Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran,
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Clinical Tuberculosis and Epidemiology, Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran,
Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Tuberculosis (TB) is a chronic bacterial disease, which despite the presence of effective drug strategies, still remains a serious health problem worldwide. Estimation of survival rate is an appropriate indicator for prognosis in patients with pulmonary TB. Therefore, this research was designed with the aim of accurate estimation of the survival of patients by taking both the death event and relapse into consideration. Materials and Methods: Based on a retrospective cohort study, information of 2,299 patients with pulmonary TB that had been referred to and treated in Masih Daneshvari Hospital from 2005 to 2015 was reviewed. To estimate the survival of patients with pulmonary TB, the competing risks model, which considered death and relapse as competing events, was used. In addition, the effect of factors affecting the cumulative incidence function (CIF) of death event and relapse was also examined. Results: The effect of risk factors on the CIF of death events and relapse showed that patients’ age, marital status, contact with TB patients, adverse effect of drugs, imprisonment and HIV positivity were factors that affected the CIF of death. Meanwhile, sex, marital status, imprisonment and HIV positivity were factors affecting the CIF of relapse (P <0.05). Considering death and relapse as competing events, survival estimation in pulmonary TB patients showed that survival in this group of patients in the first, third, fifth and tenth year after treatment was 39%, 14%, 7% and 0%, respectively. Conclusion: The use of competing risks model in survival analysis of patients with pulmonary TB with consideration of competing events, enables more accurate estimation of survival.