ArticleBMC cancer2024
Diagnostic value of applying preoperative breast ultrasound and clinicopathologic features to predict axillary lymph node burden in early invasive breast cancer: a study of 1247 patients.
Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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15 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
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- Nomogram prediction model for pathological complete response of metastatic axillary lymph nodes of breast cancer after neoadjuvant chemotherapy.BMC medical imaging · 2026Article
- Nomogram combining clinical and ultrasonographic features for differentiating granulomatous lobular mastitis from invasive lobular carcinoma.Frontiers in oncology · 2026Article
- Preoperative total cholesterol and axillary lymph node burden in breast cancer: an exploratory analysis with a preliminary nomogram.Frontiers in surgery · 2026Article
- Article
- Long-term Outcomes of Early Breast Cancer Stratified by Axillary Ultrasound Assessment.Journal of breast cancer · 2025Article
- Preoperative Axillary Ultrasound in the Era of Z0011: A Model for Predicting High Axillary Disease Burden.Current oncology (Toronto, Ont.) · 2025Article
- Bi-modal ultrasound radiomics and habitat analysis enhanced the pre-operative prediction of axillary lymph node burden in patients with early-stage breast cancer.Frontiers in oncology · 2025Article
- Integration of multi-imaging technique and immunohistochemistry for the development of a predictive nomogram for axillary lymph node metastasis in breast cancer.Frontiers in endocrinology · 2025Article
- Predicting the axillary lymph node tumor burden in breast cancer patients using ultrasonic radiomics nomogram model.PloS one · 2025Article
- Prediction of axillary lymph node metastasis in breast cancer patients based on ultrasonograhic-clinicopathologic features.Pakistan journal of medical sciences · 2025Article
- Predicting Axillary Lymph Node Metastasis in Young Onset Breast Cancer: A Clinical-Radiomics Nomogram Based on DCE-MRI.Breast cancer (Dove Medical Press) · 2025Article
- Article
- Clinically node-negative invasive lobular carcinoma of the breast showing multiple lymph node metastases.Radiology case reports · 2024Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSince the Z0011 trial, the assessment of axillary lymph node status has been redirected from the previous assessment of the occurrence of lymph node metastasis alone to the assessment of the degree of lymph node loading. Our aim was to apply preoperative breast ultrasound and clinicopathological features to predict the diagnostic value of axillary lymph node load in early invasive breast cancer.
methodsThe 1247 lesions were divided into a high lymph node burden group and a limited lymph node burden group according to axillary lymph node status. Univariate and multifactorial analyses were used to predict the differences in clinicopathological characteristics and breast ultrasound characteristics between the two groups with high and limited lymph node burden. Pathological findings were used as the gold standard.
resultsUnivariate analysis showed significant differences in ki-67, maximum diameter (MD), lesion distance from the nipple, lesion distance from the skin, MS, and some characteristic ultrasound features (P < 0.05). In multifactorial analysis, the ultrasound features of breast tumors that were associated with a high lymph node burden at the axilla included MD (odds ratio [OR], 1.043; P < 0.001), shape (OR, 2.422; P = 0.0018), hyperechoic halo (OR, 2.546; P < 0.001), shadowing in posterior features (OR, 2.155; P = 0.007), and suspicious lymph nodes on axillary ultrasound (OR, 1.418; P = 0.031). The five risk factors were used to build the predictive model, and it achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.702.
conclusionBreast ultrasound features and clinicopathological features are better predictors of high lymph node burden in early invasive breast cancer, and this prediction helps to develop more effective treatment plans.
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