Risk factors for poor engagement in drug-resistant TB care in South Africa: a systematic review

McNabb, Katherine C.; Bergman, Alanna; Farley, Jason E.

doi:10.5588/pha.21.0007

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Then, among recurrent cases from these two countries, the MDR-TB prevalence was 3.9% 17.7% respectively [ 12 ]. In 2019, 23 persons per every 100,000 in the South Africa population were reported to have MDR-TB [ 13 , 14 ]. Regarding risk factors, recent studies conducted in Tanzania and Niger showed TB relapse , history of irregular treatment, cigarette smoking, alcohol abuse, treatment failure, underweight and HIV as leads factors of MDR-TB occurrence [ 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

et al. 2021

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Background Despite the World Health Organization efforts to expand access to the tuberculosis treatment, multidrug resistant tuberculosis (MDR-TB) remains a major threat. MDR-TB represents a challenge for clinicians and staff operating in national tuberculosis (TB) programmes/centres. In sub-Saharan African countries including Burundi, MDR-TB coexists with high burden of other communicable and non-communicable diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence which well defines the at-risk population. In this study, using data from two referral anti-tuberculosis in Burundi, we model the key factors associated with MDR-TB in Burundi. Methods A case-control study was conducted from 1stAugust 2019 to 15th January 2020 in Kibumbu Sanatorium and Bujumbura anti-tuberculosis centres for cases and controls respectively. In all, 180 TB patients were selected, comprising of 60 cases and 120 controls using incidence density selection method. The associated factors were carried out by mixed effect logistic regression. Model performance was assessed by the Area under Curve (AUC). Model was internally validated via bootstrapping with 2000 replications. All analysis were done using R Statistical 3.5.0. Results MDR-TB was more identified among patients who lived in rural areas (51.3%), in patients’ residence (69.2%) and among those with a household size of six or more family members (59.5%). Most of the MDR-TB cases had already been under TB treatment (86.4%), had previous contact with an MDR-TR case (85.0%), consumed tobacco (55.5%) and were diabetic (66.6 %). HIV prevalence was 32.3 % in controls and 67.7 % among cases. After modelling using mixed effects, Residence of patients (aOR= 1.31, 95%C: 1.12-1.80), living in houses with more than 6 family members (aOR= 4.15, 95% C: 3.06-5.39), previous close contact with MDR-TB (aOR= 6.03, 95% C: 4.01-8.12), history of TB treatment (aOR= 2.16, 95% C: 1.06-3.42), tobacco consumption (aOR = 3.17 ,95% C: 2.06-5.45) and underlying diabetes’ ( aOR= 4.09,95% CI = 2.01-16.79) were significantly associated with MDR-TB. With 2000 stratified bootstrap replicates, the model had an excellent predictive performance, accurately predicting 88.15% (95% C: 82.06%-92.8%) of all observations. The coexistence of risk factors to the same patients increases the risk of MDR-TB occurrence. TB patients with no any risk factors had 17.6% of risk to become MDR-TB. That probability was respectively three times and five times higher among diabetic and close contact MDR-TB patients. Conclusion The relatively high TB’s prevalence and MDR-TB occurrence in Burundi raises a cause for concern especially in this context where there exist an equally high burden of chronic diseases including malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.

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Section: Introductionmentioning

confidence: 99%

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

et al. 2021

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“…However, a lack of national reporting of adverse events precluded comparisons of toxicity between the two cohorts. We found no evidence that measured patient characteristics shown to be associated with dropout from MDR/RR-TB treatment such as HIV, previous TB treatment, sex, and age [ 23 ], were responsible for the difference by accounting for them in the analysis. However, it is possible other unmeasured factors may be responsible.…”

Section: Discussionmentioning

confidence: 97%

Treatment of Multidrug-resistant or Rifampicin-resistant Tuberculosis With an All-oral 9-month Regimen Containing Linezolid or Ethionamide in South Africa: A Retrospective Cohort Study

