Evidence map›Paper›PMID 27469388›Full record

ArticleScientific reports2016

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

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Capturing RecentTropical medicine and infectious disease · 2024
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  13. Paradox of serial interferon-gamma release assays: variability width more important than specificity size.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2018
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 4 countries.

Mark W MosesDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Alice ZwerlingDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Adithya CattamanchiDepartment of Medicine, UCSF, San Francisco, USA.
Claudia M DenkingerTuberculosis and Hepatitis Programme, FIND, Geneva, Switzerland.
Niaz BanaeiDepartment of Medicine, Stanford University, Palo Alto, USA.
Sandra V KikEvidence Team, KNCV, The Hague, Netherlands.
John MetcalfeDepartment of Medicine, UCSF, San Francisco, USA.
Madhukar PaiDepartment of Epidemiology &Biostatistics and McGill International TB Centre, McGill University, Montreal, Canada.
David DowdyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Johns Hopkins University · USFoundation for Innovative New Diagnostics · CHKoninklijke Nederlandse Chemische Vereniging · NLMcGill University · CAStanford University · US

Funding

CIHR
6 · The paper itself

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.

Indexed as

Health PersonnelModels, StatisticalCohort StudiesFalse Positive ReactionsFemaleHumansIncidenceInterferon-gamma Release TestsLatent TuberculosisMaleMarkov ChainsMass ScreeningMedical OveruseNorth AmericaSensitivity and Specificity

Identifiers

PMID27469388
PMCPMC4965809
OpenAlexW2477849047

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.