The prognostic risk stratification model for metastatic small-cell lung cancer: An analysis of the SEER database.

Abstract

Distant metastases of small-cell lung cancer (DM-SCLC) is an important factor in the selection of treatment strategies. In this study, we established a nomogram to predict DM-SCLC and determine the benefit of radiotherapy (RT) for DM-SCLC. We analyzed DM-SCLC prognosis based on surveillance, epidemiology, and end result database (SEER) data. A comprehensive and practical nomogram that predicts the overall survival (OS) of DM-SCLC was constructed and the results were compared with the 7th edition of the American Joint Committee on Cancer (AJCC) TNM stage system. A concordance index (C-index) and receiver operating characteristic plot were generated to evaluate the nomogram discrimination. The calibration was evaluated with a calibration plot, and its effectiveness was evaluated by a decision curve analysis (DCA). A score was assigned to each variable, and a total score was established for the risk stratification model. A total of 13,403 DM-SCLC patients were included. Eight characteristic variables were identified as independent prognostic variables. The C-index of the validation and training cohorts was 0.716 and 0.734, respectively. The area under the receiver operating characteristic curve (AUC) values of the nomogram used to predict 1-, 2-, and 3-year OS were 0.751, 0.744, and 0.786 in the validation cohorts (0.761, 0.777, 0.787 in the training cohorts), respectively. The calibration curve of 1-, 2-, 3-year survival rates showed that the prediction of the nomogram was in good agreement with the actual observation. The nomogram exhibited higher clinical utility after evaluation with the 1-, 2-, 3-year DCA compared with the AJCC stage system. A predictive nomogram and risk stratification model have been constructed to evaluate the prognosis of DM-SCLC effectively and accurately. This nomogram may provide a reference for prognosis stratification and treatment decisions.