Abstract P2-01-33: Non-sentinel lymph nodes involvement in early breast cancer patients: Performance of two predictive nomograms integrating the analysis of sentinel nodes by one step nucleic acid amplification in a cohort of 299 patients
Authors: V Bordes, L Campion, P Jezequel, A Lefrancois, F Boiffard, V Brillaud-Meflah, F Dravet, I Jaffre, J-M Classe
Journal: Cancer Research (2017)

Abstract Backgrounds: Sentinel lymph node (SLN) biopsy is a highly accurate predictor of axillary status and has become the surgical axillary standard in breast cancer patients. About 50–70 % of patients with involved SLN have no additional non sentinel node (NSN) involved, suggesting that it be possible to avoid ALND in selected patients. Many tools have been developed to help surgeons in NSLN evaluation but they all need pathological data from tumor and SLN and can't be used during surgery. Developed for intraoperative detection of SLN macro or micrometastasis involvement, the semi-automated molecular one step nucleic acid amplification (OSNA), as accurate as pathology, is available. Two simple nomograms have been developed to predict NSN involvement based on the number of CK19 mRNA copy determined by OSNA: · Nomogram developed by Peg V (Eur J Surg Oncol 2013): based on total tumoral load (TTL). TTL is defined as the addition of CK19 mRNA copies of each positive SLN (copies/μL). A TTL≥1.2 × 10(5) copies/ml (specificity=85.3%, negative predictive value (NPV) = 80%) can predict NSN involvement. · Nomogram developed by Di Filippo F (Journal of Experimental &amp; Clinical Cancer Research 2015): based on the number of CK19 mRNA copies and ultrasound tumor size. These two variables are categorized using quartiles with a score for each and the addition of both corresponds to a probability of NSN involvement (sensitivity = 98.1%, NPV = 92.5 %). Patients and Methods: this is a retrospective study of 299 patients. Each patient had SLN involvement (macro or micrometastasis) and underwent a complementary ALND. The main objective was to evaluate the performance of each nomogram using a discrimination ability model, assessed by ROC analysis. Predictive accuracy was measured by the area under ROC curves (AUC) reported with its 95 % confidence interval. The second objective was to compare the two nomograms using Hanley &amp; McNeil method, to test the statistical significance of the difference between the AUC. Analysis was performed using stata 13.1 SE. Results: The mean age was 59, 1 year. Most patients were treated for an infiltrating ductal carcinoma (80.3%, 240/299). The mean ultrasound tumor size was 13 mm and the mean pathological tumor size was 15 mm. The median number of examined SLN was 2 with a macro-metastasis in 67, 6%, 202/299). 70 patients had involved nodes in ALND (23%). The discrimination of N Peg, quantified with AUC was 0.685 (p&amp;lt;0, 00001). The discrimination of N Di Filippo, quantified with AUC was 0.72 (p&amp;lt;0, 00001). Hanley &amp; McNeil method shows that Di Filippo nomogram is significantly superior to Peg nomogram (p=0,048). Conclusion: The current study shows that these two nomograms are reliable and can be used to predict NSLN involvement. The combination of molecular data and ultrasound tumor size seems to be more efficient than molecular data alone. These results are similar to results of nomogram studies based on pathological analysis but only these nomograms integrating molecular data can be used during the surgery. Citation Format: Bordes V, Campion L, Jezequel P, Lefrancois A, Boiffard F, Brillaud-Meflah V, Dravet F, Jaffre I, Classe J-M. Non-sentinel lymph nodes involvement in early breast cancer patients: Performance of two predictive nomograms integrating the analysis of sentinel nodes by one step nucleic acid amplification in a cohort of 299 patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-01-33.