ArticlePloS one2021
Determinants of tuberculosis treatment interruption among patients in Vihiga County, Kenya.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Article
- Dietary practices and nutritional status of adult pulmonary tuberculosis patients in Kiambu level five hospital, Kiambu county, Kenya.BMC nutrition · 2026Article
- Analysis of rpoB mutations associated with rifampicin resistance in Mycobacterium tuberculosis isolates in Malawi.BMC infectious diseases · 2026Article
- Prevalence of comorbidities and their impact on prognosis among patients with rifampicin-resistant tuberculosis: a multicenter retrospective cohort study in China.Scientific reports · 2025Article
- Antimicrobial resistance, equity and justice in low- and middle-income countries: an intersectional critical interpretive synthesis.Nature communications · 2025Article
- Lived experiences of persons on tuberculosis treatment in Nairobi County, Kenya: a mixed methods study.BMC public health · 2024Article
- Determinants of an unfavorable treatment outcome among tuberculosis patients in the Jimma Zone, Southwest Ethiopia.Scientific reports · 2024Article
- Development and validation of a prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance tuberculosis.BMC infectious diseases · 2023Article
- Incidence and predictors of treatment interruption among patients on anti-tuberculosis treatment in Nekemte public healthcare facilities, Oromia, Western Ethiopia.Frontiers in epidemiology · 2023Article
- Treatment Outcomes and Risk Factors of Multidrug-Resistant Tuberculosis Patients in Xi'an China, a Retrospective Cohort Study.Infection and drug resistance · 2022Article
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3 authors.
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Abstract
backgroundDespite robust Tuberculosis (TB) program with effective chemotherapy and high coverage, treatment interruption remains a serious problem. Interrupting TB treatment means that patients remain infectious for longer time and are at risk of developing drug resistance and death. This study was conducted to identify and describe predictors of TB treatment interruption.
methodsA cohort of 291 notified TB patients from 20 selected health facilities in Vihiga County were enrolled in to the study and followed up until the end of treatment. Patient characteristics that potentially predict treatment interruption were recorded during treatment initiation using structured questionnaires. Patients who interrupted treatment were traced and reasons for stoppage of treatment recorded. Kaplan Meier method was used to estimate probabilities of treatment interruption by patient characteristics and determine time intervals. The Log rank test for the equality of survival distributions analyzed significance of survival differences among categorical variables. For multivariable analysis, Cox proportional hazard model, was fitted to identify predictors of TB treatment interruption through calculation of hazard ratios with 95% Confidence Intervals (CIs). For variable analysis, statistical significance was set at P ≤ 0.05. Reasons for treatment interruption were categorized according to most recurrent behavioral or experiential characteristics.
resultsParticipants' median age was 40 years (IQR = 32-53) and 72% were male. Of the 291 patients, 11% (n = 32) interrupted treatment. Incidences of treatment interruption significantly occurred during intensive phase of treatment. Independent predictors of treatment interruption included alcohol consumption (HR = 9.2, 95% CI; 2.6-32.5, p < 0.001), being female (HR = 5.01, 95% CI; 1.68-15.0, p = 0.004), having primary or lower education level (HR = 3.09, 95% CI; 1.13-8.49, p < 0.029) and having a treatment supporter (HR = 0.33, 95% CI; 0.14-0.76, p = 0.009). Reasons for interrupting treatment were categorized as: alcoholism, feeling better after treatment initiation, associated TB stigma, long distance to health facility, lack of food, perception of not having TB and pill burden.
conclusionTB treatment interruption was high and largely associated with patients' socio-demographic and behavioral characteristics. These multidimensional factors suggest the need for interventions that not only target individual patients but also environment in which they live and receive healthcare services.
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