Baseline Xpert MTB/RIF ct values predict sputum conversion during the intensive phase of anti-TB treatment in HIV infected patients in Kampala, Uganda: a retrospective study

Artificial intelligence-based radiographic extent analysis to predict tuberculosis treatment outcomes: a multicenter cohort study

Predicting outcomes in pulmonary tuberculosis is challenging despite effective treatments. This study aimed to identify factors influencing treatment success and culture conversion, focusing on artificial intelligence (AI)-based chest X-ray analysis and Xpert MTB/RIF assay cycle threshold (Ct) values. In this retrospective study across six South Korean referral centers (January 1 to December 31, 2019), we included adults with rifampicin-susceptible pulmonary tuberculosis confirmed by Xpert assay from sputum samples. We analyzed patient characteristics, AI-based tuberculosis extent scores from chest X-rays, and Xpert Ct values. Of 230 patients, 206 (89.6%) achieved treatment success. The median age was 61 years, predominantly male (76.1%). AI-based radiographic tuberculosis extent scores (median 7.5) significantly correlated with treatment success (odds ratio [OR] 0.938, 95% confidence interval [CI] 0.895-0.983) and culture conversion at 8 weeks (liquid medium: OR 0.911, 95% CI 0.853-0.973; solid medium: OR 0.910, 95% CI 0.850-0.973). Sputum smear positivity was 49.6%, with a median Ct of 26.2. However, Ct values did not significantly correlate with major treatment outcomes. AI-based radiographic scoring at diagnosis is a significant predictor of treatment success and culture conversion in pulmonary tuberculosis, underscoring its potential in personalized patient management.

Tuberculosis treatment monitoring tests during routine practice: study design guidance

SCOPE

The current tools for tuberculosis (TB) treatment monitoring, smear microscopy and culture, cannot accurately predict poor treatment outcomes. Research into new TB treatment monitoring tools (TMTs) is growing, but data are unreliable. In this article, we aim to provide guidance for studies investigating and evaluating TB TMT for use during routine clinical care. Here, a TB TMT would guide treatment during the course of therapy, rather than testing for a cure at the regimen's end. This article does not cover the use of TB TMTs as surrogate endpoints in the clinical trial context.

METHODS

Guidelines were initially informed by experiences during a systematic review of TB TMTs. Subsequently, a small content expert group was consulted for feedback on initial recommendations. After revision, feedback from substantive experts across sectors was sought.

QUESTIONS ADDRESSED BY THE GUIDELINE AND RECOMMENDATIONS

The proposed considerations and recommendations for studies evaluating TB TMTs for use during the treatment in routine clinical care fall into eight domains. We provide specific recommendations regarding study design and recruitment, outcome definitions, reference standards, participant follow-up, clinical setting, study population, treatment regimen reporting, and index tests and data presentation. Overall, TB TMTs should be evaluated in a manner similar to diagnostic tests, but TB TMT accuracy must be assessed at multiple timepoints throughout the treatment course, and TB TMTs should be evaluated in study populations who have already received a diagnosis of TB. Study design and outcome definitions must be aligned with the developmental phase of the TB TMT under evaluation. There is no reference standard for TB treatment response, so different reference standards and comparator tests have been proposed, the selection of which will vary depending on the developmental phase of the TMT under assessment. The use of comparator tests can assist in generating evidence. Clarity is required when reporting of timepoints, TMT read-outs, and analysis results. Implementing these recommendations will lead to higher quality TB TMT studies that will allow data to be meaningfully compared, thereby facilitating the development of novel tools to guide individual TB therapy and improve treatment outcomes.

