Evidence map›Paper›PMID 22095393›Full record

ArticleRheumatology international2012

Detection of latent tuberculosis infection in rheumatologic diseases before anti-TNFα therapy: tuberculin skin test versus IFN-γ assay.

Ismail Hanta, Suleyman Ozbek, Sedat Kuleci, Gulsah Seydaoglu, Ezgi Ozyilmaz

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Rheumatology international, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
0.2field-weighted citation impact, top 47% 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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Observational
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

5 authors at 1 institution in 1 country.

Ismail HantaDepartment of Chest Diseases, Faculty of Medicine, University of Cukurova, 01330 Balcali, Adana, Turkey. ihanta@cu.edu.tr
Suleyman Ozbek
Sedat Kuleci
Gulsah Seydaoglu
Ezgi Ozyilmaz
Cukurova University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to evaluate tuberculin skin test (TST) and interferon-gamma (IFN-γ) test results for latent tuberculosis infection (LTBI) in patients with rheumatologic diseases prior to anti-TNFα therapy. Ninety patients were evaluated in the study at the Departments of Chest Diseases and Rheumatology for anti-TNFα therapy for their rheumatologic diseases. Tuberculin skin test was performed (Mantoux method) and peripheral blood samples were collected for IFN-γ assay (QuantiFeron TB-Gold In Tube) before the anti-TNFα therapy. Of 90 patients, TST positivity was detected in 56 (62.2%) patients, while IFN-γ positivity was detected in 34 (37.8%) patients. Among 56 TST positive patients, IFN-γ positivity was detected in 24 (42.9%) patients, and among 34 TST negative patients, IFN-γ positivity was detected in 10 (29.4%) patients. There was no significant agreement between TST and IFN-γ assay results (Kappa = 0.12, P = 0.2). Forty-three (47.8%) patients were using immunosuppressive drugs owing to their rheumatologic diseases. In this group, TST and IFN-γ positivity is significantly lower than in those who did not receive immunosuppressive treatment (P < 0.05). We conclude that the IFN-γ assay may not be preferred to TST as a diagnostic test in patients with rheumatologic diseases prior to anti-TNFα treatment.

Indexed as

AdultFemaleHumansInterferon-gammaLatent TuberculosisMaleMiddle AgedRheumatic DiseasesTuberculin TestInterferon-gamma

Identifiers

PMID22095393
OpenAlexW2091489660

What OpenQuestion holds

Textmetadata
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.