ArticleMedical science monitor : international medical journal of experimental and clinical research2017
Predictive Value of Clinicopathological Characteristics for Sentinel Lymph Node Metastasis in Early Breast Cancer.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 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
- Predictors of sentinel lymph node metastasis in cT1-2 cN0 breast cancer: A retrospective cohort study.Medicine · 2026Article
- Integrating intratumoral and peritumoral ultrasound radiomics with clinicopathological features to predict axillary lymph node metastasis in early breast cancer.Gland surgery · 2026Article
- Deep learning-powered multi-parametric ultrasound for classifying metastatic versus reactive axillary lymph nodes.Breast cancer research : BCR · 2025Article
- Differences in Sentinel lymph node biopsy outcomes and prognosis between HER2-low and HER2-zero breast cancer.BMC cancer · 2025Article
- Preoperative ultrasonography-guided core-needle biopsy-based factors for predicting the upgrade of axillary lymph nodes in breast cancer.Quantitative imaging in medicine and surgery · 2025Article
- Ki-67 and 21-gene recurrence score assay in decision making for adjuvant chemotherapy in breast cancer patients.Discover oncology · 2025Review
- Construction of a prediction model for axillary lymph node metastasis in breast cancer patients based on a multimodal fusion strategy of ultrasound and pathological images.Frontiers in oncology · 2025Article
- Development of fully automated deep-learning-based approach for prediction of sentinel lymph node metastasis in breast cancer patients using ultrasound imaging.Frontiers in oncology · 2025Article
- Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- A nomogram model for predicting the risk of axillary lymph node metastasis in patients with early breast cancer and cN0 status.Oncology letters · 2024Article
- Investigating the role of tumour-to-skin proximity in predicting nodal metastasis in breast cancer.Breast cancer research and treatment · 2024Article
- Prediction of sentinel lymph node metastasis in breast cancer patients based on preoperative features: a deep machine learning approach.Scientific reports · 2024Article
- Factors Predictive of Positive Lymph Nodes for Breast Cancer.Current oncology (Toronto, Ont.) · 2023Article
- Impact of oral statin therapy on clinical outcomes in patients with cT1 breast cancer.BMC cancer · 2023Article
- Subtype of breast cancer influences sentinel lymph node positivity.Archives of medical science : AMS · 2023Article
- Predictive Factors for Unnecessary Axillary Dissection According to SLN Metastasis in T1, T2 Stage Breast Cancer.Indian journal of surgical oncology · 2022Article
- Prediction of Sentinel Lymph Node Biopsy Status in Breast Cancers with PET/CT Negative Axilla.World journal of nuclear medicine · 2022Article
- Differences in tumor-infiltrating lymphocyte density and prognostic factors for breast cancer by patient age.World journal of surgical oncology · 2022Article
- Analysis of the Influencing Factors of Sentinel Lymph Node Metastasis in Breast Cancer.Evidence-based complementary and alternative medicine : eCAM · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Sentinel lymph node biopsy (SLNB) is one of the preferred treatments for breast cancer including clinically negative lymph node breast cancer. However, for 60-70% of patients this invasive axilla surgery is unnecessary. Our study aimed to identify the predictors for sentinel lymph node (SLN) metastasis in early breast cancer patients and provide evidence for rational decision-making in specified clinical situations. MATERIAL AND METHODS Medical records of 417 breast cancer patients who were treated with a breast surgical procedure and SLNB in Ningbo Medical Center Lihuili Eastern Hospital were retrospectively reviewed. Univariate analysis and multivariate logistic regression analysis were used to analyze the correlation between SLN metastasis and clinicopathological characteristics, including patient age, menstrual status, body mass index (BMI), family history, tumor size, laterality of tumor, histological grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 index, and molecular subtypes of the tumor. RESULTS In the cohort of 417 cases, the ratio of SLNM was 23.0%. Univariate analysis found that age, tumor size, histological grade, and Ki67 index were associated with SLN metastasis. However, age, tumor size, and histological grade were the only three independent predictors for SLN metastasis by multivariate logistic regression analysis. When these three factors were considered together, three different levels of SLN metastasis groups could be classified: low-risk group with the ratio of 14.3%, moderate-risk group with the ratio of 31.4%, and high-risk group with the ratio of 66.7%. CONCLUSIONS Our study demonstrated that age, tumor size, and histological grade were three independent predictive factors for SLN metastasis in early breast cancer patients. This finding may help surgeons in the decision-making process for early breast cancer patients before considering axilla surgical procedure.
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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.