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. 2025 Jan-Dec:32:10732748251363328.
doi: 10.1177/10732748251363328. Epub 2025 Jul 27.

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

Xinhua Zhang  1   2 , Chuang Zhang  3 , Jian Zhang  2 , Xiuming Zhang  1 , Xiaowen Dou  2
Affiliations

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

Xinhua Zhang et al. Cancer Control. 2025 Jan-Dec.

Abstract

IntroductionThis study aimed to assess the predictive value of integrating ultrasonographic features, pathological characteristics, and inflammatory markers for axillary lymph node metastasis (ALNM) in early-stage breast cancer (BC), and to construct a corresponding nomogram.MethodsA retrospective review was conducted on clinical data from 287 early-stage BC patients who underwent surgery at Shenzhen Luohu People's Hospital between January 2020 and March 2024. Based on histopathological evaluation, patients were categorized into ALNM-positive (ALNM+) and ALNM-negative (ALNM-) groups. Independent predictors of ALNM were identified using univariate and multivariate logistic regression analyses. These variables were used to develop a predictive nomogram. Model performance was evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA), assessing its accuracy, discrimination, calibration, and clinical utility.ResultsMultivariate analysis identified vascular invasion, neutrophil-to-lymphocyte ratio (NLR), lymphocyte count, tumor size, lymph node echogenicity, and margin characteristics as independent predictors of ALNM. The nomogram showed excellent discriminative ability (AUC = 0.944, 95% CI: 0.906-0.981; C-index = 0.944, 95% CI: 0.906-0.982) and good calibration (Brier score = 0.063). DCA indicated meaningful clinical benefit across relevant threshold probabilities.ConclusionThe nomogram developed in this study demonstrates strong predictive performance and clinical value for preoperative ALNM assessment in early-stage BC. It may serve as a practical tool to guide individualized surgical and therapeutic decision-making.

Keywords: axillary lymph node metastasis (ALNM); breast cancer (BC); inflammatory markers; nomogram; risk.

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Conflict of interest statement

Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Flow Chart. Illustration of Patient Inclusion
Figure 2.
Figure 2.
Two Groups of Patients With Axillary Lymph Node Metastasis (A) Proportion of Vascular invasion; (B) Proportion of Tumor Size
Figure 3.
Figure 3.
(A) Correlations Between Variables; (B) the Importance Ranking of Significant Variables in Univariate Analysis
Figure 4.
Figure 4.
A Nomogram for Predicting the Risk of Lymph Node Metastasis in Early Breast Cancer
Figure 5.
Figure 5.
(A) The Receiver Operating Characteristic Curve (ROC) of the Nomogram; (B) the Calibration Curve
Figure 6.
Figure 6.
DCA Analysis of ALNM Prediction Model for Breast Cancer
See this image and copyright information in PMC

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