# Prevalence and predictors of NTM in presumed/confirmed drug-resistant TB

## TL;DR

This study examines the prevalence of non-tuberculous mycobacteria (NTM) in individuals with drug-resistant tuberculosis in Ghana and identifies factors associated with NTM isolation.

## Contribution

The study provides insights into NTM species distribution and predictors in drug-resistant TB patients in a specific geographic region.

## Key findings

- NTM was isolated in 30.6% of culture-positive samples from drug-resistant TB patients.
- M. intracellulare was the most common NTM species identified.
- Follow-up samples had increased odds of NTM isolation compared to initial samples.

## Abstract

Non-tuberculous mycobacteria (NTM) are increasingly isolated in individuals with presumed/confirmed pulmonary TB. We aimed to estimate the prevalence and species distribution of NTM among presumed/confirmed drug-resistant TB (DR-TB) individuals and determine NTM isolation predictors.

Sputum samples collected for DR-TB diagnosis and follow-up from 2012 to 2021 in Ghana were retrospectively analysed. Samples were subjected to sputum smear microscopy (SSM) and mycobacterial culture. The MPT64 assay was performed on positive cultures to distinguish between Mycobacterium tuberculosis complex MTBc and NTM. NTM isolates were re-cultured for species identification using GenoType® Mycobacterium CM/AS line-probe assay, polymerase chain reaction, and Sanger sequencing targeting 16S rRNA and rpoB genes. MTBc isolates identified by GenoType underwent spoligotyping. A logistic regression model was used to identify the predictors of NTM isolation.

Of the 2,492 samples, 839 (33.7%) tested culture-positive for mycobacteria, with 257 (30.6%) presumed to be NTM. Of these, 53 (23.6%) were identified at the species level, with a predominance of M. intracellulare (66.0%). MPT64 testing missed 18 (3%) MTBc isolates. Logistic regression showed increased odds of NTM isolation in follow-up samples (aOR 2.41, 95% CI 1.46–3.99). NTM species were isolated from 46 patients, with four classified as NTM pulmonary disease

Enhancing our understanding of local NTM epidemiology and improving local diagnostic capabilities can optimise patient management strategies and outcomes.