Celso Nabais1, Joana Figueiredo2, Paulina Lopes2, Manuela Martins3, António Araújo2. 1. Department of Surgery, Centro Hospitalar Lisboa Central, Portugal. Electronic address: celso.nabais@gmail.com. 2. Department of Surgery, Centro Hospitalar Lisboa Central, Portugal. 3. Department of Pathology, Centro Hospitalar Lisboa Central, Portugal.
Abstract
BACKGROUND: This study aimed to determine the relationship between CK19 mRNA copy number in sentinel lymph nodes (SLN) assessed by one-step nucleic acid amplification (OSNA) technique, and non-sentinel lymph nodes (NSLN) metastization in invasive breast cancer. A model using total tumor load (TTL) obtained by OSNA technique was also constructed to evaluate its predictability. METHODS: We conducted an observational retrospective study including 598 patients with clinically T1-T3 and node negative invasive breast cancer. Of the 88 patients with positive SLN, 58 patients fulfill the inclusion criteria. RESULTS: In the analyzed group 25.86% had at least one positive NSLN in axillary lymph node dissection. Univariate analysis showed that tumor size, TTL and number of SLN macrometastases were predictive factors for NSLN metastases. In multivariate analysis just the TTL was predictive for positive NSLN (OR 2.67; 95% CI 1.06-6.70; P = 0.036). The ROC curve for the model using TTL alone was obtained and an AUC of 0.805 (95% CI 0.69-0.92) was achieved. For TTL >1.9 × 105 copies/μL we got 73.3% sensitivity, 74.4% specificity and 88.9% negative predictive value to predict NSLN metastases. CONCLUSION: When using OSNA technique to evaluate SLN, NSLN metastases can be predicted intraoperatively. This prediction tool could help in decision for axillary lymph node dissection.
BACKGROUND: This study aimed to determine the relationship between CK19 mRNA copy number in sentinel lymph nodes (SLN) assessed by one-step nucleic acid amplification (OSNA) technique, and non-sentinel lymph nodes (NSLN) metastization in invasive breast cancer. A model using total tumor load (TTL) obtained by OSNA technique was also constructed to evaluate its predictability. METHODS: We conducted an observational retrospective study including 598 patients with clinically T1-T3 and node negative invasive breast cancer. Of the 88 patients with positive SLN, 58 patients fulfill the inclusion criteria. RESULTS: In the analyzed group 25.86% had at least one positive NSLN in axillary lymph node dissection. Univariate analysis showed that tumor size, TTL and number of SLN macrometastases were predictive factors for NSLN metastases. In multivariate analysis just the TTL was predictive for positive NSLN (OR 2.67; 95% CI 1.06-6.70; P = 0.036). The ROC curve for the model using TTL alone was obtained and an AUC of 0.805 (95% CI 0.69-0.92) was achieved. For TTL >1.9 × 105 copies/μL we got 73.3% sensitivity, 74.4% specificity and 88.9% negative predictive value to predict NSLN metastases. CONCLUSION: When using OSNA technique to evaluate SLN, NSLN metastases can be predicted intraoperatively. This prediction tool could help in decision for axillary lymph node dissection.