Validation of a Nomogram Predicting Non-Sentinel Lymph Node Metastases among Patients with Breast Cancer after Primary Systemic Therapy-a transSENTINA Substudy

Abstract

Background: Prediction of non-sentinel lymph node (SLN) status after primary systemic therapy (PST) may allow tailored axillary staging. The aim of this analysis was to compare established nomograms from i) the primary operative (n = 6) and ii) the neoadjuvant (n = 1) setting with an optimized nomogram to predict non-SLN status in patients after PST. Methods: 181 patients converting from cN1 prior to PST to ycN0 but found to have a histologically positive SLN in the SENTINA trial were analyzed. Established models were applied. An optimized model was compiled using univariate and subsequent multivariable logistic regression (backward selection, likelihood ratio test). Results: Area-under-The-curve (AUC) values from the primary operative models showed sufficient performance (0.82-0.71). For the neoadjuvant model, the AUC was found to be inferior to prior analyses (0.66) but within published confidence intervals. The SENTINA nomogram comprised the diameter of the largest lymph node (p = 0.006, odds ratio (OR) = 1.19), tumor size prior to PST (p = 0.085, OR = 1.31), and number of all positive SLN (p = 0.083, OR = 2.04). This model was validated using a separate cohort of arm C (n = 168, AUC 0.79, 95% confidence interval 0.74-0.85). Conclusion: We validated 7 models of prediction of non-SLN among patients showing axillary conversion through PST. Our own 'SENTINA nomogram' yielded AUC values comparable to previous nomograms.