A nomogram prognostic model for clinical stage IA NSCLC: based on SEER databases

Abstract Background: The aim of this study was to establish and validate a nomogram model for accurate prediction of patients’ survival with T1aN0M0 none small cell lung cancer (NSCLC).Methods: The patients, diagnosed with the stage IA NSCLC from 2004-2015, were identified from the Surveillance, Epidemiology and End Results (SEER) database. The variables with a P value < 0.05 in a multivariate Cox regression were selected to establish the nomogram. The discriminative ability of the model was evaluated by the concordance index(C-index). The proximity of the nomogram prediction to the actual risk was depicted by a calibration plot. The clinical usefulness was estimated by the decision curve analysis (DCA). Survival curves were made with Kaplan-Meier method and compared by Log-Rank test. Result: Eight variables, including treatment, age, sex, race, marriage, tumor size, histology and grade were selected to develop the nomogram model by univariate and multivariate cox regression. The C-index was 0.704 (95%CI, 0.694 to 0.714) in the training set and 0.713 (95%CI, 0.697 to 0.728) in the test set, which performed significantly better than 8th edition AJCC TNM stage system (0.550, 95% CI, 0.408-0.683, P<0.001). The calibration curve showed that the prediction ability of 3-years and 5-years survival rate demonstrated a high degree of agreement between the nomogram model and the actual observation. The DCA curves also proved that the nomogram-assisted decisions could improve patient outcomes. Conclusions: We established and validated a prognostic nomogram to predict 3-years and 5-years overall survival in stage IA NSCLC.