A Clinical Nomogram for Predicting Cancer-Specific Survival in Pulmonary Large-Cell Neuroendocrine Carcinoma Patients: A Population-Based Study

Haochuan Ma,1,* Zhiyong Xu,1,* Rui Zhou,1,* Yihong Liu,2 Yanjuan Zhu,1– 4 Xuesong Chang,2 Yadong Chen,2 Haibo Zhang1– 5 1The Second Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China; 2Department of Oncology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, People’s Republic of China; 3Guangdong-Hong Kong-Macau Joint Laboratory on Chinese Medicine and Immune Disease Research, Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China; 4Guangdong Provincial Key Laboratory of Clinical Research on Traditional Chinese Medicine Syndrome, Guangzhou, People’s Republic of China; 5State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Haibo ZhangDepartment of Oncology, Guangdong Provincial Hospital of Traditional Chinese Medicine, No. 111, Dade Road, Guangzhou, Guangdong, 510120, People’s Republic of ChinaTel +86-20-81887233Fax +86-20-81874903Email haibozh@gzucm.edu.cnPurpose: This study was designed to construct and validate a nomogram that was available for predicting cancer-specific survival (CSS) in patients with pulmonary large-cell neuroendocrine carcinoma (LCNEC).Patients and Methods: Using the US Surveillance, Epidemiology, and End Results (SEER) database, we identified patients pathologically diagnosed as LCNEC from 1975 to 2016. Univariate and multivariate Cox regression was conducted to assess prognostic factors of CSS. A novel nomogram model was constructed and validated by the concordance index (C-index), calibration curves and decision curve analysis (DCA).Results: A total of 624 LCNEC patients were enrolled. Five prognostic factors for CSS were identified and