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Khosa, C.

Publications and source records attributed to Khosa, C..

2 recordsLinked to original sources

Associations Between QuantiFERON-TB Gold Plus IFNγ Concentrations and Progression to Symptomatic Tuberculosis in Global High-Burden TB Settings

IntroductionPredictive biomarkers for symptomatic tuberculosis (TB) progression would transform targeted prevention efforts. Although interferon-gamma release assays (IGRAs), including QuantiFERON(R) TB-Gold Plus (QFT-Plus), have been studied for this purpose, systematic evaluation of the QFT-Plus TB1 and TB2 Interferon-Gamma (IFN{gamma}) concentrations remains limited, particularly in high-burden TB settings. MethodsBaseline TB1 and TB2 IFN{gamma} concentrations from 5,259 participants in TB-endemic regions were analyzed in relation to subsequent TB outcomes over a median of 525 days follow-up. Participants were categorized as controls (no TB), suspected TB (no microbiological confirmation), or laboratory-confirmed TB, including a subset meeting a stringent case definition ([&ge;]2 positive microbiologic tests). Associations between baseline IFN{gamma} concentrations and progression to symptomatic TB were assessed. ResultsIn the full cohort (IGRA+/-participants), baseline TB2 IFN{gamma} concentrations were significantly higher compared to controls among participants who developed suspected TB (p=0.01), laboratory-confirmed TB (p=0.01), or met the stringent case definition (p<0.0001). In IGRA+ participants, baseline TB2 concentrations were significantly higher than controls in suspected (p=0.01) and laboratory-confirmed (p=0.02) groups. Associations with baseline TB1 IFN{gamma} concentrations and TB progression were observed for participants meeting the stringent case definition within the full cohort (p=0.009). Among stringent definition cases, TB2 concentrations achieved an area under the Receiver Operating Characteristic curve of 0.84, with a sensitivity of 80% and specificity of 78%. ConclusionsQuantitative IFN{gamma} concentrations from QFT-Plus, particularly TB2, were associated with progression to symptomatic TB, met or exceeded WHO-recommended sensitivity and specificity thresholds for predictive biomarkers, and may support biomarker-based stratification in TB clinical research. SummaryIn an exploratory analysis from a global tuberculosis (TB) epidemiology study, higher QuantiFERON-TB Gold Plus IFN{gamma} concentrations were associated with progression to symptomatic TB and met WHO predictive biomarker thresholds, supporting their potential value for risk stratification in TB research.

immunology↗

Improving diagnosis and monitoring of treatment response in pulmonary tuberculosis using the molecular bacterial load assay (MBLA)

ObjectivesBetter outcomes in tuberculosis require new diagnostic and treatment monitoring tools. In this paper we evaluated the utility of a marker of M. tuberculosis viable count, the Molecular Bacterial Load assay (MBLA) for diagnosis and treatment monitoring of tuberculosis in a high burden setting. MethodsPatients with smear positive pulmonary tuberculosis from two sites in Tanzania and one each in Malawi and Mozambique. Sputum samples were taken weekly for the first 12 weeks of treatment and evaluated by MBLA and mycobacterial growth indicator tube method (MGIT). ResultsThe results of high and low positive control samples confirmed inter site reproducibility. Over the 12 weeks of treatment there was a steady decline in the viable bacterial load as measured by the MBLA that corresponds to rise in time to a positive result (TTP) in the Mycobacterial Growth Indicator Tube. Both MBLA and MGIT provided similar time to test negativity. Importantly, as treatment progressed samples in MGIT were increasingly likely to be contaminated, which compromised the acquisition of results but did not affect MBLA samples. ConclusionsMBLA produces a reproducible measure of Mtb viable count comparable to that of MGIT that is not compromised by contamination in a real-world setting. As a molecular test, the results can be available in as little as four hours and could allow health care professionals to identify rapidly patients who are failing therapy.

microbiology↗