245 例乳腺癌和 250 例匹配对照。使用交叉验证在同一研究中识别出这些模式,形成与乳腺癌相关的相似性评分。从 S1 中提取的纹理模式在梅奥乳腺摄影健康研究队列的另一个嵌套病例对照研究(S2)中进行了检查:平均在诊断前 8.5 年进行乳腺摄影,使用 Cumulus 估计风险因素信息和乳腺摄影密度(PD)。使用来自 S1、S2 和 S1+S2(后两者作为交叉验证)的 MTR 评分在 S2 中进行评估。使用比值比(OR)分析 MTR 评分与乳腺癌的关联,作为四分位数和连续变量,并调整已知的风险因素,包括年龄、体重指数(BMI)和激素使用情况。
S1 和 S2 的平均年龄分别为 58.0±5.7 岁和 55.2±10.5 岁。S1 上的 MTR 评分显示出区分癌症和对照的显著能力(操作特征曲线下面积(AUC)=0.63±0.02,P<0.001),这在调整 PD 后仍然存在。S2 基于 PD、基于 S2 训练的 MTR 评分和基于 S1 训练的 MTR 评分,AUC 分别为 0.63、0.61 和 0.60。当调整 PD 后,基于 S1 训练的 S2 的 MTR 评分最高四分位数与乳腺癌相关:以四分位数对照为参考的比值比;1.04(0.59 至 1.81);0.95(0.52 至 1.74);1.84(1.10 至 3.07)。基于 S1 的 PD 和 MTR 评分的连续综合模型的 AUC 为 0.66±0.03。
S1 中与乳腺癌风险相关的局部纹理模式也是 S2 的一个独立危险因素。在 S2 中识别出的其他纹理并未显著改善风险分离。因此,在 X 射线技术、人群特征、随访时间和地理位置存在差异的情况下,提示风险升高的纹理模式仍然存在。