ArticleBMC cancer2023
A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection.
Article in BMC cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Whole-brain radiotherapy with simultaneous integrated boost in treatment of patients with brain metastases: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Whole-brain radiotherapy with simultaneous integrated boost in treatment of patients with brain metastases: a systematic review and meta-analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Harnessing cuproptosis: a new avenue for targeted cancer therapies.Apoptosis : an international journal on programmed cell death · 2025Review
- A non-invasive preoperative model for predicting sentinel lymph node metastasis in breast cancer using clinical data and MRI.BMC medical imaging · 2025Article
- Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model.European journal of medical research · 2025Article
- Sonographic localisation of lymph nodes suspicious of metastatic breast cancer to surgical axillary levels.Journal of medical radiation sciences · 2025Review
- Prediction of axillary nodal burden using preoperative magnetic resonance imaging scoring in patients with clinically node-negative breast cancer: a retrospective cohort study.Gland surgery · 2024Article
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Abstract
backgroundTo develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features. METHODS AND MATERIALS: Patients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0-2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors.
resultsUnivariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749.
conclusionOur model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.
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