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

Background Predictive biomarkers for symptomatic tuberculosis (TB) progression would transform targeted prevention efforts. Although interferon-gamma release assays (IGRAs), including QuantiFERON® TB-Gold Plus (QFT-Plus), have been studied for this purpose, systematic evaluation of the QFT-Plus TB1 and TB2 Interferon-Gamma (IFNγ) concentrations remains limited, particularly in high-burden TB settings. Methods Baseline TB1 and TB2 IFNγ concentrations from 5246 participants (ages 15–34 years) in TB-endemic regions were analyzed in relation to subsequent TB outcomes over a median of 525 days follow-up (NCT05190146). Participants were categorized as controls (no TB), suspected TB (no microbiological confirmation), or laboratory-confirmed TB, including a subset meeting a stringent case definition (≥2 positive microbiologic tests). Associations between baseline IFNγ concentrations and progression to symptomatic TB were assessed. Results In the full cohort (IGRA+/− participants), baseline TB2 IFNγ concentrations were significantly higher compared with controls among participants who developed suspected TB (P = .01), laboratory-confirmed TB (P = .01), or met the stringent case definition (P < .0001). In IGRA+ participants, baseline TB2 concentrations were significantly higher than controls in suspected (P = .01) and laboratory-confirmed (P = .02) groups. Associations with baseline TB1 IFNγ concentrations and TB progression were observed for participants meeting the stringent case definition within the full cohort (P = .001). Among stringent definition cases, TB2 concentrations achieved an area under the receiver operating characteristic curve of 0.84, with sensitivity of 80% and specificity of 78%. Conclusions Quantitative IFNγ 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.