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

Autor: Haibo Zhang, Yi-hong Liu, Xue-Song Chang, Hao-Chuan Ma, Yan-juan Zhu, Rui Zhou, Ya-Dong Chen, Zhiyong Xu
Rok vydání: 2021
Předmět:
Zdroj: International Journal of General Medicine
ISSN: 1178-7074
Popis: 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 merged to establish nomograms. In the training and validation cohorts, calibration curves displayed the nomogram predictions are in a good agreement with the actual survival. The C-Index of the training and validation cohorts were both higher than 0.8, and the DCA results showed that the nomogram has clinical validity and utility.Conclusion: The proposed nomogram resulted in accurate CSS prognostic prediction for patients with LCNEC.Keywords: pulmonary large-cell neuroendocrine carcinoma, prognosis, nomogram, SEER database, cancer-specific survival
Databáze: OpenAIRE