ArticleSensors (Basel, Switzerland)2012
A logistic regression model for predicting axillary lymph node metastases in early breast carcinoma patients.
Article in Sensors (Basel, Switzerland), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Construction of a prediction model for axillary lymph node metastasis in stage cN0 hormone receptor-positive breast cancer: based on interpretable machine learning methods.Frontiers in oncology · 2026Article
- Tumor characteristics and survival rate of axillary metastatic breast cancer patients: a three decades retrospective cohort study.Scientific reports · 2025Article
- Assessment of the axilla in women with early-stage breast cancer undergoing primary surgery: a review.World journal of surgical oncology · 2024Review
- Association between postoperative pathological results and non-sentinel nodal metastasis in breast cancer patients with sentinel lymph node-positive breast cancer.World journal of surgical oncology · 2024Article
- Article
- Evaluation of KISS1 Receptor Gene Expression in Egyptian Female Patients with Breast Cancer.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- Method for Data Quality Assessment of Synthetic Industrial Data.Sensors (Basel, Switzerland) · 2022Article
- Could Ultrasound-Based Radiomics Noninvasively Predict Axillary Lymph Node Metastasis in Breast Cancer?Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2020Article
- KISS1 in metastatic cancer research and treatment: potential and paradoxes.Cancer metastasis reviews · 2020Review
- Independent risk factors for axillary lymph node metastasis in breast cancer patients with one or two positive sentinel lymph nodes.BMC women's health · 2020Article
- A Model to Predict the Risk of Lymph Node Metastasis in Breast Cancer Based on Clinicopathological Characteristics.Cancer management and research · 2020Article
- Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer.European radiology · 2019Article
- Development and Validation of Nomograms Predictive of Axillary Nodal Status to Guide Surgical Decision-Making in Early-Stage Breast Cancer.Journal of Cancer · 2019Article
- Kisspeptin and Cancer: Molecular Interaction, Biological Functions, and Future Perspectives.Frontiers in endocrinology · 2018Review
- A logistic regression model predicting high axillary tumour burden in early breast cancer patients.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2017Article
- Article
- Prediction of lateral pelvic lymph node metastasis from lower rectal cancer using magnetic resonance imaging and risk factors for metastasis: Multicenter study of the Lymph Node Committee of the Japanese Society for Cancer of the Colon and Rectum.International journal of colorectal disease · 2017Article
- 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
- Development of nomograms to predict axillary lymph node status in breast cancer patients.BMC cancer · 2017Article
- Article
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Nodal staging in breast cancer is a key predictor of prognosis. This paper presents the results of potential clinicopathological predictors of axillary lymph node involvement and develops an efficient prediction model to assist in predicting axillary lymph node metastases. Seventy patients with primary early breast cancer who underwent axillary dissection were evaluated. Univariate and multivariate logistic regression were performed to evaluate the association between clinicopathological factors and lymph node metastatic status. A logistic regression predictive model was built from 50 randomly selected patients; the model was also applied to the remaining 20 patients to assess its validity. Univariate analysis showed a significant relationship between lymph node involvement and absence of nm-23 (p = 0.010) and Kiss-1 (p = 0.001) expression. Absence of Kiss-1 remained significantly associated with positive axillary node status in the multivariate analysis (p = 0.018). Seven clinicopathological factors were involved in the multivariate logistic regression model: menopausal status, tumor size, ER, PR, HER2, nm-23 and Kiss-1. The model was accurate and discriminating, with an area under the receiver operating characteristic curve of 0.702 when applied to the validation group. Moreover, there is a need discover more specific candidate proteins and molecular biology tools to select more variables which should improve predictive accuracy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.