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Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study

  • Breast
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Abstract

Objectives

The purpose of this study was to establish two preoperative nomograms to evaluate the risk for axillary lymph node (ALN) metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features.

Methods

We prospectively evaluated 593 consecutive female participants who were diagnosed with cT1-3N0-1M0 breast cancer between March 2018 and May 2019 at Sun Yat-Sen Memorial Hospital. The participants were randomly classified into training and validation sets in a 4:1 ratio for the development and validation of the nomograms, respectively. Multivariate logistic regression analysis was performed to identify independent predictors of ALN status. We developed Nomogram A and Nomogram B to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2), respectively.

Results

A total of 528 participants were evaluated in the final analyses. Multivariable analysis revealed that the number of suspicious lymph nodes, long axis, short-to-long axis ratio, cortical thickness, tumor location, and histological grade were independent predictors of ALN status. The AUCs of nomogram A in the training and validation groups were 0.83 and 0.78, respectively. The AUCs of nomogram B in the training and validation groups were 0.87 and 0.87, respectively. Both nomograms were well-calibrated.

Conclusion

We developed two preoperative nomograms that can be used to predict ALN metastasis (presence vs. absence) and the number of metastatic ALNs (≤ 2 vs. > 2) in early breast cancer patients. Both nomograms are useful tools that will help clinicians predict the risk of ALN metastasis and facilitate therapy decision-making about axillary surgery.

Key Points

• We developed two preoperative nomograms to predict axillary lymph node status based on ultrasonographic-clinicopathologic features.

• Nomogram A was used to predict axillary lymph node metastasis (presence vs. absence). The AUCs in the training and validation groups were 0.83 and 0.78, respectively. Nomogram B was used to estimate the number of metastatic lymph nodes ( ≤ 2 vs. > 2). The AUCs in the training and validation group were 0.87 and 0.87, respectively.

• Our nomograms may help clinicians weigh the risks and benefits of axillary surgery more appropriately.

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Abbreviations

ACOSOG:

American College of Surgeons Oncology Group

ALN:

Axillary lymph node

ALND:

Axillary lymph node dissection

ASCO:

American Society of Clinical Oncology

ER:

Estrogen receptor

FNR:

False-negative rate

Her-2:

Human epidermal growth factor receptor-2

MSKCC:

Memorial Sloan-Kettering Cancer Center

PR:

Progesterone receptor

SLN:

Sentinel lymph node

SLNB:

Sentinel lymph node biopsy

TILs:

Tumor-infiltrating lymphocytes

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Acknowledgements

This study was supported by grants from the National Natural Science Foundation of China (81972467), the Guangdong Natural Science Foundation (2020A1515010458), and the Guangzhou Science Technology and Innovation Commission (202102010221, 20212200003). We appreciate the assistance from Artificial Intelligence Lab, Sun Yat-sen Memorial Hospital. We thank all the individuals who took part in these studies and all the researchers, clinicians, and technicians who have enabled this work to be carried out.

Funding

This study has received funding from the National Natural Science Foundation of China (81972467), the Guangdong Natural Science Foundation (2020A1515010458), and the Guangzhou Science Technology and Innovation Commission (202102010221, 20212200003).

Author information

Author notes

  1. Wengcheng Fong and Luyuan Tan contributed equally to this work.

Authors and Affiliations

  1. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China

    Wengcheng Fong, Luyuan Tan, Cui Tan, Hongli Wang, Fengtao Liu, Huan Tian, Shiyu Shen, Ran Gu, Yue Hu, Xiaofang Jiang, Jingsi Mei, Jing Liang, Tingting Hu, Kai Chen & Fengyan Yu

  2. Department of Breast Surgery, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiang West Road, Guangzhou, 510120, China

    Wengcheng Fong, Luyuan Tan, Huan Tian, Tingting Hu, Kai Chen & Fengyan Yu

  3. Department of Pathology, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Cui Tan

  4. Diagnostic Department, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Hongli Wang, Fengtao Liu, Shiyu Shen, Ran Gu, Yue Hu, Xiaofang Jiang, Jingsi Mei & Jing Liang

  5. Artificial Intelligence Laboratory, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China

    Kai Chen

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  1. Wengcheng Fong
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  14. Kai Chen
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  15. Fengyan Yu
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Corresponding authors

Correspondence to Kai Chen or Fengyan Yu.

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Guarantor

The scientific guarantor of this publication is Fengyan Yu, MD, PHD.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

Yaping Yang (Diagnostic Department, Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China) specializes in statistical analysis and provided statistical advice in this study.

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Written informed consent was obtained from all subjects (patients) in this study.

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Institutional Review Board approval was obtained.

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• prospective

• diagnostic or prognostic study

• performed at one institution

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Fong, W., Tan, L., Tan, C. et al. Predicting the risk of axillary lymph node metastasis in early breast cancer patients based on ultrasonographic-clinicopathologic features and the use of nomograms: a prospective single-center observational study. Eur Radiol 32, 8200–8212 (2022). https://doi.org/10.1007/s00330-022-08855-8

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  • DOI: https://doi.org/10.1007/s00330-022-08855-8

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