Nomogram to predict non-sentinel lymph node status using total tumor load determined by one-step nucleic acid amplification: first report from Thailand

• Main Authors: Doonyapat Sa-nguanraksa, Eng O-charoenrat, Anchalee Kulprom, Norasate Samarnthai, Visnu Lohsiriwat, Kampanart Nimpoonsri, Pornchai O-charoenrat
• Other Authors: UCL
• Format: Article
• Published: 2020
• Subjects: Medicine
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/51565
• Institution: Mahidol University

© 2019, The Japanese Breast Cancer Society. Background: Axillary staging is a significant prognostic factor often used to determine the treatment course for breast cancer. One-step nucleic acid amplification (OSNA) is now the most accepted method for intra-operative assessment of sentinel lymph nodes (SLN) as it can semi-quantitatively determine the tumor burden in these SLN. Axillary lymph node dissection (ALND) may be omitted in patients with limited disease in the axilla. The objective was to create nomogram for prediction of non-sentinel lymph node (NSLN) status using OSNA to avoid unnecessary ALND. Patients and methods: Patients with invasive breast cancer T1–T3 and clinically negative axillary lymph nodes underwent SLN biopsy assessed by OSNA. The patients with positive SLN underwent ALND. Correlations between total tumor load (TTL), clinicopathological parameters, and NSLN status were analyzed by Chi square statistic and logistic regression. Model discrimination was evaluated using receiver-operating characteristic (ROC) analysis. Results: The total number of patients who underwent SLN biopsies was 278. There were 89 patients with positive SLN. NSLNs were positive in 40 patients. Larger tumor size, presence of lymphovascular invasion (LVI) and higher log TTL were independent factors that predicted positive NSLN. TTL can discriminate NSLN status with area under the ROC curve of 0.789 (95% CI 0.686–0.892). Two nomograms using different parameters obtained pre- and post-operatively can predict NSLN involvement with better area under the ROC curve (0.801, 95% CI 0.702–0.900 and 0.849, 95% CI 0.766–0.932, respectively). Conclusions: Nomograms using results obtained via OSNA can predict NSLN status, as well as aid in deciding to omit the use of ALND.