Significance of metastatic lymph nodes ratio in overall survival for patients with resected Non–Small-Cell Lung Cancer

Abstract

Abstract Background: TNM stage is widely applied to classify lung cancer and the foundation of clinical decisions. However, increasing studies have pointed out that this staging system is not precise enough especially for the N status. In this study, we aim to build a convenient survival prediction model that incorporated the current items of lymph node status. Methods: We collected data of resectable NSCLC(IA-IIIB) patients from Surveillance, Epidemiology, and End Results (SEER) database (2006-2015). X-tile program was applied to calculate the optimal threshold of metastatic lymph nodes ratio (MLNR). Then, independent prognostic factors were determined by multivariable cox regression analysis and enrolled to build a nomogram model. The calibration curve as well as the concordance index(C-index ) were selected to evaluate the nomogram. Finally, patients were grouped based on their specified risk points and divided into three risk levels. The prognostic value of MLNR and examined lymph nodes number (ELNs) were presented in subgroups. Results: 40853 NSCLC patients after surgery were finally enrolled and analyzed. Age, metastatic lymph nodes ratio, histology type, adjuvant treatment, and AJCC 8th T stage were deemed as independent prognostic parameters after multivariable cox regression analysis. Nomogram was built using those variables and its efficiency in predicting patients’ survival was better than the conventional AJCC stage system after evaluation. Our new model has a significant higher concordance index(C-index) (training set,0.683 v 0.641, respectively; P<0.01; testing set, 0.676 v 0.638, respectively; p<0.05). Similarly, the calibration curve shows the nomogram was in better accordance with the actual observation in both cohorts. And then, after risk stratification, we found MLNR is more reliable than ELNs in predicting overall survival(OS). Conclusions: We developed a nomogram model for NSCLC patients after surgery. This novel and useful tool outperforms the widely used TNM staging system and could benefits clinicians in treatment options and cancer control.