Development and validation of a prognostic model of resectable small-cell lung cancer: a large population-based cohort study and external validation.

ABSTRACT

BACKGROUND: Survival outcomes of patients with resected SCLC differ widely. The aim of our study was to build a model for individualized risk assessment and accurate prediction of overall survival (OS) in resectable SCLC patients. METHODS: We collected 1052 patients with resected SCLC from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were selected by COX regression analyses, based on which a nomogram was constructed by R code. External validation were performed in 114 patients from Shandong Provincial Hospital. We conducted comparison between the new model and the AJCC staging system. Kaplan-Meier survival analyses were applied to test the application of the risk stratification system. RESULTS: Sex, age, T stage, N stage, LNR, surgery and chemotherapy were identified to be independent predictors of OS, according which a nomogram was built. Concordance index (C-index) of the training cohort were 0.721, 0.708, 0.726 for 1-, 3- and 5-year OS, respectively. And that in the validation cohort were 0.819, 0.656, 0.708, respectively. Calibration curves also showed great prediction accuracy. In comparison with 8th AJCC staging system, improved net benefits in decision curve analyses (DCA) and evaluated integrated discrimination improvement (IDI) were obtained. The risk stratification system can significantly distinguish the ones with different survival risk. We implemented the nomogram in a user-friendly webserver. CONCLUSIONS: We built a novel nomogram and risk stratification system integrating clinicopathological characteristics and surgical procedure for resectable SCLC. The model showed superior prediction ability for resectable SCLC.