Tianwang Guan1, Yanfang Li1, Zicong Qiu2, Yichi Zhang2, Wenrui Lin2, Yanxian Lai1, Kenie Wang2, Yan Shen1, Liping Du1, Cheng Liu1,3. 1. Department of Cardiology, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China. 2. Department of Clinical Medicine, Clinical Medical College, Guangzhou Medical University, Guangzhou, China. 3. Department of Cardiology, School of Medicine, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.
Abstract
BACKGROUND: Primary malignant cardiac tumors (PMCTs) are fatal, but up to now, there is still a lack of survival prediction model for prognosis evaluation. We developed nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for PMCTs by the Surveillance, Epidemiology, and End Result (SEER) database. METHODS: A total of 506 PMCTs participants were identified in the SEER database from 1973 to 2014 and were randomly assigned into the training cohort (N = 354) and the validation cohort (N = 152). The prognostic factors for PMCTs were identified by Kaplan-Meier and multivariate Cox analysis and further incorporated to build OS and CSS nomograms. The nomograms were internally and externally validated via concordance indexes (C-index) and calibration curves. RESULTS: The independent prognostic factors for OS and CSS in PMCTs were associated with age at diagnosis, histopathology, tumor stage, cancer-directed surgery, and chemotherapy (all P < .05). In the internal validation, the C-index values were 0.71 (95% confidence interval [CI]: 0.68-0.75) for OS nomogram, and 0.70 (95% CI: 0.67-0.74) for CSS nomogram. In the external validation, the C-index values were 0.71 (95% CI: 0.66-0.77) for OS nomogram, and 0.71 (95% CI: 0.65-0.77) for CSS nomogram. The calibration curves of internal and external validation showed consistency between the nomograms and the actual observation. The risk stratification of PMCTs was significant distinction (P < .05). CONCLUSION: We developed and validated credible nomograms to predict OS and CSS in PMCTs. These nomograms can be offered to clinicians to more precisely estimate the survival and identify risk stratification of PMCTs.
BACKGROUND:Primary malignant cardiac tumors (PMCTs) are fatal, but up to now, there is still a lack of survival prediction model for prognosis evaluation. We developed nomograms to predict overall survival (OS) and cancer-specific survival (CSS) for PMCTs by the Surveillance, Epidemiology, and End Result (SEER) database. METHODS: A total of 506 PMCTsparticipants were identified in the SEER database from 1973 to 2014 and were randomly assigned into the training cohort (N = 354) and the validation cohort (N = 152). The prognostic factors for PMCTs were identified by Kaplan-Meier and multivariate Cox analysis and further incorporated to build OS and CSS nomograms. The nomograms were internally and externally validated via concordance indexes (C-index) and calibration curves. RESULTS: The independent prognostic factors for OS and CSS in PMCTs were associated with age at diagnosis, histopathology, tumor stage, cancer-directed surgery, and chemotherapy (all P < .05). In the internal validation, the C-index values were 0.71 (95% confidence interval [CI]: 0.68-0.75) for OS nomogram, and 0.70 (95% CI: 0.67-0.74) for CSS nomogram. In the external validation, the C-index values were 0.71 (95% CI: 0.66-0.77) for OS nomogram, and 0.71 (95% CI: 0.65-0.77) for CSS nomogram. The calibration curves of internal and external validation showed consistency between the nomograms and the actual observation. The risk stratification of PMCTs was significant distinction (P < .05). CONCLUSION: We developed and validated credible nomograms to predict OS and CSS in PMCTs. These nomograms can be offered to clinicians to more precisely estimate the survival and identify risk stratification of PMCTs.