Analysis on the Characteristics and Prognosis of Pulmonary Neuroendocrine Tumors

作者:Wu, Bai-Shou; Hu, Yi*; Sun, Jing; Wang, Jin-Liang; Wang, Peng; Dong, Wei-Wei; Tao, Hai-Tao; Gao, Wen-Juan
来源:Asian Pacific Journal of Cancer Prevention, 2014, 15(5): 2205-2210.
DOI:10.7314/APJCP.2014.15.5.2205

摘要

Objective: To retrospectively review the clinical characteristics and analyze the prognostic factors of Chinese patients with pulmonary neuroendocrine tumors. Materials and Methods: The clinical data of 176 patients with pulmonary neuroendocrine tumors in Chinese PLA General Hospital from Mar., 2000 to Oct., 2012 were retrospectively analyzed. The parameters were evaluated by univariate and multivariate analysis, including the gender, age, smoking history, family history, TNM staging, localization (central or peripheral), tumor size, nodal status, histological subtype and treatment (operation or non-operation). Results: There were 23 patients with typical carcinoids (TC) (13.1%), 41 with atypical carcinoids (AC) (23.3%), 10 with large cell neuroendocrine carcinoma (LCNEC) (5.7%) and 102 with small cell lung cancer (SCLC) (57.9%). The median follow-up time was 64.5 months for AC, 38 months for LCNEC and 27 months for SCLC. The typical carcinoid censored data was 18 (more than 50% of the patients), so the median follow-up time was not obtained, and actuarial 5-year survivals for TC, AC, LCNEC and SCLC were 75.1%, 51.7%, 26.7% and 38.8%, respectively. COX univariate analysis revealed that the age (P=0.001), histological subtype (P=0.005), nodal status (P=0.000), treatment (P=0.000) and TNM staging (P=0.000) were the prognostic factors of the patients with pulmonary neuroendocrine tumors, whereas its multivariate analysis showed that only the age(P=0.001), TNM staging (P=0.002) and treatment (P=0.000) were independent prognostic factors. Conclusions: Radical surgery remains the treatment of choice, and is the only curative option. The age, TNM staging and treatment are confirmed to be the independent prognostic factors in multivariable models for pulmonary neuroendocrine tumors.