| dc.description.abstract | Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis (Mtb), remains a global health threat, presenting significant challenges to effective treatment due to the emergence of drug-resistant strains. The prevalence and mechanisms of drug resistance amplification in TB remain areas of ongoing research and debate.
This study investigated the consequences of suboptimal treatment on the acquisition of drug resistance mutations in Mtb. We sought to assess the frequency of amplification while identifying potential risk factors; in particular, our goal was to understand the true prevalence of resistance amplification. Utilizing patient data collected during a comprehensive TB transmissibility and treatment study in Peru, we examined changes in drug susceptibility profiles through conventional drug sensitivity testing (phenotypic) and identifying genotypic changes via whole-genome sequencing. This dual examination provides a comprehensive understanding of drug resistance dynamics, going beyond conventional phenotypic assessments to explore the genomic landscape.
We investigated various factors that we hypothesized might contribute to suboptimal treatment outcomes, as suboptimal treatment has been associated with resistance amplification. Specifically, we examined variables such as HIV status, diabetes status, the presence of cavitary lesions, Mtb lineage, time to effective treatment, and adherence to treatment regimens.
While logistic regression analysis did not reveal statistically significant relationships between suboptimal treatment and resistance amplification, our study
provides valuable insight into the acquisition of drug-resistance amplification. It underscores the complexity of TB treatment outcomes and emphasizes the need for further investigation into the factors contributing to drug-resistance amplification. Our main finding was that drug-resistance amplification is rare. Thus, relying solely on phenotypic drug susceptibility testing (DST) data may lead to an overestimation of resistance amplification. This finding highlights the importance of considering the limitations of phenotypic DST data and the potential benefits of integrating advanced molecular techniques such as whole genome sequencing to gain a more accurate understanding of drug resistance dynamics in TB patients. | |
