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. K E Y W O R D S cancer-specific survival, nomograms, overall survival, primary malignant cardiac tumors, risk classification systems
BackgroundCardiovascular death (CVD) in breast cancer patients without chemotherapy (CT) or (and) radiotherapy (RT) has not been studied yet. This study evaluates the correlation between breast cancer and CVD risk independent of chemotherapy or (and) radiotherapy.MethodsData of female breast cancer patients without receiving CT or RT were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database (2004–2015). Data were divided into two cohorts: tumor resection cohort and no resection cohort. The CVD risk in patients was expressed as standardized mortality ratios (SMRs). A 1:1 propensity score matching (PSM) was applied to balance inter-group bias, and competing risk regressions were utilized to evaluate the impact of tumor resection on CVD.ResultsThe CVD risk was significantly higher (SMR = 2.196, 95% CI: 2.148–2.245, P<0.001) in breast cancer patients who did not receive CT or RT compared to the general population. Breast cancer patients without tumor resection showed higher CVD risk than patients who underwent tumour resection (tumor resection SMR = 2.031, 95% CI: 1.983–2.079, P<0.001; no resection SMR = 5.425, 95% CI: 5.087–5.781, P<0.001). After PSM, the CVD risk among patients without tumor resection indicated an increase of 1.165-fold compared to patients with tumor resection (HR=1.165, 95% CI: 1.039–1.306, P=0.009).ConclusionsFemale breast cancer patients are at higher risk of CVD despite unexposure to cardio-toxic CT or RT. However, female breast cancer patients subjected to tumor resection have decreased CVD risk. These results indicated that monitoring female breast cancer patients not receiving RT or CT might serve as a preventative measure against CVD.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.