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Objectives <p>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.</p> Methods <p>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).</p> Results <p>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.</p> Conclusion <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月17日

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  • Zi-Han Qiu,
  • Zhou Huang,
  • Dong-Xing Shen,
  • Li Zhu,
  • Xiao-Bo Huang,
  • Wei-Hu Wang,
  • Jian Tie,
  • Liang-Fang Shen,
  • Mei Shi,
  • Jia-Yi Chen,
  • Min Liu,
  • Jing Cheng,
  • Jun Zhang,
  • Hui Fang,
  • Hao Jing,
  • Yong-Wen Song,
  • Jing Jin,
  • Yue-Ping Liu,
  • Bo Chen,
  • Yuan Tang,
  • Shu-Nan Qi,
  • Ning-Ning Lu,
  • Yi-Rui Zhai,
  • Wen-Wen Zhang,
  • Xin Liu,
  • Ye-Xiong Li,
  • Yu Tang,
  • Shu-Lian Wang

摘要

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.