Abstract:
Tuberculosis (TB) is a global health concern; nearly one-third of the global
population is infected with Mycobacterium tuberculosis and at risk of developing the disease
(WHO, 2011). The objective of this study is to Model time –to- cure of tuberculosis patients
using mixture cure model and identify the risk factors for the cure of tuberculosis patients under
DOTS.
Methods: longitudinal retrospective cohort (1st July, 2014 and 1st January, 2016) follow up
(retrospective cohort design) of tuberculosis patients’ data were obtained from Jimma University
Specialized Hospital TB Patient Clinic located in Jimma town. Univariate and multivariate
analyses were performed using a logistic Cox PH mixture cure model and for uncured group
standard Cox regression model.
Results: Of all 501 tuberculosis patients 439(87.62%) susceptible group 328(74.15%) were
cured. The median cure time from TB was 6 months and 62(12.37%) non susceptible those
multi-drug resistance TB none of them cured with in the follow up period. In the two population
susceptible and non-susceptible or multidrug resistances TB the most of the MDR-TB patients
are pulmonary negative 55 of them. From these patients of TB type pulmonary negative was risk
to develop MDR-TB. An increased incidence of TB was reported for smear result (pulmonary
positive, pulmonary negative and extra pulmonary), weight at initiation of treatment and HIV
(HIV-/HIV+) were the risk factors predicting time to cure from tuberculosis diseases. HR and
95%CI were 2.3 [1.808 :3.121], 0.9853 [0.9766 :0.9941] and 0.7564 [0.522 , 1.095]
respectively. Then both direction selection methods are applied using the software and
AIC=3455.42 were small with the following end covariates.
Conclusions: body weight at initiation of treatment and smear result are the risk factor for time
to cure in tuberculosis patients in multivariable Cox proportional regression model during anti
tuberculosis treatment period for uncured and regiment in addition two was the risk for cured
population in multivariable logistic Cox PH mixture cure model.
