A nomogram from the SEER database for predicting the prognosis of patients with non-small cell lung cancer

Abstract Objective The purpose of this study was to establish and validate a nomogram to predict the prognosis in patients with non-small cell lung cancer (NSCLC) from multiple perspectives. Results A total of 98,640 eligible patients were randomly divided into a training set (n = 69,048) and a validation set (n = 29,592). The baseline characteristics of the two sets were similar. We used clinical data from patients in the training set for univariate and multivariate Cox regression analyses. Twelve independent risk factors were incorporated for constructed a prognostic nomogram. And the nomogram with a concordance index of 0.777 (95 % CI, 0.775 to 0.779) for overall survival. The calibration curve results showed that the actual survival rate was consistent with the predicted survival rate. The area under curve of the receiver operating characteristic curves demonstrated that the nomogram has a high prediction of the overall survival rate in patients with NSCLC. Conclusion We have developed a nomogram with high prediction accuracy and discrimination ability, which can help clinicians making personalized survival predictions for NSCLC patients.