Intraoperative Molecular Analysis of Total Tumor Load in Sentinel Lymph Node: A Predictor of Axillary Status in Early Breast Cancer

Document Type : Research Articles


Division of General Surgery, Faculty of Medicine, Songklanagarind Hospital, Prince of Songkla University, Songkhla, Thailand.


Background: Axillary lymph node dissection (ALND) remains the standard of care in breast cancer patients with positive sentinel lymph node (SLN). However, approximately 40–60% of patients with positive SLNs have not developed to non-SLN metastasis and ALND seems to be an overtreatment. The purpose of this study was to analyze predictors and define a specific cut-off of total tumor load (TTL) of CK19 that can be used as a predictive factor of non-SLN metastasis in early breast cancer patients. Materials and Methods: The records of 238 patients with cT1-3N0 breast cancer who had an intraoperative SLN evaluation performed through One-Step nucleic acid (OSNA) assay at Songklanagarind Hospital between 1 January 2015 and 31 December 2019 were examined. Univariate and Multivariate analysis was used to identify clinicopathologic features in SLN-positive patients that predict metastasis to non-SLNs. Finally, receiver operative characteristics (ROC) curves were used to choose an optimal TTL cut-off value. Results: Of a total of 110 patients who had a positive SLN, only 48 (43.64%) were found to have positive nodes in non-SLN. Multivariate analysis revealed that lymphovascular invasion, type of SLN metastasis and SLN TTL (copies/μL) were independent predictors of positive non-SLNs.  TTL cut-off value was 19,000 copies/μL, with an AUC of 0.838 with 72.7% sensitivity and 84.7% specificity to predict non-SLN metastasis. Conclusions: The likelihood of positive non-SLNs in patients who showed a positive SLN correlates with lymphovascular invasion, type of SLN metastasis and SLN TTL (copies/μL). Our result revealed that the patients with a SLN TTL ≥19,000 copies/µl continue to attract the recommendation to proceed with ALND. This cut-off value can then help clinicians to assess which patients would benefit from ALND.


Main Subjects

Volume 23, Issue 1
January 2022
Pages 349-354
  • Receive Date: 30 September 2021
  • Revise Date: 18 November 2021
  • Accept Date: 17 January 2022
  • First Publish Date: 17 January 2022