Evidence map›Paper›PMID 28208160›Full record

ArticlePloS one2017

Quantitative and qualitative profiles of circulating monocytes may help identifying tuberculosis infection and disease stages.

Marco Pio La Manna, Valentina Orlando, Francesco Dieli, Paola Di Carlo, Antonio Cascio, Gilda Cuzzi, Fabrizio Palmieri, Delia Goletti, Nadia Caccamo

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
5.5field-weighted citation impact, top 3% 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

62 citing papers in PubMed, 101 citations in OpenAlex.

  1. Trial
  2. Trial
  3. The lung tissue environment inbioRxiv : the preprint server for biology · 2026
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  11. Antigen specificity shapes antibody functions in tuberculosis.bioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Single-Cell Sequencing Reveals Functional Alterations in Tuberculosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  14. Specific immune response toFrontiers in immunology · 2024
    Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Observational
  20. Article

2 more citing papers are in PubMed but not listed here.

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

9 authors at 3 institutions in 1 country.

Marco Pio La MannaCentral Laboratory of Advanced Diagnosis and Biomedical Research(CLADIBIOR), Azienda Universitaria Ospedaliera Policlinico P. Giaccone, Palermo, Italy.
Valentina OrlandoCentral Laboratory of Advanced Diagnosis and Biomedical Research(CLADIBIOR), Azienda Universitaria Ospedaliera Policlinico P. Giaccone, Palermo, Italy.
Francesco DieliCentral Laboratory of Advanced Diagnosis and Biomedical Research(CLADIBIOR), Azienda Universitaria Ospedaliera Policlinico P. Giaccone, Palermo, Italy.
Paola Di CarloDepartment of Sciences for Health Promotion and Mother-Child Care "G. D'Alessandro", University of Palermo, Palermo, Italy.
Antonio CascioDepartment of Sciences for Health Promotion and Mother-Child Care "G. D'Alessandro", University of Palermo, Palermo, Italy.
Gilda CuzziTranslational Research Unit, National Institute for Infectious Diseases L. Spallanzani, Rome, Italy.
Fabrizio PalmieriTranslational Research Unit, National Institute for Infectious Diseases L. Spallanzani, Rome, Italy.
Delia GolettiTranslational Research Unit, National Institute for Infectious Diseases L. Spallanzani, Rome, Italy.
Nadia CaccamoCentral Laboratory of Advanced Diagnosis and Biomedical Research(CLADIBIOR), Azienda Universitaria Ospedaliera Policlinico P. Giaccone, Palermo, Italy.ORCID http://orcid.org/0000-0002-1018-5710
Azienda Ospedaliera Universitaria Policlinico "Paolo Giaccone" di Palermo · ITIstituto Nazionale per le Malattie Infettive Lazzaro Spallanzani · ITUniversity of Palermo · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) is one of the most important cause of morbidity and death among infectious diseases, and continuous efforts are needed to improve diagnostic tools and therapy. Previous published studies showed that the absolute cells number of monocytes or lymphocytes in peripheral blood or yet the ratio of monocytes to lymphocytes displayed the ability to predict the risk of active TB. In the present study we evaluated the ratio of monocytes to lymphocytes variation and we also analyzed the ex-vivo expression of CD64 on monocytes as tools to identify biomarkers for discriminating TB stages. Significant differences were found when the average ratio of monocytes to lymphocytes of active TB patients was compared with latent TB infection (LTBI) subjects, cured TB and healthy donors (HD). By the receiver operator characteristics (ROC) curve analysis the cut-off value of 0.285, allowed the discrimination of active TB from HD, with a sensitivity of 91.04% and a specificity of 93.55% (95% of confidence interval: 0.92-0.99). The ROC curve analysis comparing TB patients and LTBI groups, led to a sensitivity and the specificity of the assay of 85.07% and 85.71%, respectively (95% of confidence interval: 0.85 to 0.96). The upregulation of CD64 expression on circulating monocytes in active TB patients could represent an additional biomarker for diagnosis of active TB. In conclusion, we found that the ML ratio or monocyte absolute count or phenotypic measures show predictive value for active TB.

Indexed as

AdolescentAdultAgedAged, 80 and overBiomarkersCase-Control StudiesFemaleHumansMaleMiddle AgedMonocytesMycobacterium tuberculosisPhenotypeTuberculosisYoung AdultBiomarkers

Identifiers

PMID28208160
PMCPMC5313257
OpenAlexW2589099144

What OpenQuestion holds

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LicenceCC BY
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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.