# Predictors of drug-resistant TB outcomes: Body mass index, HIV, and comorbidities

## TL;DR

This study explores how factors like BMI, HIV, and comorbidities affect treatment outcomes for drug-resistant tuberculosis patients in South Africa.

## Contribution

The study highlights the limited predictive power of BMI and HIV alone, emphasizing the role of comorbidities and socioeconomic factors in DR-TB outcomes.

## Key findings

- Extensively drug-resistant TB patients had the poorest treatment outcomes.
- Substance use and income level were stronger predictors of treatment success than BMI or HIV status.
- A multidimensional approach is needed to improve DR-TB treatment outcomes.

## Abstract

The success rates for treating drug-resistant tuberculosis (DR-TB) in programmatic settings have been unsatisfactory. By identifying the factors that predict treatment outcomes, we can implement effective corrective measures that will significantly enhance patient management and improve results for those with DR-TB.

This study aimed to investigate predictive factors influencing treatment outcomes among DR-TB patients, focusing on the combined effects of body mass index (BMI), human immunodeficiency virus (HIV) status, comorbidities, socioeconomic factors, substance use and DR-TB type.

The study was conducted in rural Eastern Cape, South Africa.

This retrospective cohort study was designed to utilise logistic regression models on data from 200 patient medical records. We examined variables including BMI, HIV co-infection, comorbidities (e.g. diabetes, hypertension), income, substance use and DR-TB classifications (multidrug-resistant, rifampicin-resistant, pre-extensively drug-resistant, extensively drug-resistant).

Key findings indicate a weak association between lower BMI and reduced treatment success (odds ratio [OR]: 0.92, 95% confidence interval [CI]: 0.81–1.05). HIV-positive status was marginally associated with lower treatment success (OR: 0.89, 95% CI: 0.75–1.12), while income level and substance use emerged as stronger predictors (e.g. substance use OR: 0.72, 95% CI: 0.60–0.88). Among DR-TB types, extensively drug-resistant tuberculosis patients exhibited the poorest outcomes (OR: 0.55, 95% CI: 0.40–0.75). The multivariate model achieved an accuracy of 63.1%, suggesting limited predictive power of BMI and HIV alone and highlighting the significant influence of comorbidities, socioeconomic status and behavioural factors.

These findings underscore the importance of a multidimensional approach in improving DR-TB treatment outcomes through tailored clinical and social interventions.

The study noted limited connections between DR-TB and various comorbidities. It highlights the necessity of managing coexisting conditions in DR-TB patients because of their significant impact on treatment outcomes. Customised interventions are essential for those with severe or complex comorbidities.