scholarly journals Do axillary sentinel lymph node micrometastases predict involvement of the non-sentinel lymph nodes in breast cancer?

2013 ◽  
Vol 11 (8) ◽  
pp. 610
Author(s):  
Ashley Topps ◽  
Emma de Sousa ◽  
Katherine McNamara ◽  
Katherine Miller ◽  
Mohammed Absar
2017 ◽  
Vol 44 (6) ◽  
pp. 612-618
Author(s):  
PAULO HENRIQUE WALTER DE AGUIAR ◽  
RANNIERE GURGEL FURTADO DE AQUINO ◽  
MAYARA MAIA ALVES ◽  
JULIO MARCUS SOUSA CORREIA ◽  
AYANE LAYNE DE SOUSA OLIVEIRA ◽  
...  

ABSTRACT Objective: to verify the agreement rate in the identification of sentinel lymph node using an autologous marker rich in hemosiderin and 99 Technetium (Tc99) in patients with locally advanced breast cancer. Methods: clinical trial phase 1, prospective, non-randomized, of 18 patients with breast cancer and clinically negative axilla stages T2=4cm, T3 and T4. Patients were submitted to sub-areolar injection of hemosiderin 48 hours prior to sentinel biopsy surgery, and the identification rate was compared at intraoperative period to the gold standard marker Tc99. Agreement between methods was determined by Kappa index. Results: identification rate of sentinel lymph node was 88.9%, with a medium of two sentinel lymph nodes per patients. The study identified sentinel lymph nodes stained by hemosiderin in 83.3% patients (n=15), and, compared to Tc99 identification, the agreement rate was 94.4%. Conclusion: autologous marker rich in hemosiderin was effective to identify sentinel lymph nodes in locally advanced breast cancer patients.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Meng ◽  
Ting Zheng ◽  
Yuanyuan Wang ◽  
Zhao Li ◽  
Qi Xiao ◽  
...  

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.


2008 ◽  
Vol 121 (20) ◽  
pp. 2107-2109 ◽  
Author(s):  
Tao ZHANG ◽  
Hong WANG ◽  
Bao-ping CHEN ◽  
Hai-song ZHANG ◽  
Xi-liang WEI ◽  
...  

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