Construction and validation of a prognostic nomogram model for SCLC patients in Shandong Province, China

Abstract

Abstract Background: The prognosis of patients with small cell lung cancer (SCLC) is poor. We aim to figure out the survival rate of SCLC and construct a nomogram survival prediction for SCLC patients in Shandong. Methods: We collected the clinical data of 2219 SCLC patients in various tumor hospitals and general hospitals in fifteen cities in Shandong province from 2010-2014, and the data were randomly divided into a training set and a validation set according to 7:3. We used univariate and multivariate to determine the independent prognostic factors of SCLC, and developed a prognostic nomogram model based on these factors. The predictive discriminatory and accuracy performance of this model was evaluated by the area under the receiver operator characteristic (ROC) curve (AUC), and calibration curves. Results: The overall 5-year survival rate of Shandong SCLC patients was 14.27% with the median survival time being 15.77 months. Multivariate analysis showed that region, sex, age, year of diagnosis, TNM stage (assigned according to the AJCC 8th edition), and treatment type (surgery, chemotherapy, and radiotherapy) were independent prognostic factors and were included in the prognostic nomogram model. The AUC of the training set was 0.724, 0.710, and 0.704 for 1-year, 3-year, and 5-year; the AUC of the validation set was 0.678, 0.670, and 0.683 for 1-year, 3-year, and 5-year. The calibration curves of the prediction are consistent with the ideal curve. Conclusion: We construct a nomogram prognostic model to predict SCLC prognosis with certain discrimination which can provide both clinicians and patients with an effective tool for predicting outcomes and guiding treatment decisions.