Combining bi-modal imaging and immunohistochemical indicators to predict axillary lymph nodes status in cN 1 breast cancer patients receiving neoadjuvant chemotherapy
10.3760/cma.j.cn131148-20230131-00050
- VernacularTitle:双模态影像联合免疫组化构建模型预测cN 1期乳腺癌新辅助化疗后腋窝淋巴结状态
- Author:
Yuman LI
1
;
Xingyu LIANG
;
Tong WU
;
Xiangli XU
;
Hui JING
;
Jiawei TIAN
Author Information
1. 哈尔滨医科大学附属第二医院超声科，哈尔滨 150086
- Keywords:
Ultrasound;
Breast cancer;
Axillary lymph nodes;
Pathologic complete response;
Neoadjuvant chemotherapy;
Mammography
- From:
Chinese Journal of Ultrasonography
2023;32(8):699-706
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate whether ultrasound features, mammographic features and immunohistochemical indicators show any association with rates of axillary pathologic complete response(pCR) in cN 1 breast cancer patients receiving neoadjuvant chemotherapy(NAC), and to construct prediction models of axillary pCR to predict axillary lymph nodes (ALN) status, so as to select suitable patients for less invasive axillary surgery after NAC. Methods:This retrospective study evaluated 134 consecutive cN 1 breast cancer patients with ALN metastasis who underwent NAC in the Second Affiliated Hospital and Tumor Hospital of Harbin Medical University from July 2020 to July 2022. According to the pathological results of ALN surgery after NAC, the cases were divided into pCR and non pathologic complete respose(npCR) groups. The ultrasound images, mammographic images and immunohistochemical indicators of the two groups were compared. In terms of logistic regression algorithm, the model A(the ultrasound model), the model B(the ultrasound combined with mammography model), the model C(the ultrasound combined with immunohistochemistry model) and the model D(the ultrasound combined with mammography and immunohistochemistry model) were respectively established for predicting the pathological state of axillary lymph nodes in breast cancer patients, ROC curves were plotted to evaluate the performance of the models, and the diagnostic efficiency of different models was compared by Delong′s test. The model with the best predictive performance was shown in a nomogram. Results:①The P values between two groups of the short diameter of ALN, the ratio of long/short diameter of ALN, fatty hilum and central hilar vascularity, mammographic spiculation, estrogen receptor(ER), progesterone receptor(PR), human epidermal growth factor receptor 2(HER2) were <0.05 by the t test and χ 2 test analysis. ②The ratio of long/short diameter and fatty hilum in the model A were independent factors for predicting the pathological status of ALN after NAC. The independent predictors of model B and Model C were respectively added with mammographic spiculation and immunohistochemical indicators (ER, PR) on the basis of model A. In the model D, the ratio of long/short diameter, short diameter, fatty hilum, mammographic spiculation, and immunohistochemical indicators (ER, PR) remained significant independent predictors associated with axillary pCR. ③The area under ROC curve (AUC) of the model A, B, C, D was 0.78, 0.84, 0.84 and 0.89, respectively. The sensitivity was 0.71, 0.80, 0.78 and 0.86, the specificity was 0.76, 0.74, 0.76 and 0.80, and the accuracy was 0.73, 0.76, 0.77 and 0.83, respectively. ④Delong′s test showed the model D had an improved AUC of 0.89(0.89 vs 0.78, 0.84, 0.84, all P<0.05). Conclusions:The prediction models combining bi-modal imaging and immunohistochemical indicators show good prediction ability and can provide reference for selecting suitable patients for less invasive axillary surgery after NAC.
