scholarly journals Corrigendum: Decreased Survival of Invasive Ductal Breast Cancer Patients With Two Macrometastatic Lymph Nodes Among Few Resected Ones: Should Current Sentinel-Lymph-Node Guidelines Be Revised?

2021 ◽  
Vol 11 ◽  
Author(s):  
Felipe A. C. Luz ◽  
Rogério A. Araújo ◽  
Marcelo J. B. Silva
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Breast Cancer Patients ◽  
Invasive Ductal Breast Cancer ◽  
Ductal Breast Cancer

Number of lymph nodes removed in sentinel lymph node-negative breast cancer patients is significantly related to patient age and tumor size

Cancer ◽  
2010 ◽  
Vol 116 (8) ◽  
pp. 1987-1991 ◽  
Author(s):  
Elisa Rush Port ◽  
Sujata Patil ◽  
Michelle Stempel ◽  
Monica Morrow ◽  
Hiram S. Cody
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Tumor Size ◽  
Breast Cancer Patients ◽  
Patient Age ◽  
Node Negative ◽  
Node Negative Breast Cancer

scholarly journals Development of a prediction model based on LASSO regression to evaluate the risk of non-sentinel lymph node metastasis in Chinese breast cancer patients with 1–2 positive sentinel lymph nodes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Meng ◽  
Ting Zheng ◽  
Yuanyuan Wang ◽  
Zhao Li ◽  
Qi Xiao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Lymph Nodes ◽  
Prediction Model ◽  
Cancer Patients ◽  
Sentinel Lymph Nodes ◽  
Lasso Regression ◽  
Breast Cancer Patients ◽  
Positive Slns

AbstractThis study aimed to develop an intraoperative prediction model to evaluate the risk of non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer patients with 1–2 positive sentinel lymph nodes (SLNs). The clinicopathologic data of 714 patients with 1–2 positive SLNs were investigated. Univariate and multivariate analyses were performed to identify the risk factors of NSLN metastasis. A new mathematical prediction model was developed based on LASSO and validated in an independent cohort of 131 patients. The area under the receiver operating characteristic curve (AUC) was used to quantify performance of the model. Patients with NSLN metastasis accounted for 37.3% (266/714) and 34.3% (45/131) of the training and validation cohorts, respectively. A LASSO regression-based prediction model was developed and included the 13 most powerful factors (age group, clinical tumour stage, histologic type, number of positive SLNs, number of negative SLNs, number of SLNs dissected, SLN metastasis ratio, ER status, PR status, HER2 status, Ki67 staining percentage, molecular subtype and P53 status). The AUCs of training and validation cohorts were 0.764 (95% CI 0.729–0.798) and 0.777 (95% CI 0.692–0.862), respectively. We presented a new prediction model with excellent clinical applicability and diagnostic performance for use by clinicians as an intraoperative clinical tool to predict risk of NSLN metastasis in Chinese breast cancer patients with 1–2 positive SLNs and make the final decisions regarding axillary lymph node dissection.

scholarly journals Risk factors for non-sentinel lymph node metastases in breast cancer patients with positive sentinel lymph nodes

2008 ◽  
Vol 121 (20) ◽  
pp. 2107-2109 ◽  
Author(s):  
Tao ZHANG ◽  
Hong WANG ◽  
Bao-ping CHEN ◽  
Hai-song ZHANG ◽  
Xi-liang WEI ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Lymph Nodes ◽  
Cancer Patients ◽  
Lymph Node Metastases ◽  
Sentinel Lymph Nodes ◽  
Breast Cancer Patients ◽  
Node Metastases
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