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ARTICLE
Year : 2016  |  Volume : 5  |  Issue : 5  |  Page : 237

Using competing risks model and competing events in outcome of pulmonary tuberculosis patients


1 Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
2 Mycobacteriology Research Center (MRC), National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences; Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
3 Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Correspondence Address:
Anoshirvan Kazemnejad
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran
Iran
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Source of Support: None, Conflict of Interest: None


DOI: 10.1016/j.ijmyco.2016.09.015

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Introduction: Although tuberculosis (TB) is curable, the rate of failure and mortality is high in comparison to other infectious diseases worldwide. It has been shown that majority of TB patients leave treatment before completing the therapeutic regimen. The aftermath of incomplete regimens might result in drug resistant-TB bacilli (DR-TB), relapses, and death. For this reason, proper knowledge about the disease and associated risk factor is crucial to decreasing TB cases among the general population. In the present study, we aimed to investigate the associated factors and competing events among pulmonary tuberculosis patients. Materials and methods: Based on a cohort study, associated risk factors and competing events from 2366 confirmed TB patients that referred to the National Center for Tuberculosis for diagnosis and treatment (2005–2015) were collected and analyzed. Results: Our results showed that gender, age, marital status, TB contact, drug adverse effect, and HIV positive, imprisoned, significantly affect the relapse cases, drug resistance, and mortality rate (P-value <0.05). Conclusions: Use of competing risks model with competing events can provide a better way to understand the associated risk factors co-related with outcome of the pulmonary TB process, especially among DR-TB patients.


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