A nomogram to predict pathological axillary lymph node status in neoadjuvant chemotherapy-treated patients with breast cancer

OBJECTIVES: Accurately predicting axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NACT) is of vital importance for making decisions regarding the axillary treatment plan for breast cancer patients. This study aimed to identify factors influencing ypN0 and to develop a predictive nomogram to evaluate the probability of ypN0 in NACT-treated patients with breast cancer. METHODS: Overall, 1559 patients with cT1-4N1-2M0 breast cancer who received NACT and mastectomy between 2000 and 2014 in 12 institutions in China were analyzed retrospectively. Patients treated in three cancer hospitals (training set, n = 1072) were used to construct a nomogram based on multivariate logistic regression analyses. The nomogram was validated by determining the area under the receiver operating characteristic curve (AUC) and calibration curve values in patients from nine other general hospitals (validation set, n = 487). RESULTS: In the training and validation sets, 26.8% (287 of 1072) and 22.4% (109 of 487) patients, respectively, achieved ypN0. The nomogram incorporated seven predictive factors including clinical T and N stages, histological grade, lymphovascular invasion, molecular subtype, NACT cycles, and clinical response to NACT. The AUC values for the training and validation sets were 0.748 (95% CI, 0.714-0.782) and 0.739 (95% CI, 0.684-0.794), respectively. In addition, the calibration curve showed good agreement between the nomogram-based predictions and the actual observations. CONCLUSION: A nomogram was established to predict the status of axillary lymph nodes in NACT-treated patients with breast cancer. The predictive model performed well both in the training and external validation sets. This nomogram can serve as a preoperative, non-invasive decision-support tool to assist clinicians in identifying candidates for axillary de-escalation strategies.

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Publication Details

Journal
Discover Oncology
Published
2026-07-17
DOI
https://doi.org/10.1007/s12672-026-05558-0
Primary Topic
Breast Cancer Treatment Studies
Type
article
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article

A nomogram to predict pathological axillary lymph node status in neoadjuvant chemotherapy-treated patients with breast cancer

Liangfang Shen, J K Chen, Mei Shi, XJ Huang et al.
Discover Oncology
Breast Cancer Treatment Studies
article

A nomogram to predict pathological axillary lymph node status in neoadjuvant chemotherapy-treated patients with breast cancer

Liangfang Shen, J K Chen, Mei Shi, XJ Huang, Wei Zhang, Yirui Zhai, Weihu Wang, Tie J, Zi-han Qiu, Dong-Xing Shen, Z Huang, J Y Zhang, J Q Jin, S N Qi, H Jing, Yuan Tang, Bo Chen, Min Liu, Ning-Ning Lu, Jing Cheng, Li Zhu, Xin Liu, Yue-Ping Liu, Ye-Xiong Li, Shu-Lian Wang, Yong-Wen Song, Hui Fang, Yu Tang
article en

Abstract

OBJECTIVES: Accurately predicting axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NACT) is of vital importance for making decisions regarding the axillary treatment plan for breast cancer patients. This study aimed to identify factors influencing ypN0 and to develop a predictive nomogram to evaluate the probability of ypN0 in NACT-treated patients with breast cancer. METHODS: Overall, 1559 patients with cT1-4N1-2M0 breast cancer who received NACT and mastectomy between 2000 and 2014 in 12 institutions in China were analyzed retrospectively. Patients treated in three cancer hospitals (training set, n = 1072) were used to construct a nomogram based on multivariate logistic regression analyses. The nomogram was validated by determining the area under the receiver operating characteristic curve (AUC) and calibration curve values in patients from nine other general hospitals (validation set, n = 487). RESULTS: In the training and validation sets, 26.8% (287 of 1072) and 22.4% (109 of 487) patients, respectively, achieved ypN0. The nomogram incorporated seven predictive factors including clinical T and N stages, histological grade, lymphovascular invasion, molecular subtype, NACT cycles, and clinical response to NACT. The AUC values for the training and validation sets were 0.748 (95% CI, 0.714-0.782) and 0.739 (95% CI, 0.684-0.794), respectively. In addition, the calibration curve showed good agreement between the nomogram-based predictions and the actual observations. CONCLUSION: A nomogram was established to predict the status of axillary lymph nodes in NACT-treated patients with breast cancer. The predictive model performed well both in the training and external validation sets. This nomogram can serve as a preoperative, non-invasive decision-support tool to assist clinicians in identifying candidates for axillary de-escalation strategies.

Discover Oncology
Hebei Medical University (CN), Union Hospital (HK), Central South University (CN), Sun Yat-sen University (CN), Jilin University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking University (CN), Ruijin Hospital (CN), Tianjin Medical University Cancer Institute and Hospital (CN), National Cancer Center (US), Peking University Cancer Hospital (CN), Sun Yat-sen Memorial Hospital (CN), Fourth Hospital of Hebei Medical University (CN), First Hospital of Jilin University (CN), Xijing Hospital (CN), Xiangya Hospital Central South University (CN), Huazhong University of Science and Technology (CN), Air Force Medical University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Breast Cancer Treatment Studies
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