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ORIGINAL RESEARCH article
Front. Oncol.
Sec. Surgical Oncology
Volume 14 - 2024 |
doi: 10.3389/fonc.2024.1326385
This article is part of the Research Topic Best Surgical Treatment of Breast Cancer Managed Primarily with Neoadjuvant Medical Therapy View all 8 articles
A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: a nationwide, multicenter retrospective cohort study (CSBrS-012)
Provisionally accepted- 1 The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- 2 Department of Breast Disease, Henan Provincial Cancer Hospital, Zhengzhou, Henan Province, China
- 3 Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi Province, China
- 4 Sheng Jing Hospital Affiliated, China Medical University, Shenyang, Liaoning Province, China
- 5 Zhejiang Cancer Hospital, University of Chinese Academy of Sciences, Hangzhou, Zhejiang, China
- 6 Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei Province, China
- 7 Jilin Cancer Hospital, Changchun, Jilin Province, China
- 8 The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China
- 9 Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, China
- 10 The Second Hospital of Shandong University, Jinan, Shandong Province, China
- 11 First Hospital, Peking University, Beijing, Beijing Municipality, China
- 12 First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
- 13 First Affiliated Hospital of Chinese PLA General Hospital, Beijing, Beijing Municipality, China
- 14 Beijing Chaoyang Hospital, Capital Medical University, Beijing, Beijing Municipality, China
- 15 Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, China
- 16 Shandong Provincial Hospital, Jinan, Shandong Province, China
- 17 Inner Mongolia Autonomous Region Cancer Hospital, Hohhot, Inner Mongolia Autonomous Region, China
- 18 Obstetrics and Gynecology Hospital, Fudan University, Shanghai, Shanghai Municipality, China
- 19 Lanzhou University Second Hospital, Lanzhou, Gansu Province, China
- 20 The First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China
- 21 Xiang Yang No.1 People’s Hospital, Xiangyang, China
- 22 First Affiliated Hospital of Jilin University, Changchun, Jilin Province, China
We investigated the factors associated with pathologic node negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram.The CSBrS-012 study (2010-2020) included female primary breast cancer patients who were treated with NAC followed by breast and axillary surgery in twenty hospitals across China. In the present study, a total of 7711 eligible patients were included, comprising 6428 patients in the primary cohort from 15 hospitals and 1283 patients in the external validation cohort from 5 hospitals. Hospitals were randomly assigned. The primary cohort was randomized 3:1 and divided into a training set and an internal validation set. Univariate analysis and multivariate logistic regression analysis were performed on the training set, after which a nomogram was constructed and validated internally and externally.In total, 3560 patients (46.2%) achieved ypN0, and 1558 patients (20.3%) achieved a pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which are independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) of the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively.We present a real-world study based on nationwide large-sample data that can be used to screen for ypN0 effectively to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.
Keywords: breast cancer, Neoadjuvant chemotherapy, Pathologic nodal response, Prediction nomogram, Pathologic complete response
Received: 26 Dec 2023; Accepted: 24 Apr 2024.
Copyright: © 2024 Maimaitiaili, Li, Chai, Zhenzhen, Rui, Zhao, Yang, Liu, Liu, Zhang, Mao, Yu, Liu, Fu, Wang, Jiang, Zhao, Tian, Cao, Wu, Song, Jin, Wu, He, Zhimin and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jianjun He, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Fan Zhimin, First Affiliated Hospital of Jilin University, Changchun, 130012, Jilin Province, China
Huimin Zhang, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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