Biomarkers Correlated with Tuberculosis Preventive Treatment Response: A Systematic Review and Meta-Analysis.

Haoran Zhang, Zuyu Sun, Yi Liu, Rongrong Wei, Nanying Che

Abstract readReview

In one paragraph

Review in Microorganisms, 2023. 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

–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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Haoran ZhangBiobank of Beijing Chest Hospital, Capital Medical University, Beijing 100054, China.

Zuyu SunDepartment of Pathology, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing Chest Hospital, Capital Medical University, Beijing 100054, China.

Yi LiuBiobank of Beijing Chest Hospital, Capital Medical University, Beijing 100054, China.

Rongrong WeiBiobank of Beijing Chest Hospital, Capital Medical University, Beijing 100054, China.

Nanying CheBiobank of Beijing Chest Hospital, Capital Medical University, Beijing 100054, China.ORCID 0000-0003-4179-1737

Funding

Beijing Municipal Science and Technology Project Z191100006619079National Natural Science Foundation of China 82072381

6 · The paper itself

Abstract

backgroundThere is a need to identify alternative biomarkers to predict tuberculosis (TB) preventive treatment response because observing the incidence decline renders a long follow-up period.

methodsWe searched PubMed, Embase and Web of Science up to 9 February 2023. The biomarker levels during preventive treatment were quantitatively summarized by means of meta-analysis using the random-effect model.

resultsEleven eligible studies, published during 2006-2022, were included in the meta-analysis, with frequently heterogeneous results. Twenty-six biomarkers or testing methods were identified regarding TB preventive treatment monitoring. The summarized standard mean differences of interferon-γ (INF-γ) were -1.44 (95% CI: -1.85, -1.03) among those who completed preventive treatment (τ

conclusionsOur results suggested that decreased INF-γ was observed among those who completed preventive treatment but not in those without preventive treatment. Further studies are warranted to explore its value in preventive treatment monitoring due to limited available data and extensive between-study heterogeneity.

Indexed as

biomarkersmeta-analysismonitoringpreventive treatmenttuberculosis

Identifiers

PMID36985316

DOI10.3390/microorganisms11030743

PMCPMC10057454

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