ArticleInflammation2012
Comparison of quantiferon test with tuberculin skin test for the detection of tuberculosis infection in children.
Article in Inflammation, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 11 citations in OpenAlex.
- Pooled it
- Risk Factors for Indeterminate Interferon-Gamma Release Assay for the Diagnosis of Tuberculosis in Children-A Systematic Review and Meta-Analysis.Frontiers in pediatrics · 2019Pooled it
- Comparison of interferon gamma release assays and tuberculin skin test performance for diagnosing Mycobacterium tuberculosis infection in the Pakistani population.Scientific reports · 2025Article
- Interferon-Gamma Release Assays Versus Tuberculin Skin Test for Active Tuberculosis Diagnosis: A Systematic Review and Diagnostic Meta-Analysis.Diagnostics (Basel, Switzerland) · 2025Review
- Comparison of IFN-γ Levels in Children with Tuberculosis Disease (TB) and Latent Tuberculosis Infection (LTBI).Open access Macedonian journal of medical sciences · 2018Article
- Interferon-gamma release assay for the diagnosis of latent tuberculosis infection: A latent-class analysis.PloS one · 2017Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The efficacy of Quantiferon-TB gold test (QFT-GIT) remains to be documented in pediatric population. Tuberculin skin test (TST) is a conventional test available for the diagnosis of latent tuberculosis infection (LTBI). We aimed to investigate the concordance between QFT-GIT and TST in children with and without tuberculosis infection. Ninety-seven patients, aged 3 months-14 years, admitted to pediatric outpatient clinics of Dr. Sadi Konuk Training Hospital Bakırköy, Turkey between March 2008 and April 2009 were recruited. Demographic features, TST results, history of exposure to active tuberculosis (TB), chest X-ray findings, clinical history, presence of Bacillus Calmette Guerin (BCG) vaccination scar were recorded. Patients were categorized into four groups namely, active TB, LTBI, no TB and healthy. It was found that BCG scar positivity did not influence QFT-GIT results. There was a statistically significant agreement between QFT-GIT and TST results (κ = 0.486; p < 0.01). In patients ≥ 5 years of age, TST positivity and QFT positivity had a significant relationship (p < 0.01). In all patient groups, sensitivity and specificity was 65.85 % and 82.14 %, respectively. In active TB group, TST and QFT-GIT results demonstrated significant agreement ratio of 40.8 % (κ = 0.364; p < 0.01). Sensitivity and specificity was 100 % and 30 %, respectively. Utilization of QFT-GIT in the diagnosis of LTBI reduces false-positive results and prevents unnecessary treatment with INH and its adverse effects.
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Registered trials
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.