scholarly journals The Clinical Relevance of Target Lymph Node Biopsy after Primary Systemic Therapy in Initially Node-Positive Breast Cancer Patients

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2620
Author(s):  
Steffi Hartmann ◽  
Angrit Stachs ◽  
Gesche Schultek ◽  
Bernd Gerber ◽  
Toralf Reimer

Purpose: To assess the impact of the removal of the target lymph node (TLN) on therapy after the completion of primary systemic therapy (PST) in initially node-positive breast cancer patients. Methods: Pooled data analysis of participants of the prospective CLIP- and TATTOO-study at the University of Rostock was performed. Results: A total of 75 patients were included; 63 of them (84.0%) converted to clinically node-negative after PST. Both TLN and sentinel lymph node (SLN) were identified in 41 patients (51.2%). In five out of 63 patients (7.9%), the TLN was metastatic after PST and the SLN was either tumor-free or not detected. Axillary lymph node dissection (ALND) was conducted in all five patients. In one patient, systemic therapy recommendation was influenced by the TLN; adjuvant radiotherapy was influenced by the TLN in zero patients. For patients with fewer than three removed SLNs, the FNR was 28.6% for the SLN biopsy alone and 7.1% for targeted axillary dissection (TAD). Conclusions: Removal of the TLN in addition to the SLN after PST has only minimal impact on the type of adjuvant systemic therapy and radiotherapy. However, the extent of axillary surgery was relevantly affected and FNR was improved by TAD.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e12090-e12090
Author(s):  
Wenyan Wang ◽  
Xin Wang ◽  
Xiang Wang ◽  
Jiaqi Liu ◽  
Pin Zhang

e12090 Background: Pathological complete response (pCR) of axillary lymph nodes (ALNs) is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC), and ALN status is an important prognostic factor for breast cancer patients. Our goal is to develop a new predictive clinical model to assess the axillary lymph node pCR rate after NAC. Methods: A retrospective series of 547 patients who had biopsy-proven positive ALNs at diagnosis and undergoing axillary lymph node dissection from 2007 to 2014 in National Cancer Center/Cancer Hospital of Chinese Academy of Medical Sciences. We analyzed the clinicopathologic features and developed a nomogram to predict the probability of ALN pCR. Univariate assessment was performed using a logistic regression model. A multivariate logistic regression stepwise model was used to generate a nomogram to predict ALN pCR in node positive patients Variables with P < 0.05 on multivariable analysis were included in the nomogram. The adjusted area under the receiver operating characteristic curve (AUC) was calculated to quantify the ability to rank patients by risk. Internal validation was estimated using 50-50 hold out validation method. Nomogram was validated externally with the prospective cohort of 167 patients from 2016 to 2018. Results: In retrospective study, there were 172 (31.4%) patients achieved axillary pCR after NAC. Multivariate analysis indicated that clinical nodal (N) stage, hormone receptor (HR) status and clinical response of primary tumor after NAC were significant independent predictors for axillary pCR ( P< 0.05). The NAC nomogram was based on these three variables. In the internal validation of performance, the AUCs for the training and test sets were 0.719 and 0.753, respectively. The nomogram was validated in an external cohort with an AUC of 0.734. Conclusions: We developed a nomogram to predict the likelihood of axillary pCR in node positive breast cancer patients after NAC. The predictive model performed well in prospective external validation. This practical tool could provide information to surgeons regarding whether to perform additional ALND after NAC.


2021 ◽  
Author(s):  
Wenyan Wang ◽  
Xin Wang ◽  
Xiang Wang ◽  
Pilin Wang

Abstract Background Pathological complete response (pCR) of axillary lymph nodes (ALNs) is frequently achieved in patients with clinically node-positive breast cancer after neoadjuvant chemotherapy (NAC), and ALN status is an important prognostic factor for breast cancer patients. Our goal is to develop a new predictive clinical model to assess the axillary lymph node pCR rate after NAC. Methods A retrospective series of 547 patients who had biopsy-proven positive ALNs at diagnosis and undergoing axillary lymph node dissection from 2007 to 2014 in National Cancer Center/Cancer Hospital of Chinese Academy of Medical Sciences. We analyzed the clinicopathologic features and developed a nomogram to predict the probability of ALN pCR. Univariate assessment was performed using a logistic regression model. A multivariate logistic regression stepwise model was used to generate a nomogram to predict ALN pCR in node positive patients Variables with P < 0.05 on multivariable analysis were included in the nomogram. The adjusted area under the receiver operating characteristic curve (AUC) was calculated to quantify the ability to rank patients by risk. Internal validation was estimated using 50–50 hold out validation method. Nomogram was validated externally with the prospective cohorts of 167 patients from 2016 to 2018 of Cancer Hospital of Chinese Academy of Medical Sciences and 75 patients from 2018 to 2019 of Beijing Tiantan hospital. Results In retrospective study, there were 172 (31.4%) patients achieved axillary pCR after NAC. Multivariate analysis indicated that clinical nodal (N) stage, estrogen receptor (ER) status and clinical response of primary tumor after NAC were significant independent predictors for axillary pCR (P < 0.05). The NAC nomogram was based on these three variables. In the internal validation of performance, the AUCs for the training and test sets were 0.719 and 0.753, respectively. The nomogram was validated in external cohorts with AUCs of 0.862 and 0.766, respectively, which demonstrated good discriminatory power in the external validation data sets. Conclusion We developed a nomogram to predict the likelihood of axillary pCR in node positive breast cancer patients after NAC. The predictive model performed well in multicenter prospective external validation. This practical tool could provide information to surgeons regarding whether to perform additional ALND after NAC.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianqian Yuan ◽  
Jinxuan Hou ◽  
Yukun He ◽  
Yiqian Liao ◽  
Lewei Zheng ◽  
...  

Abstract Background Breast cancer-related lymphedema (BCRL) is associated with extensive axillary dissection. Axillary lymph node dissection (ALND) based on breast lymphatics level (BLL) was proposed to minimize the surgical extent for node-positive breast cancer patients. Methods A total of 156 consecutive sentinel lymph node-positive (SLN+) or clinically node-positive (cN+) patients underwent sentinel lymph node biopsy (SLNB) with indocyanine green and methylene blue (MB). The SLNs were injected with 0.1 ml MB before removal, and a standard ALND was subsequently performed. The nodes adjacent to the blue-stained axillary lymph nodes from the breast (bALNs) were sent for pathological examination separately by resecting serial tissue every 0.5 cm away from the marginal blue-stained bALNs. Then, a pilot study comparing ALND based on BLL and standard ALND was performed. Results BLL were successfully identified in 20 SLN+ (100%) and 134 cN+ (98.5%) patients. The median number of BLL was four, ranging from three to six. A horizontal line 1.0 cm away from the superior blue-stained bALN and a vertical line 1.0 cm away from the medial blue-stained bALN formed BLL II, III, and IV. All of the additional positive nodes were within 1.0 cm of the blue-stained bALNs. The minimized axillary dissection should resect upwards from the lowest BLL that contains the first confirmed negative blue-stained bALNs. In the pilot study, no patient developed axillary recurrence. Conclusion The ALND surgical procedure based on BLL could minimize the surgical extent for pathological node-positive breast cancer patients and potentially reduce the BCRL rate. Trial registration ChiCTR1800014247.


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