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Insights into tuberculosis: A survival analysis of time to recurrence in Portugal, between 2002 and 2009.

Soares, P, Duarte, R, Gomes, Gabriela ORCID:, Rocha, C and Lopes, J S (2020) 'Insights into tuberculosis: A survival analysis of time to recurrence in Portugal, between 2002 and 2009.'. Pulmonology, Vol 26, Issue 5, pp. 318-320.

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Recurrence of TB has been associated with poor adherence to treatment, smoking, alcoholism, unemployment, drug abuse, the severity of pulmonary cavitation, HIV infection and duration of treatment.1 However, the risk factors can vary considerably across countries and between studies. Since little is known about risk factors for recurrence in Portugal, we aimed to identify predictors of treatment recurrence in the country. Surveillance data on TB for the period of 2002–2009 was provided by SVIG-TB, a database from the Portuguese National Health System. For this analysis, only cases of confirmed TB disease were considered, and patients that had information on the first and second TB episodes. The variables studied were chosen as TB risk factors according to previous reports about TB recurrence. The existence of missing data was assessed and missing data characterised (missingness between 0 and 10%). From this characterisation, we chose to explore multiple imputation using random-forest based on multivariate imputation by chained equations. We used a semi-parametric Cox regression model in which the event of interest was the second episode of TB, with time being measured from the end of treatment for a first TB episode. Patients without the second episode of TB before the end of the study were eliminated. A total of 8364 individuals were analysed, of which 145 (1.73%) had a recurrent TB episode during the time of the

Item Type: Article
Additional Information: Letter to the Editor
Subjects: WF Respiratory System > Tuberculosis > WF 200 Tuberculosis (General)
WF Respiratory System > Tuberculosis > WF 205 Epidemiology
WF Respiratory System > Tuberculosis > WF 205.1 General coverage
Faculty: Department: Biological Sciences > Vector Biology Department
Digital Object Identifer (DOI):
Depositing User: Samantha Sheldrake
Date Deposited: 29 Jun 2020 09:25
Last Modified: 28 Sep 2020 09:29


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