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Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model
Mark W Moses1, Alice Zwerling1, Adithya Cattamanchi2
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Scientific Reports
|July 30, 2016
Summary
Serial latent tuberculosis infection testing in healthcare workers using the QuantiFERON-TB Gold assay can lead to significant over-diagnosis. Adjusting test cutoffs or using confirmatory tests reduces false positives but may miss true infections.
Area of Science:
- Infectious Diseases
- Public Health
- Diagnostic Accuracy
Background:
- Healthcare workers (HCWs) in low-incidence settings undergo serial latent tuberculosis infection (LTBI) testing using the QuantiFERON-TB Gold In-Tube (QFT) assay.
- The QFT assay shows frequent test result variability (conversions and reversions), raising concerns about its clinical impact in serial testing protocols.
Purpose of the Study:
- To project the diagnostic outcomes of serial QFT testing in a simulated North American HCW cohort.
- To evaluate the impact of different QFT testing strategies on false-positive rates and true infection detection.
Main Methods:
- A microsimulation Markov model was employed to simulate a North American HCW cohort undergoing serial QFT testing.
- The model incorporated major sources of variability inherent in the QFT assay and serial testing protocols.
Main Results:
- Serial QFT testing with the standard cutoff (>0.35 IU/mL) resulted in a 24.6% false-positive rate over ten years.
- Increasing the QFT cutoff to >1.0 IU/mL or using a confirmatory test reduced false positives to 2.3% and 4.1%, respectively.
- However, these adjusted strategies also decreased the detection of true incident infections within the first year from 76.5% to 54.8% or 61.5%.
Conclusions:
- Serial QFT testing in North American HCWs may lead to substantial over-diagnosis and over-treatment of LTBI.
- Implementing higher QFT cutoffs or confirmatory testing can mitigate over-diagnosis but may compromise the timely detection of true infections.

