Evidence map›Paper›PMID 40268506›Full record

SynthesisThe European respiratory journal2025

How to diagnose TB in migrants? A systematic review of reviews and decision tree analytical modelling exercise to evaluate properties for single and combined tuberculosis screening tests.

Dominik Zenner, Hassan Haghparast-Bidgoli, Tahreem Chaudhry, Ibrahim Abubakar, Frank Cobelens

Abstract readSystematic Review
In one paragraph

Synthesis in The European respiratory journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Dominik ZennerWolfson Institute of Population Health, Queen Mary University of London, London, UK d.zenner@qmul.ac.uk.
Hassan Haghparast-BidgoliInstitute for Global Health, University College London, London, UK.
Tahreem ChaudhryWolfson Institute of Population Health, Queen Mary University of London, London, UK.
Ibrahim AbubakarInstitute for Global Health, University College London, London, UK.ORCID https://orcid.org/0000-0002-0370-1430
Frank CobelensAmsterdam University Medical Centers, location Universiteit of Amsterdam, Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimising tuberculosis disease testing algorithms is fundamental to ensuring the effectiveness and cost-effectiveness of migrant screening programmes, including better understanding of individual and combined screening test properties. The aim of our study was to estimate pooled tuberculosis test properties from the literature and combine them in decision analytical modelling with a focus on whether tests used for the diagnosis of tuberculosis infection might add value to these algorithms.

methodsWe performed a systematic review of reviews of diagnostic tests for active tuberculosis, searching PubMed, Embase, Web of Science and Cochrane library, and pooled test properties extracted from original papers included in reviews. We used these pooled results in a decision tree analysis to estimate test properties for common migrant screening algorithms.

resultsWe retrieved 1477 records and included 32 reviews, including data from 437 original studies for 18 tuberculosis tests, providing pooled results for 13. Our modelling showed that algorithms with interferon-γ release assays had the highest diagnostic odds ratios (dORs) (

conclusionsThe significant test accuracy benefit of adding interferon-γ release assays to an active tuberculosis screening pathway will help inform clinicians and policy-makers on the most effective screening algorithms.

Indexed as

Mass ScreeningTransients and MigrantsTuberculosisAlgorithmsCost-Benefit AnalysisDecision TreesHumansInterferon-gamma Release TestsPredictive Value of TestsReview Literature as TopicSensitivity and Specificity

Identifiers

PMID40268506
PMCPMC12287609

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Registered trials

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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.