Objectives We evaluated the qualitative and quantitative agreement of the novel chemiluminescent TB-IGRA VIRCLIA® Monotest with QuantiFERON®-TB Gold Plus (QFT-Plus) for detecting tuberculosis infection. Methods In this prospective comparative study, 226 consecutive samples submitted for routine tuberculosis infection testing were analyzed using the TB-IGRA VIRCLIA® Monotest and the QFT-Plus chemiluminescence immunoassay (CLIA). Agreement between the two tests was assessed by calculating the overall agreement, positive and negative percent agreement (PPA/NPA), Cohen’s kappa ( κ ), Deming regression, and Bland–Altman analysis. An exploratory QFT-Plus-derived borderline range (0.20–0.70 IU/mL) was analyzed separately. Additional quantitative analyses were performed after excluding observations at the QFT-Plus upper quantification limit (10 IU/mL). Results Overall qualitative agreement was 92.9% ( κ = 0.85; 95% confidence interval (CI), 0.79–0.92), with PPA of 90.1% (95% CI, 83.8–94.1) and NPA of 96.8% (95% CI, 91.1–98.9). Agreement was 94.25% for TB1 ( κ = 0.885; 95% CI, 0.824–0.945) and 89.82% for TB2 ( κ = 0.796; 95% CI, 0.718–0.875). In the borderline range, agreement decreased to 78.05% for TB1 ( κ = 0.529; 95% CI, 0.289–0.769) and 69.05% for TB2 ( κ = 0.316; 95% CI, 0.067–0.564), compared to 97.84 and 94.57%, respectively, for values outside this range. Deming regression slopes decreased from 3.085 to 0.811 for TB1 and from 3.146 to 0.926 for TB2 after excluding observations at the QFT-Plus upper quantification limit, with substantially narrower Bland–Altman limits of agreement. Conclusion The TB-IGRA VIRCLIA® Monotest showed a high overall qualitative agreement with QFT-Plus, particularly outside the borderline range. Agreement decreased near the positivity threshold, particularly for TB2, supporting cautious interpretation and potential repeat or confirmatory testing of borderline results. Quantitative comparisons at high interferon-gamma (IFN-γ) concentrations were substantially influenced by the QFT-Plus upper quantification limit.
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Serrano et al. (2026) studied this question.
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