Abstract
Background: In 2015, large cell neuroendocrine carcinoma (LCNEC) was removed from the large cell carcinoma group and classified with small cell lung carcinoma (SCLC) constituting two members of the high-grade neuroendocrine tumors (NETs) of the lung. However, the difference between high-grade LCNEC and SCLC in terms of clinicopathological characteristics and prognosis has not been fully understood owing to the rarity of LCNEC. Patients and methods: Patients with high-grade LCNEC and SCLC at initial diagnosis between 2001 and 2014 were identified using the Surveillance, Epidemiology, and End Results (SEER) program database. Clinicopathological characteristics between high-grade LCNEC and SCLC were compared using the Pearson's chi-squared test or Fisher's exact test. Differences in overall survival (OS) and cancer-specific survival (CSS) were compared using the log-rank test, Cox models and propensity score matching (PSM) analysis. Results: A total of 1223 patients with high-grade LCNEC and 18182 patients with high-grade SCLC were enrolled. To the best of our knowledge, this study involved the largest number of high-grade LCNEC patients to date, with respect to a comparison between high-grade LCNEC and high-grade SCLC patients. There were significant differences in age, sex, race, laterality, SEER stage, nodal status, surgery, radiation and chemotherapy, but not marital status, between high-grade LCNEC and SCLC patients. High-grade LCNEC patients had a better OS and CSS than high-grade SCLC patients. Subgroup analysis also confirmed the better prognosis of the high-grade LCNEC patients in the regional stage, distant stage and surgery subgroups. However, no significant difference in prognosis was observed between the two non-surgery subgroups, which was confirmed using PSM analysis. Furthermore, high-grade LCNEC patients showed different metastatic patterns to high-grade SCLC patients. Conclusion: These results suggested that high-grade LCNEC and high-grade SCLC were different histological types, and that a detailed classification for high-grade NETs of the lung was needed.