Prognostic nomogram for predicting long-term cancer-specific survival in patients with lung carcinoid tumors

BMC Cancer

Feng Zhao¹  Yiwu Zhou²  Qingbing Han³  Yanqi He³  Shuang Zhao³ 

[1] Department of Cancer Center, Sichuan Academy of Medical Sciences&Sichuan Provincial People’s Hospital, Chengdu, China;Department of Emergency Medicine, Emergency Medical Laboratory, West China Hospital, Sichuan University, Chengdu, Sichuan, China;Disaster Medical Center, Sichuan University, Chengdu, Sichuan, China;Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China;

关键词: Lung carcinoid tumors;    Nomogram;    Cancer-specific survival;   

DOI  :  10.1186/s12885-021-07832-6

来源: Springer

【 摘 要 】

BackgroundLung carcinoid is a rare malignant tumor with poor survival. The current study established a nomogram model for predicting cancer-specific survival (CSS) in patients with lung carcinoid tumors.MethodsA total of 1956 patients diagnosed with primary lung carcinoid tumors were extracted from the Surveillance, Epidemiology, and End Results database. The specific predictors of CSS for lung carcinoid tumors were identified and integrated to build a nomogram. Validation of the nomogram was conducted using parameters concordance index (C-index), calibration plots, decision curve analyses (DCAs), and the receiver operating characteristic (ROC) curve.ResultsAge at diagnosis, grade, histological type, N stage, M stage, surgery of the primary site, radiation of the primary site, and tumor size were independent prognostic factors of CSS. High discriminative accuracy of the nomogram model was shown in the training cohort (C-index = 0.873), which was also testified in the internal validation cohort (C-index = 0.861). In both cohorts, the calibration plots showed good concordance between the predicted and observed CSS at 3, 5, and 10 years. The DCA showed great potential for clinical application. The ROC curve showed superior survival predictive ability of the nomogram model (area under the curve = 0.868).ConclusionsWe developed a practical nomogram that provided independent predictions of CSS for patients with lung carcinoid tumors. This nomogram may have the potential to assist clinicians in prognostic evaluations or developing individualized therapies for patients with this neoplasm.

【 授权许可】

CC BY