Longitudinal dynamics and treatment-associated determinants of interferon-gamma responses in tuberculosis: a 10-year...

Monitoring treatment efficacy and detecting recurrence are critical in tuberculosis (TB) management. However, longitudinal patterns of interferon-gamma release assay (IGRA) results and the quantitative influence of factors such as treatment remain poorly characterized, leaving its long-term performance unclear. This study aimed to investigate longitudinal changes in IGRA and explore their potential utility for monitoring immune dynamics and treatment response. We retrospectively examined 491 patients with two QuantiFERON-TB Gold tests (≥1-month interval) between 2013 and 2024. Analyses included moving average plots, linear regression, and stratification by time interval, treatment status, and treatment response. Multivariable regression and receiver operating characteristic analyses were performed to identify significant predictors. Longitudinal analysis revealed a significant but weak negative correlation between interferon-gamma (IFN-γ) levels and time, with an estimated decline of -0.33 IU/year (r = -0.17, P = 0.0001), albeit with poor model fit (R² = 0.03, relative root mean square error = 16.33%). Moving average trajectories showed significant differences in changes in IFN-γ levels between treated and untreated subgroups (mean: -0.89 IU/mL, P < 0.001) and between therapy-converted and refractory subgroups (mean: 0.82 IU/mL, P < 0.0001). However, receiver operating characteristic analyses indicated poor discriminative power for these clinical statuses (area under the curve ≤ 0.582). Multivariable regression analysis confirmed diabetes mellitus as an independent factor associated with IFN-γ decreases (coefficient: -1.082, P = 0.040), alongside anti-TB treatment and the testing interval. The waning of IGRA reactivity was evident during TB and post-TB phases. However, despite significant associations with treatment status and treatment response, substantial variability limits its clinical utility. Therefore, QFT trends require cautious interpretation, driving the need for a more reliable assay or superior biomarkers.