Early Microbiologic Markers of Pulmonary Tuberculosis Treatment Outcomes

Rationale: Earlier biomarkers of pulmonary tuberculosis (PTB) treatment outcomes are critical to monitor shortened anti-TB treatment (ATT). Objectives: To identify early microbiologic markers of unfavorable TB treatment outcomes. Methods: We performed a subanalysis of 2 prospective TB cohort studies conducted from 2013 to 2019 in India. We included participants aged ⩾18 years who initiated 6-month ATT for clinically or microbiologically diagnosed drug-sensitive PTB and completed at least one follow-up visit. Sputum specimens were subjected to a baseline Xpert Mycobacterium tuberculosis/rifampin (MTB/RIF) assay, acid-fast bacilli (AFB) microscopy and liquid and solid cultures, and serial AFB microscopy and liquid and solid cultures at weeks 2, 4, and 8. Poisson regression was used to assess the impact of available microbiologic markers (test positivity, smear grade, time to detection, and time to conversion) on a composite outcome of failure, recurrence, or death by 18 months after the end of treatment. Models were adjusted for age, sex, nutritional status, diabetes, smoking, alcohol consumption, and regimen type. Results: Among 1,098 eligible cases, there were 251 (22%) adverse TB treatment outcomes: 127 (51%) treatment failures, 73 (29%) recurrences, and 51 (20%) deaths. The primary outcome was independently associated with the Xpert MTB/RIF assay (medium-positive adjusted incidence rate ratio [aIRR], 1.91; 95% confidence interval [CI], 1.07-3.40; high-positive aIRR, 2.51; 95% CI, 1.41-4.46), positive AFB smear (aIRR, 1.48; 95% CI, 1.06-2.06), and positive liquid culture (aIRR, 1.98; 95% CI, 1.21-3.23) at baseline; Week 2 positive liquid culture (aIRR, 1.47; 95% CI, 1.04-2.09); and Week 8 positive AFB smear (aIRR, 1.63; 95% CI, 1.06-2.50) and positive liquid culture (aIRR, 1.54; 95% CI, 1.07-2.22). There was no evidence of Mycobacterium tuberculosis growth in the Mycobacterium Growth Indicator Tube at Week 4 conferring a higher risk of adverse outcomes (aIRR, 1.25; 95% CI, 0.89-1.75). Conclusions: Our analysis identifies Week 2 respiratory mycobacterial culture as the earliest microbiologic marker of unfavorable PTB treatment outcomes.

Integrating Molecular Diagnostics and GIS Mapping: A Multidisciplinary Approach to Understanding Tuberculosis Disease Dynamics in South Africa Using Xpert MTB/RIF

An investigation was carried out to examine the use of national Xpert MTB/RIF data (2013-2017) and GIS technology for MTB/RIF surveillance in South Africa. The aim was to exhibit the potential of using molecular diagnostics for TB surveillance across the country. The variables analysed include Mycobacterium tuberculosis (Mtb) positivity, the mycobacterial proportion of rifampicin-resistant Mtb (RIF), and probe frequency. The summary statistics of these variables were generated and aggregated at the facility and municipal level. The spatial distribution patterns of the indicators across municipalities were determined using the Moran's I and Getis Ord (Gi) statistics. A case-control study was conducted to investigate factors associated with a high mycobacterial load. Logistic regression was used to analyse this study's results. There was striking spatial heterogeneity in the distribution of Mtb and RIF across South Africa. The median patient age, urban setting classification, and number of health care workers were found to be associated with the mycobacterial load. This study illustrates the potential of using data generated from molecular diagnostics in combination with GIS technology for Mtb surveillance in South Africa. Spatially targeted interventions can be implemented in areas where high-burden Mtb persists.

Analysis of Dynamic Efficacy Endpoints of the Nix-TB Trial

BACKGROUND

Safer, better, and shorter treatments for multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB) are an urgent global health need. The phase 3 clinical trial Nix-TB (NCT02333799) tested a 6-month treatment of MDR and XDR-TB consisting of high-dose linezolid, bedaquiline, and pretomanid (BPaL). In this study, we investigate the relationship between the pharmacokinetic characteristics of the drugs, patient characteristics and efficacy endpoints from Nix-TB.

METHODS

Pharmacokinetic data were collected at weeks 2, 8, and 16. Efficacy endpoints including treatment outcomes, time to stable culture conversion, and longitudinal time to positivity in the mycobacterial growth indicator tube assay were each characterized using nonlinear mixed-effects modeling. Relationships between patient, treatment pharmacokinetics, and disease characteristics and efficacy endpoints were evaluated.

RESULTS

Data from 93 (85% of the total) participants were analyzed. Higher body mass index was associated with a lower incidence of unfavorable treatment outcomes. Median time to stable culture conversion was 3 months in patients with lower baseline burden compared with 4.5 months in patients with high baseline burden. Participants with minimal disease had steeper time to positivity trajectories compared with participants with high-risk phenotypes. No relationship between any drugs' pharmacokinetics (drug concentration or exposure metrics) and any efficacy outcomes was observed.

CONCLUSIONS

We have successfully described efficacy endpoints of a BPaL regimen from the Nix-TB trial. Participants with high-risk phenotypes significantly delayed time to culture conversion and bacterial clearance. The lack of a relationship between pharmacokinetic exposures and pharmacodynamic biomarkers opens the possibility to use lower, safer doses, particularly for toxicity-prone linezolid.

CLINICAL TRIALS REGISTRATION

NCT02333799.