Ayvaci Mehmet U S, Alagoz Oguzhan, Chhatwal Jagpreet, Munoz del Rio Alejandro, Sickles Edward A, Nassif Houssam, Kerlikowske Karla, Burnside Elizabeth S
Industrial & Systems Engineering, University of Wisconsin, 1513 University Avenue, Madison, WI 53706, USA.
BMC Cancer. 2014 Aug 11;14:584. doi: 10.1186/1471-2407-14-584.
Increasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age.
We analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50-64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC).
The models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group--mass margins, and in the younger group--mass size were positive predictors of invasive cancer.
Clinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age.
对某些乳腺癌潜在不必要的诊断和治疗的关注度日益增加，促使我们研究预测浸润性乳腺癌与原位导管癌（DCIS）的临床和乳腺钼靶特征是否因年龄而异。
我们分析了1997年1月6日至2007年6月29日在加利福尼亚大学旧金山分校解读的35871例前瞻性收集的连续诊断性乳腺钼靶片中的1475例恶性乳腺活检病例，其中1063例为浸润性癌，412例为DCIS。我们构建了三个逻辑回归模型，以预测以下几组中浸润性癌与DCIS的概率：65岁及以上女性（老年组）、50 - 64岁女性（中年组）和50岁以下女性（年轻组）。我们确定了显著的预测因素，并使用受试者操作特征曲线下面积（AUC）测量所有模型的性能。
老年组和中年组的模型表现明显优于年轻组的模型（AUC分别为0.848对0.778；p = 0.049以及AUC为0.851对0.778；p = 0.022）。在所有年龄组中，可触及性和主要乳腺钼靶表现是区分浸润性癌与DCIS的显著预测因素。乳腺癌家族史、肿块形状和肿块边缘是老年组浸润性癌的显著阳性预测因素，而钙化分布是浸润性癌的阴性预测因素（即预测为DCIS）。在中年组中，肿块边缘，在年轻组中，肿块大小是浸润性癌的阳性预测因素。
临床和乳腺钼靶表现特征在老年女性中比在年轻女性中能更好地预测浸润性乳腺癌与DCIS。特定的预测变量因年龄而异。
