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Predictive factors of postoperative survival among patients with pulmonary neuroendocrine tumor. | LitMetric

AI Article Synopsis

Article Abstract

Background: Pulmonary neuroendocrine tumor (NET) occurs with 20% of all lung cancers, and there are a limited number of literatures about the molecular aberrations, treatment and prognosis; especially in resected cases, as the operation indication for large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC) is rare due to their aggressive behaviors. We investigated the relationship between postoperative survival and molecular expression patterns of pulmonary NET to establish a more effective treatment strategy.

Methods: In the present study, the curative surgical resection of pulmonary NET was reviewed retrospectively. A total of 105 patients with pulmonary NET, who underwent complete resection between 1978 and 2016, were subjected to analysis with respect to histological characterization and clinical behaviors of pulmonary NET using immunohistochemistry (IHC) of neuroendocrine markers and programmed cell death-ligand 1 (PD-L1).

Results: The pathological types included 67 SCLC, 18 LCNEC, 14 typical carcinoids (TCs) and 6 atypical carcinoids (ACs). The ACs had significantly worse prognosis than TCs. PD-L1 expression ratio in SCLC/LCNEC/TC/AC was 26.1%/50%/15.4%/20%, respectively. However, it was not significantly correlated with each prognosis. Therefore, the SCLC patients were analyzed, the overall 5-year survival of SCLC patients was found to be 47.3%. In the univariate analysis of the molecular expression of SCLC, neuroendocrine markers such as chromogranin-A (CGA) and synaptophysin (SYN) showed poor prognosis, albeit without significant differences.

Conclusions: The neuroendocrine markers such as CGA and SYN might assist the prediction of prognosis and probably influence the decision for adjuvant chemotherapy or follow-up intervals after surgery in SCLC patients; however additional studies are essential.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6344740PMC
http://dx.doi.org/10.21037/jtd.2018.11.115DOI Listing

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