title: Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model.
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 false-positive 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.
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
authors.forename: Mark W
authors.initials: MW
authors.lastname: Moses
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
authors.forename: Alice
authors.initials: A
authors.lastname: Zwerling
authors.affiliation: Department of Medicine, UCSF, San Francisco, USA.
authors.forename: Adithya
authors.initials: A
authors.lastname: Cattamanchi
authors.affiliation: Tuberculosis and Hepatitis Programme, FIND, Geneva, Switzerland.
authors.forename: Claudia M
authors.initials: CM
authors.lastname: Denkinger
authors.affiliation: Department of Medicine, Stanford University, Palo Alto, USA.
authors.forename: Niaz
authors.initials: N
authors.lastname: Banaei
authors.affiliation: Evidence Team, KNCV, The Hague, Netherlands.
authors.forename: Sandra V
authors.initials: SV
authors.lastname: Kik
authors.affiliation: Department of Medicine, UCSF, San Francisco, USA.
authors.forename: John
authors.initials: J
authors.lastname: Metcalfe
authors.affiliation: Department of Epidemiology &Biostatistics and McGill International TB Centre, McGill University, Montreal, Canada.
authors.forename: Madhukar
authors.initials: M
authors.lastname: Pai
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
authors.forename: David
authors.initials: D
authors.lastname: Dowdy
mesh_terms: D015331:Cohort Studies; D005189:False Positive Reactions; D005260:Female; D006282:Health Personnel; D006801:Humans; D015994:Incidence; D059425:Interferon-gamma Release Tests / Q000379:methods*; D055985:Latent Tuberculosis / Q000175:diagnosis* / Q000453:epidemiology; D008297:Male; D008390:Markov Chains; D008403:Mass Screening; D000069342:Medical Overuse / Q000706:statistics & numerical data; D015233:Models, Statistical; D009656:North America / Q000453:epidemiology; D012680:Sensitivity and Specificity