Making sense of agreement among interferon-gamma release assays and tuberculosis skin testing

Area of Science:

• Infectious Diseases
• Diagnostic Accuracy
• Mathematical Modeling

Background:

• Interferon-gamma release assays (IGRAs) and tuberculin skin testing (TST) are used for latent tuberculosis infection (LTBI) diagnosis.
• Lack of a framework to assess agreement between IGRA and TST hinders interpretation of study variability.
• Understanding agreement variability is crucial for accurate LTBI assessment.

Purpose of the Study:

• To develop a mathematical model to explain variations in agreement between IGRA and TST.
• To investigate the impact of cut-off point selection on IGRA and TST agreement.
• To provide a framework for analyzing discrepancies in IGRA and TST results.

Main Methods:

• A mathematical model for agreement between dichotomous diagnostic tests was employed.
• The model was used to analyze variations in agreement between IGRA and TST results.
• Published literature was used to illustrate model-based predictions and explore cut-off effects.

Main Results:

• Deviations from model predictions suggest potential issues with prevalence surrogates in IGRA and TST studies.
• Test agreement is dependent on cut-off point selection for a given prevalence of Mycobacterium tuberculosis infection.
• Altering cut-off points can lead to varied changes in test agreement, including increases, decreases, or no change.

Conclusions:

• The proposed mathematical model explains paradoxical findings in IGRA studies.
• Study-to-study variability in IGRA and TST agreement is influenced by factors like experimental error, clinical risk, and non-tuberculous mycobacteria prevalence.
• Re-analysis of existing studies using this model may reveal new hypotheses, emphasizing the need for epidemiologically well-characterized populations in future IGRA research.