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Paper Information

Journal:   MEDICAL JOURNAL OF THE ISLAMIC REPUBLIC OF IRAN (MJIRI)   2017 , Volume 31 , Number 1; Page(s) 0 To 0.

Survival analysis of thalassemia major patients using Cox, Gompertz proportional hazard and Weibull accelerated failure time models



* Department of Biostatistics, Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
Background: Thalassemia major (TM) is a severe disease and the most common anemia worldwide. The survival time of the disease and its risk factors are of importance for physicians. The present study was conducted to apply the semi-parametric Cox PH model and use parametric proportional hazards (PH) and accelerated failure time (AFT) models to identify the risk factors related to survival of TM patients. Methods: The data of this historical cohort study (296 patients with TM) were collected during 1994 and 2013 in Zafar Clinic in Tehran. Gompertz PH and Weibull AFT models were used for survival analysis (SA) of these patients. Data analysis was performed using R3. 2. 2 software. Results: 153 (51. 7%) of patients were female; the mean (± SD) age of the patients was 29. 11 (± 0. 47) years. One-year survival rate for males and females was 0. 963± 0. 007 and 0. 973± 0. 013, respectively; and 3-year survival rate for males and females was 0. 711± 0. 057 and 0. 733± 0. 114, respectively. In the Gompertz model, birthplace and age at onset of the disease were significant factors (p= 0. 035, and p= 0. 005) in survival time. Also, in the Weibull model, birth place and age at onset of the disease were significant factors (p= 0. 013, and p= 0. 008) in survival time. The Akaike Information Criterion (AIC) for Weibull model was 158. 51, which was lower than other parametric models. Conclusion: According to the results, the Weibull AFT model was found to be a better model for identifying the risk factors related to survival of patients with TM disease. Informing parents, especially mothers and paying attention to blood screening for early diagnosis may increase the survival rate of patients.
Keyword(s): Survival analysis,Accelerated failure time model,Proportional hazards models,Thalassemia major
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