e21064 Background: Chemotherapy is very common for resected Non-Small-Cell Lung Cancer (NSCLC) patients. However, models for predicting the survival outcomes of resected NSCLC patients with chemotherapy are scarce. The aim of this study was to develop a clinical nomogram for predicting overall survival in these patients. Methods: A total of 16661 resected NSCLC with chemotherapy were cases extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We identified and integrated the prognostic factors to build a nomogram.The model was subjected to bootstrap internal validation with the SEER database and external validations with 1108 patients from China. The predictive accuracy and discriminative ability were illustrated by calibration, concordance index (C-index) and risk group stratification. Results: On multivariate analysis independent factors for OS were age, sex, examined lymph node count, extent of surgery, N stage, T stage and grade which were then integrated into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year OS showed excellent agreement between nomogram prediction and actual observation. The C-index of the nomogram was higher than that of AJCC 8th edition system for predicting OS (training cohort, 0.61 vs. 0.58; P < 0.01; validation cohort, 0.66 vs. 0.63, P = 0.56). The stratification into different risk groups allowed significant distinction between survival curves. Conclusions: We established a nomogram that can provide individual prediction of OS for resected NSCLC patients with chemotherapy. This practical prognostic model may help clinicians for treatment planning and to guide future studies.
A nomogram model to predict death rate among non-small cell lung cancer (NSCLC) patients with surgery in surveillance, epidemiology, and end results (SEER) database
