Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model

Mark W. Moses, Alice Zwerling, Adithya Cattamanchi, Claudia M. Denkinger, Niaz Banaei, Sandra V. Kik, John Metcalfe, Madhukar Pai, David Dowdy

Research output: Contribution to journalArticle

Abstract

Healthcare workers (HCWs) in low-incidence settings are often serially tested for latent TB infection (LTBI) with the QuantiFERON-TB Gold In-Tube (QFT) assay, which exhibits frequent conversions and reversions. The clinical impact of such variability on serial testing remains unknown. We used a microsimulation Markov model that accounts for major sources of variability to project diagnostic outcomes in a simulated North American HCW cohort. Serial testing using a single QFT with the recommended conversion cutoff (IFN-g > 0.35 IU/mL) resulted in 24.6% (95% uncertainty range, UR: 23.8-25.5) of the entire population testing false-positive over ten years. Raising the cutoff to >1.0 IU/mL or confirming initial positive results with a (presumed independent) second test reduced this falsepositive percentage to 2.3% (95%UR: 2.0-2.6%) or 4.1% (95%UR: 3.7-4.5%), but also reduced the proportion of true incident infections detected within the first year of infection from 76.5% (95%UR: 66.3-84.6%) to 54.8% (95%UR: 44.6-64.5%) or 61.5% (95%UR: 51.6-70.9%), respectively. Serial QFT testing of HCWs in North America may result in tremendous over-diagnosis and over-treatment of LTBI, with nearly thirty false-positives for every true infection diagnosed. Using higher cutoffs for conversion or confirmatory tests (for initial positives) can mitigate these effects, but will also diagnose fewer true infections.

Original languageEnglish (US)
Article number30781
JournalScientific reports
Volume6
DOIs
StatePublished - Jul 29 2016

ASJC Scopus subject areas

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    Moses, M. W., Zwerling, A., Cattamanchi, A., Denkinger, C. M., Banaei, N., Kik, S. V., Metcalfe, J., Pai, M., & Dowdy, D. (2016). Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model. Scientific reports, 6, [30781]. https://doi.org/10.1038/srep30781