Morgan,

Ndjeka,

Hasan

et al. 2024

Clinical Infectious Diseases

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Background In 2019, the South African tuberculosis program replaced ethionamide with linezolid as a part of an all-oral 9-month regimen. We evaluated treatment outcomes for patients assigned to regimens including linezolid in 2019 and ethionamide in 2017. Method This retrospective cohort study included patients treated for multi-drug resistant/rifampicin-resistant tuberculosis throughout South Africa between 1 Jan to 31 Dec 2017 and from 1 Jan to 31 Dec 2019. The cohort treated with a 9-month regimen containing ethionamide for four months, was compared with a cohort treated with a 9-month regimen containing linezolid for two months. The regimens were otherwise identical. Inverse probability weighting of propensity scores was used to adjust for potential confounding. A log-binomial regression model was used to estimate adjusted relative risk (aRR) comparing 24-month outcomes between cohorts including treatment success, death, loss to follow up, and treatment failure. Adverse event data were available for the linezolid cohort. Findings 817 patients were included in the cohort receiving ethionamide and 4244 in the cohort receiving linezolid. No evidence for a difference was observed between linezolid and ethionamide regimens for treatment success (aRR = 0·96, 95%CI 0·91-1·01), death (aRR = 1·01, 95%CI 0·87-1·17) or treatment failure (aRR = 0·87, 95%CI 0·44-1·75). Loss to follow up was more common in the linezolid group, although estimates were imprecise (aRR = 1·22, 95%CI 0·99-1·50). Interpretation No significant differences in treatment success and survival were observed with substitution of linezolid for ethionamide as a part of an all-oral 9-month regimen. Linezolid is an acceptable alternative to ethionamide in this shorter regimen for treatment of multi-drug resistant/rifampicin resistant tuberculosis.

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“…Risk factor identification: A critical step in developing effective interventions involves the identification of risk factors associated with poor engagement in MDR-TB care [ 56 ]. Factors such as missed appointments, treatment interruption, sub-optimal medication adherence, and loss of follow-up must be recognized and addressed systematically.…”

Section: Reviewmentioning

confidence: 99%

“…Factors such as missed appointments, treatment interruption, sub-optimal medication adherence, and loss of follow-up must be recognized and addressed systematically. Consistent risk factors, such as male sex and younger age, have been identified as predictors of poor engagement [ 56 ].…”

Section: Reviewmentioning

confidence: 99%

A Comprehensive Review on Long vs. Short Regimens in Multidrug-Resistant Tuberculosis (MDR-TB) Under Programmatic Management of Drug-Resistant Tuberculosis (PMDT)

Karnan,

Jadhav,

Ghewade

et al. 2024

Cureus

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This comprehensive review delves into the intricate landscape of multidrug-resistant tuberculosis (MDR-TB) treatment within the programmatic management of drug-resistant tuberculosis (PMDT) framework. MDR-TB poses a substantial global health threat, necessitating targeted approaches for effective management. The analysis explores the historical evolution, efficacy, safety profiles, and implementation challenges associated with long and short regimens. The findings underscore the importance of individualized clinical practices, considering patient-specific factors, and the need for ongoing monitoring within PMDT programs. Recommendations advocate for integrating advanced diagnostics, continuous surveillance, and training for healthcare professionals. The review concludes with a nuanced outlook on long versus short regimens, emphasizing a balanced approach and the imperative role of collaborative efforts in shaping the future of MDR-TB treatment. This synthesis contributes to the ongoing discourse, providing valuable insights for healthcare practitioners, policymakers, and researchers working toward optimizing outcomes for individuals afflicted with MDR-TB.

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Risk factors for poor engagement in drug-resistant TB care in South Africa: a systematic review

Cited by 7 publications

References 25 publications

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

Treatment of Multidrug-resistant or Rifampicin-resistant Tuberculosis With an All-oral 9-month Regimen Containing Linezolid or Ethionamide in South Africa: A Retrospective Cohort Study

A Comprehensive Review on Long vs. Short Regimens in Multidrug-Resistant Tuberculosis (MDR-TB) Under Programmatic Management of Drug-Resistant Tuberculosis (PMDT)

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