Is a differentiated care model needed for patients with TB? A cohort analysis of risk factors contributing to unfavourable outcomes among TB patients in two states in South India

Abstract

Background TB is a preventable and treatable disease. Yet, successful treatment outcomes at desired levels are elusive in many national TB programs, including India. We aim to identify risk factors for unfavourable outcomes to TB treatment, in order to subsequently design a care model that would improve treatment outcomes among these at-risk patients. Methods We conducted a cohort analysis among TB patients who had been recently initiated on treatment. The study was part of the internal program evaluation of a USAID-THALI project, implemented in select towns/cities of Karnataka and Telangana, south India. Community Health Workers (CHWs) under the project, used a pre-designed tool to assess TB patients for potential risks of an unfavourable outcome. CHWs followed up this cohort of patients until treatment outcomes were declared. We extracted treatment outcomes from patient’s follow-up data and from the Nikshay portal. The specific cohort of patients included in our study were those whose risk was assessed during July and September, 2018, subsequent to conceptualisation, tool finalisation and CHW training. We used bivariate and multivariate logistic regression to assess each of the individual and combined risks against unfavourable outcomes; death alone, or death, lost to follow up and treatment failure, combined as ‘unfavourable outcome’. Results A significantly higher likelihood of death and experiencing unfavourable outcome was observed for individuals having more than one risk (AOR: 4.19; 95% CI: 2.47–7.11 for death; AOR 2.21; 95% CI: 1.56–3.12 for unfavourable outcome) or only one risk (AOR: 3.28; 95% CI: 2.11–5.10 for death; AOR 1.71; 95% CI: 1.29–2.26 for unfavourable outcome) as compared to TB patients with no identified risk. Male, a lower education status, an initial weight below the national median weight, co-existing HIV, previous history of treatment, drug-resistant TB, and regular alcohol use had significantly higher odds of death and unfavourable outcome, while age > 60 was only associated with higher odds of death. Conclusion A rapid risk assessment at treatment initiation can identify factors that are associated with unfavourable outcomes. TB programs could intensify care and support to these patients, in order to optimise treatment outcomes among TB patients.

Determinants of unsuccessful tuberculosis treatment outcome in Northern Red Sea region, Eritrea

“…In the current study, HIV positive TB patients had a higher likelihood of unsuccessful TB treatment outcomes. This agrees to prior studies that reported higher odds of unsuccessful TB treatment outcomes among HIV positive TB patients [ 7 , 19 , 33 – 35 ] but there were also reports in which unknown HIV status was a determinant of unsuccessful TB treatment outcomes [ 10 , 25 ]. In Eritrea, The implementation of TB-HIV integrated services is well established.…”

Delivery of Community-based Antiretroviral Therapy to Maintain Viral Suppression and Retention in Care in South Africa

“…Studies have shown that among PLHIV with comorbidities, particularly TB, there were benefits to extending intervals between clinic visits and ART pickups from pharmacies; however, routine TB screening was still needed, and risk assessment at treatment initiation to identify factors associated with poor clinical outcomes was recommended. 24,25 Assessment and eligibility criteria may hamper access to the CCMDD program for patients who potentially have the most to gain from adaptive services. In addition, there is also an opportunity to use differentiated care not just for ART delivery but for providing additional TB prophylaxis and screening that support both TB and HIV control measures.…”

Screening for Severe Illness at Diagnosis Has the Potential to Prevent Early TB Deaths: Programmatic Experience From Karnataka, India

“…In the project setting, this assessment of risk was completed at around 2 months, possibly due to delays in laboratory-based HIV, DM, and drug susceptibility testing. 30 The risk assessment indicators used in this study were comprehensive but may be challenging in current programmatic settings. The resultant delay in severity assessment and identification is likely to miss early TB deaths.…”