OBJECTIVES: The survival rate of thalassemia patients has not been conclusively established, and the factors associated with survival remain unclear. This study aimed to determine the survival rate of thalassemia among patients in southern Iran and to identify the factors associated with mortality from thalassemia. METHODS: This retrospective cohort study was conducted based on a retrospective review of the medical records of 911 beta-thalassemia patients in 2014. Data analysis was conducted using the Kaplan-Meier method and Cox regression analysis. RESULTS: Overall, 212 patients (23.3%) died, and 26.8% had thalassemia intermedia. The 20-year, 40-year, and 60-year survival rates were 85%, 63%, and 54%, respectively. Both crude and adjusted analyses found that education, marital status, ferritin levels, and comorbidities were related to mortality. CONCLUSIONS: Sociodemographic and hematological factors were found to be significantly associated with the survival rate of thalassemia. Addressing these factors may help healthcare providers and physicians to provide the best possible care and to improve the survival rate.
beta-Thalassemia ; Cohort Studies ; Comorbidity ; Education ; Ferritins ; Health Personnel ; Humans ; Iran* ; Kaplan-Meier Estimate ; Marital Status ; Medical Records ; Mortality ; Retrospective Studies ; Statistics as Topic ; Survival Rate ; Thalassemia*

Objective To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Methods The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals’ distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). Results The study results indicated that SARIMA model (4,1,4)(0,1,0)