Evidence map›Paper›PMID 36852252›Full record

ReviewJournal of Taibah University Medical Sciences2023

Protein-based salivary biomarkers for the diagnosis of periodontal diseases: Systematic review and meta-analysis.

Esteban Arroyo, Mónica G Oliveira-Alves, Cintia M Chamorro-Petronacci, Xabier Marichalar-Mendia, Susana B Bravo-López, Juan Blanco-Carrión, Mario Pérez-Sayáns

Abstract readReview
In one paragraph

Review in Journal of Taibah University Medical Sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. High Salivary 3-Nitrotyrosine Levels in Periodontitis.Journal of clinical medicine · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Diagnostic Potential of Salivary Interleukin-1International journal of dentistry · 2024
    Article
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

7 authors.

Esteban ArroyoDepartment of Diagnosis and Surgery, Araraquara, School of Dentistry, Sao Paulo State University (Unesp), Araraquara, SP, Brazil.
Mónica G Oliveira-AlvesTechnology Research Center (NPT), Universidade Mogi das Cruzes, Mogi das Cruces, Brazil.
Cintia M Chamorro-PetronacciOral Medicine, Oral Surgery and Implantology Unit (MedOralRes), Faculty of Dentistry, University of Santiago de Compostela, Spain.
Xabier Marichalar-MendiaGrupo GIU21/042, Department of Nursing I, University of the Basque Country (UPV/EHU), Barrio Sarriena s/n, Leioa, Bizkaia, Spain.
Susana B Bravo-LópezProteomic Platform, Health Research Institute, Santiago de Compostela, A Coruña, Spain.
Juan Blanco-CarriónPeriodontology Unit, School of Medicine and Dentistry, University of Santiago de Compostela, Santiago de Compostela, Spain.
Mario Pérez-SayánsOral Medicine, Oral Surgery and Implantology Unit (MedOralRes), Faculty of Dentistry, University of Santiago de Compostela, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This systematic review and meta-analysis was aimed at determining differentially expressed protein-based biomarkers detectable in the saliva for the diagnosis of major periodontal diseases. Methods: A literature review was conducted through January 31, 2022. The methodological quality and risk of bias were assessed with the Newcastle-Ottawa scale for case-control studies. Heterogeneity among studies was analysed with the Q statistical test and the I Results: Of all protein-based biomarkers detected, 12 were suitable for meta-analysis: IL-1β, MIP-1α, albumin, TNF-α, ICTP, Ig-A, lactoferrin, MMP-8, IL-6, IL-8, IL-17 and PGE2. The salivary markers with high applicability were IL-1β for differentiating patients with chronic periodontal disease from patients with gingivitis with an OE = 73.5 pg/mL; ICTP for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 0.091 ng/mL; and PGE2 for differentiating patients with chronic periodontal disease from healthy control patients with an OE = 36.3 pg/mL. Conclusions: The biomarkers with the highest differential expression and the greatest potential for clinical applicability are IL-1β for differentiating periodontitis from gingivitis, and ICTP and PGE2 for differentiating periodontitis from healthy status.

Indexed as

BiomarkersGingivitisPeriodontal diseasesPeriodontitis

Identifiers

PMID36852252
PMCPMC9957757

What OpenQuestion holds

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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.