A nomogram for predicting the HER2 status in female patients with breast cancer in China: a nationwide, multicenter, 10-year epidemiological study

• Main Authors: Huimin Zhang, Peiling Xie, Zhuoying Li, Rong Huang, Weiliang Feng, Yanan Kong, Feng Xu, Lin Zhao, Qingkun Song, Jing Li, Baoning Zhang, Jinhu Fan, Youlin Qiao, Xiaoming Xie, Shan Zheng, Jianjun He, Ke Wang
• Format: Article
• Language: English
• Published: BMC 2019-05-01
• Series: Diagnostic Pathology
• Subjects: Breast cancer; HER2 status; Nomogram; Prediction and validation
• Online Access: http://link.springer.com/article/10.1186/s13000-019-0806-4

Abstract Background The concordance rate of human epidermal growth factor receptor 2 (HER2) status between core needle biopsy (CNB) and subsequent excisional biopsies of the same tumor varies from 81 to 96%, which may cause inappropriate neoadjuvant therapy that impair the potential benefit from HER2 targeted therapy for patients. This study aimed to establish a nomogram to predict the HER2 status pre-operatively as an auxiliary diagnosis to CNB assessment. Methods Among 4211 breast cancer patients cataloged in the Nation-wide Multicenter 10-year Retrospective Clinical Epidemiological Study of Breast Cancer in China, 2291 patients with complete relevant information were included in this study, which were further randomized 3:1 and divided into a training set and a validation set. The nomogram was established based on independent predictors of HER2 positivity recognized by logistic regression analysis and further validated internally and externally. Results The multivariate logistic regression analysis showed that T-stage, N-stage, estrogen receptor (ER) status, progesterone receptor (PR) status were independent predictors for HER2 status. The nomogram was thereby constructed by those independent predictors as well as histology type. The areas under the receiver operating characteristic curve (AUC) of the training set and the validation set were 0.636 and 0.681, respectively. The calibration plots demonstrated good fitness of the nomogram for HER2 status prediction. With the optimal cutoff value, the nomogram yielded 80.0% sensitivity, 43.1% specificity in the training set and 81.1% sensitivity, 49.8% specificity in the validation set. Conclusions The present nomogram can provide valuable information on HER2 status and combined with standard CNB assessment, clinicians could make more appropriate decision on neoadjuvant therapy of breast cancer.