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Effect of Variability on Interferon-Gamma Release Assay Performance: A Quantitative Analysis
1Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; Future Strategy Division, SD Biosensor, Seoul, Korea.
Insights
Interferon-gamma release assays (IGRAs) for latent tuberculosis infection (LTBI) show high variability. Expanding borderline zones in IGRA interpretation can reduce misclassification, but reducing manufacturing and analytical variability is crucial for reliable LTBI diagnosis.
Area of Science:
- Medical Diagnostics
- Immunology
- Infectious Diseases
Background:
- Interferon-gamma release assays (IGRAs) are standard for latent tuberculosis infection (LTBI) detection.
- Inherent variability in IGRAs challenges accurate diagnostic interpretation.
Purpose of the Study:
- To evaluate the impact of coefficient of variation (CV) on IGRA false-positive, false-negative, conversion, and reversion rates.
- To assess the effectiveness of expanding borderline zones in IGRA interpretation.
Main Methods:
- Statistical modeling was used to simulate IGRA results across CVs of 20% to 100%.
- False-positive, false-negative, conversion, and reversion rates were analyzed at various diagnostic cutoffs and borderline zones.
Main Results:
- False-negative rates increased significantly with higher CVs (1.61% to 33.41% at 0.35 IU/mL).
- Expanding the borderline zone from 0.20-0.70 IU/mL to 0.20-1.00 IU/mL reduced false-positive rates (max 3.16%) without impacting false-negative rates.
- High rates of correct reversion and false conversion were observed within borderline zones, dependent on the cutoff used.
Conclusions:
- Implementing borderline zones in IGRA interpretation can mitigate misclassification due to test variability.
- Reducing variability in manufacturing, pre-analytical, and analytical procedures is essential for improving IGRA diagnostic reliability for LTBI.
Abstract:
Interferon-gamma release assays (IGRAs) are widely used to identify latent tuberculosis infection (LTBI); however, inherent test variability affects their diagnostic interpretation. We evaluated false-positive and false-negative rates, as well as conversion and reversion rates across CVs of 20%, 40%, 60%, 80%, and 100%, using statistical modeling. At a diagnostic cutoff of 0.35 IU/mL, false-negative rates increased from 1.61% to 33.41% with increasing CVs, whereas false-positive rates ranged from 0.00% to 15.87% within the 0.20-0.70 IU/mL borderline range. Expanding the borderline to 0.20-1.00 IU/mL reduced false-positive rates to a maximum of 3.16%, without affecting false-negative rates. Within the 0.20-0.70 IU/mL borderline zone, correct reversion and false conversion rates at 0.20 and 0.35 IU/mL ranged from 0.01% to 25.00% and 0.00% to 24.20%, respectively. At 0.35, 0.70, and 1.00 IU/mL, correct conversion and false reversion rates ranged from 0.05% to 24.20% and 0.00% to 25.00%, respectively. These results highlight the importance of adopting borderline zones in IGRA interpretation to reduce misclassification, although variability from manufacturing, pre-analytical processing, and analytical procedures remains a significant challenge. Reducing such variability through improved production consistency, standardized sample handling, and automated analysis platforms is essential to enhance the diagnostic reliability of IGRAs for LTBI.
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