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Establishment of Prediction Model of Axillary Lymph Node Metastasis Before Operation for Early-Stage Breast Cancer

  • 0School of Medicine, Anhui University of Science and Technology, Huainan, Anhui, China.
Cancer Control : Journal of the Moffitt Cancer Center +

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July 28, 2025

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July 28, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A new nomogram integrating ultrasound, pathology, and inflammatory markers accurately predicts axillary lymph node metastasis (ALNM) in early breast cancer (BC). This tool aids in personalized treatment decisions for patients with early-stage breast cancer.

Area Of Science

  • Oncology
  • Radiology
  • Pathology

Background

  • Axillary lymph node metastasis (ALNM) is a critical prognostic factor in early-stage breast cancer (BC).
  • Accurate preoperative assessment of ALNM is essential for guiding treatment strategies and improving patient outcomes.

Purpose Of The Study

  • To develop and validate a predictive nomogram for ALNM in early-stage BC.
  • To integrate ultrasonographic features, pathological characteristics, and inflammatory markers for enhanced prediction.

Main Methods

  • Retrospective analysis of 287 early-stage BC patients.
  • Logistic regression to identify independent predictors of ALNM.
  • Nomogram construction and validation using C-index, ROC curve, calibration plot, and DCA.

Main Results

  • Vascular invasion, NLR, lymphocyte count, tumor size, lymph node echogenicity, and margin characteristics were independent predictors.
  • The nomogram demonstrated excellent discrimination (AUC=0.944) and good calibration.
  • Decision curve analysis confirmed significant clinical utility.

Conclusions

  • The developed nomogram is a valuable tool for preoperative ALNM assessment in early-stage BC.
  • It can assist in personalized surgical and therapeutic decision-making.
  • This integrated approach enhances predictive accuracy for ALNM.

Keywords: