ArticleSpringerPlus2016
Role of patient and tumor characteristics in sentinel lymph node metastasis in patients with luminal early breast cancer: an observational study.
Article in SpringerPlus, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- The role of preoperative lymphoscintigraphy in sentinel lymph node identification among patients with breast cancer: a retrospective study.Journal of medicine and life · 2026Article
- Ultrasound-based attention-guided deep learning combined with radiomics to predict axillary lymph node metastasis in breast cancer.BMC medical imaging · 2026Article
- Detection of Sentinel Lymph Node in Endometrial Cancer UsingWorld journal of nuclear medicine · 2025Article
- Ultrasound radiomics predicts preoperative axillary lymph node metastasis status in early-stage breast cancer to support surgical decisions: a machine learning, monocenter study.Frontiers in oncology · 2025Article
- A cutting-edge deep learning-and-radiomics-based ultrasound nomogram for precise prediction of axillary lymph node metastasis in breast cancer patients ≥ 75 years.Frontiers in endocrinology · 2024Article
- Machine-learning methods based on the texture and non-texture features of MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer.Translational cancer research · 2023Article
- Subtype of breast cancer influences sentinel lymph node positivity.Archives of medical science : AMS · 2023Article
- Ultrasound radiomics based on axillary lymph nodes images for predicting lymph node metastasis in breast cancer.Frontiers in oncology · 2023Article
- A Radiomics Model for Preoperative Predicting Sentinel Lymph Node Metastasis in Breast Cancer Based on Dynamic Contrast-Enhanced MRI.Frontiers in oncology · 2022Article
- Nomogram models for stratified prediction of axillary lymph node metastasis in breast cancer patients (cN0).Frontiers in endocrinology · 2022Article
- Predictive Factors Among Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in T1-T2 Breast Cancer.Cancer management and research · 2021Article
- Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer.Nature communications · 2020Article
- Expression of Stanniocalcin 2 in Breast Cancer and Its Clinical Significance.Current medical science · 2019Article
- Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast-enhanced MRI.Journal of magnetic resonance imaging : JMRI · 2019Article
- Biological Subtypes of Breast Cancer and Sentinel Lymph Node Biopsy.European journal of breast health · 2018Article
- Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI.European radiology · 2018Article
- Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2017Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting the risk of sentinel lymph node (SLN) metastasis is important for clinical decision-making in the setting of early breast cancer (EBC). This study is aimed to identify tumor and patient characteristics that influenced the SLN metastatic involvement, with a focus on luminal subtypes. An observational study including women treated for EBC from 2005 to 2013 was conducted. Regression analyses were used to assess the association between SLN metastasis and age, menopausal status, tumor size, histological grading, presence of extensive "in situ" carcinoma components, lymphovascular invasion (LVI), and expression of Ki-67, hormone receptors, and HER2. Of 345 women, 84 (24.3 %) had at least one SLN metastasis; 63.1 % were macrometastases. Among all patients, 31.6 % exhibited LVI. In univariate analyses, tumor size, histological grade, and LVI were associated with SLN metastasis. The multivariate model confirmed only the association between LVI and SLN status (OR 3.27, 95 % CI 1.85-5.68; p < 0.0001). Luminal subtypes were detected in 86.1 % of women. In this subgroup, the multivariate model confirmed a significant relationship between LVI and SLN status (OR 3.47, 95 % CI 1.90-6.33; p < 0.0001). Since a proper histopathological assessment of LVI is not possible prior to surgery, this factor cannot be used to guide decisions on performing SLN biopsies. Nevertheless, when a SLN biopsy is refused or contraindicated, an LVI assessment on an excisional biopsy of the tumor could facilitate prognosis determination and treatment management.
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Registered trials
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