Prognostic factors of patients with pulmonary large-cell neuroendocrine carcinoma after surgery: a competing risk analysis

Abstract

Background: Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis. Our aim was to determine the prognostic factors of patients with pulmonary LCNEC after surgery based on competing risk model. Methods: Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. For single outcome events, Kaplan-Meier method and Cox proportional risk model were used for analysis. Competing risk model was used in the analysis of multiple outcome events to adjust potential confounding factors. Competing risk model was used to calculate the cumulative incidence function of LCNEC-specific death. The Fine-Gray model was used for multivariate analysis to determine independent prognostic factors.Results: We finally screened 614 patients with pulmonary LCNEC who underwent surgery. The univariate analysis showed that T stage, N stage, M stage, regional nodes positive (RNP), and radiotherapy were significantly associated with the cumulative incidence of LCSD (P < 0.05). The Fine-Gray model showed that age, T stage, M stage, RNP, radiotherapy, and chemotherapy were independent prognostic factors for patients with pulmonary LCNEC after surgery (P < 0.05). Conclusion: Based on the competing risk model, we estimated a more accurate cumulative incidence of LCNEC-specific death and prognostic factors for patients with pulmonary LCNEC after surgery.