Treatment outcome and prognostic analysis of advanced large cell neuroendocrine carcinoma of the lung

Abstract

The optimal systemic treatment of advanced large cell neuroendocrine carcinoma (LCNEC) is still controversial. We intend to explore advanced LCNEC through SEER database, construct nomogram model of advanced LCNEC, and understand the effect of different treatment regimens on LCNEC. We collected 909 patients, divided them into a training set validation set, constructed nomograms using Cox proportional hazards regression models, and evaluated nomogram discrimination and calibration by C-index and calibration curves. Kaplan–Meier will also be used to compare OS in different groups of patients and to explore the impact of different treatment regimens on advanced LCNEC. On the nomogram plotted, the nomogram predicted AUC values over time were always greater than 0.7, the C-index was 0.681 (95% CI 0.656–0.706) and 0.663 (95% CI 0.628–0.698) in the training and validation sets, respectively, and patients were divided into two groups according to risk, and a significant difference in OS was observed between the high-risk and low-risk groups in the training and validation cohorts. Different treatment analyses showed that chemotherapy is still the best treatment for advanced LCNEC. This nomogram provides a convenient and reliable tool for individual assessment and clinical decision-making of patients with advanced LCNEC.