Effect of Chemotherapy in Stage II–IV Large-Cell Lung Carcinoma and Construction of Its Predictive Nomograms: A SEER Analysis

Abstract

Objectives: Large-cell lung carcinoma (LCLC) is generally poorly differentiated with a poor prognosis. This study aimed to explore the impact of chemotherapy on the prognosis of patients with stage II–IV LCLC and to construct nomograms to predict overall survival (OS) and cancer-specific survival (CSS). Methods: Propensity score matching analysis was used to balance the effects of baseline characteristics. The Kaplan-Meier method was used to analyze the prognostic impact of chemotherapy on LCLC patients. Cox regression analysis was used to identify prognostic risk factors, and then nomograms were constructed and validated. Results: Overall, we identified 2,532 patients with LCLC from the Surveillance, Epidemiology, and End Results (SEER) database. The chemotherapy group showed better OS and CSS compared to the non-/unknown chemotherapy group for stage II–IV LCLC patients (p < 0.05). Two nomograms were plotted based on the results of Cox regression analysis. The areas under the curves (AUCs) of 1-, 3-, and 5-year OS were 0.786, 0.824, and 0.837, and the AUCs of CSS were 0.785, 0.821, and 0.836, respectively. The calibration curves showed excellent agreement between the prediction and the actual observation, and the decision curve analysis demonstrated good clinical utility. Conclusions: Chemotherapy could improve the prognosis among stage II–IV LCLC patients. In addition, the nomograms showed good predictive ability, which could be useful in making clinical decisions.