22 January 2020 : Clinical Research
A Competing Risk Analysis Study of Prognosis in Patients with Esophageal Carcinoma 2006–2015 Using Data from the Surveillance, Epidemiology, and End Results (SEER) Database
Zhaohua Yu12CDE, Jin Yang34CD, Lei Gao12D, Qiao Huang5F, Hao Zi12F, Xiaodong Li12AG*DOI: 10.12659/MSM.918686
Med Sci Monit 2020; 26:e918686
Abstract
BACKGROUND: Competing risk analysis determines the probability of survival and considers competing events. This retrospective study aimed to undertake a competing risk analysis of prognosis in patients with esophageal carcinoma between 2006–2015 using data from the Surveillance, Epidemiology, and End Results (SEER) database.
MATERIAL AND METHODS: Clinicopathological, demographic, and survival data were analyzed for patients with esophageal carcinoma registered in the SEER database between 2006–2015. The competing risk model calculated the cumulative incidence function (CIF) of events of interest and prognosis. The Cox proportional-hazards model and the cause-specific hazard function (CS) were used to generalize the hazard function for competing risks. The Fine-Gray model was used for multivariate analysis. More accurate prognostic factors were analyzed by comparing the hazard ratio (HR) values between groups.
RESULTS: There were 14,695 patients identified with esophageal carcinoma, 9,621 died from esophageal carcinoma, and 1,251 patients died from other causes. The cumulative incidence of events of interest was significant for age at diagnosis, race, primary tumor site, grade, stage, and treatment with surgery, radiotherapy, and chemotherapy (P<0.001). Multivariate analysis showed that age at diagnosis, primary tumor site, grade, stage, and treatment with surgery, radiotherapy, and chemotherapy statuses were independent prognostic factors (P<0.05). The Fine-Gray and the CS model showed that grade, stage, and treatments with surgery, radiotherapy, and chemotherapy were significant independent prognostic factors (P<0.05).
CONCLUSIONS: A competing risk model used data from the SEER database to obtain a more accurate estimate of the CIF of esophageal carcinoma-specific mortality and prognostic factors.
Keywords: Esophageal Neoplasms, Proportional Hazards Models, SEER Program, Cause of Death, Databases, Factual, Incidence, Multivariate Analysis, nomograms, Probability, Risk Assessment, Risk Factors
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