Evidence map›Paper›PMID 39802700›Full record

ArticleBiomarker insights2025

Differentiating Latent Tuberculosis from Active Tuberculosis Through Activation Phenotypes and Chemokine Markers HLA-DR, CD38, MCP-1, and RANTES: A Systematic Review and Meta-Analysis.

Chaimae Kadi, Narjisse Ahmadi, Anass Houdou, Imad El Badisy, Oumnia Bouaddi, Zakaria Mennane, Nouhaila Najimi, Maryam Benlamari, Saber Boutayeb, Mohamed Khalis and 2 more

Abstract read
In one paragraph

Article in Biomarker insights, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Chaimae KadiLaboratory of Biology and Health, Faculty of Sciences of Tetouan, Abdelmalek Essaâdi University, Tetouan, Morocco.
Narjisse AhmadiMohammed VI University of Sciences and Health, Casablanca, Morocco.
Anass HoudouMohammed VI University of Sciences and Health, Casablanca, Morocco.
Imad El BadisyMohammed VI University of Sciences and Health, Casablanca, Morocco.
Oumnia BouaddiMohammed VI University of Sciences and Health, Casablanca, Morocco.
Zakaria MennaneLaboratory of Biology and Health, Faculty of Sciences of Tetouan, Abdelmalek Essaâdi University, Tetouan, Morocco.
Nouhaila NajimiMohammed VI University of Sciences and Health, Casablanca, Morocco.
Maryam BenlamariMohammed VI University of Sciences and Health, Casablanca, Morocco.
Saber BoutayebMohammed VI University of Sciences and Health, Casablanca, Morocco.
Mohamed KhalisMohammed VI University of Sciences and Health, Casablanca, Morocco.
Noureddine El MtiliLaboratory of Biology and Health, Faculty of Sciences of Tetouan, Abdelmalek Essaâdi University, Tetouan, Morocco.
Fouad SeghrouchniHigher Institute of Nursing Professions and Health Techniques, Rabat, Ministry of Health and Social Protection, Rabat, Morocco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Latent TB infection (LTBI) affects one fourth of the global population. Currently, there is an absence of an optimal strategy for distinguishing between active tuberculosis (aTB) and LTBI. While some researchers have explored cytokines other than interferon-gamma (IFN-γ) as biomarkers, results have shown significant variability in their ability to differentiate between these conditions. This meta-analysis aims to evaluate the performance of activation phenotype and chemokine markers in distinguishing between aTB and LTBI. Objectives: To assess the diagnostic accuracy of specific biomarkers (HLA-DR Design: This study was conducted in accordance with the PRISMA guidelines for systematic reviews and meta-analyses of diagnostic studies. Data sources and methods: We conducted a comprehensive search of PubMed, Scopus, Sciences Direct, and Web of Science for primary studies published in English up to 2023. Studies were included if they reported sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) for the biomarkers in question. We calculated pooled diagnostic sensitivity, specificity, DOR, and AUC, and used the summary receiver operating characteristic curve (SROC) to summarize the diagnostic performance of each biomarker. Results: Sixteen studies involving 1696 participants were included in the analysis. Among them, 925 individuals were diagnosed with aTB, while 771 were classified as having LTBI. The specificity, sensitivity, DOR, and AUC for CD38 Conclusion: The findings indicate that CD38 Registration: This review has been registered on PROSPERO: (CRD42023472091). Available from: https://www.crd.york.ac.uk/prospero/#recordDetails.

Indexed as

Activation phenotype markersCD38ChemokineDiagnosisHLAD-DRMCP-1Meta-analysisRANTESTuberculosis

Identifiers

PMID39802700
PMCPMC11713980

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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.