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Review
. 2025 Aug:52 Suppl 29:155-181.
doi: 10.1111/jcpe.14167. Epub 2025 Apr 19.

Host Markers of Periodontal Diseases: Meta-Analysis of Diagnostic Accuracy Studies

Mia Rakic  1   2 , Elena Calciolari  3   4 , Melissa M Grant  5   6   7 , Sandro Radovanovic  8 , Nagihan Bostanci  9 , Philip M Preshaw  10   11
Affiliations
Review

Host Markers of Periodontal Diseases: Meta-Analysis of Diagnostic Accuracy Studies

Mia Rakic et al. J Clin Periodontol. 2025 Aug.

Abstract

Objective: To identify host markers with optimal diagnostic performance for clinical implementation in the diagnosis of periodontal diseases and prediction of future disease progression and/or disease resolution.

Material and methods: Cross-sectional and prospective studies with ≥ 20 participants per group, reporting diagnostic accuracy (e.g., area under the curve [AUC]) of host markers for periodontal diagnosis (focused question 1 [FQ1]), periodontitis progression/relapse (FQ2) or resolution (FQ3) were searched in three electronic databases. Meta-analyses estimating diagnostic accuracy (DA) for individual host markers and for grouped salivary and gingival crevicular fluid (GCF) markers independently were performed whenever two or more studies were identified.

Results: Sixty-one eligible studies were identified, of which 13 were included in meta-analyses for FQ1 (discrimination between health and periodontitis). Matrix metalloproteinase-8 (MMP-8) was the most reported biomarker in both saliva and GCF, with comparable AUC (0.70-0.90), sensitivity (0.49-0.84) and specificity (0.62-0.79) in both sample types. Cytokines had good ability for discrimination of periodontitis/gingivitis versus health, although they were substantially less accurate for periodontitis versus gingivitis. Combinations of cytokines and MMPs tended to increase overall diagnostic accuracy but without significant improvement in the case of periodontitis/gingivitis discrimination. Bone markers were the best performing group of salivary markers (AUC = 0.91) when compared to cytokines (AUC = 0.86) and MMPs (AUC = 0.77). GCF microRNAs (MiRs) were a singly meta-analysed group of biomarkers demonstrating AUC = 0.79.

Conclusion: Reported studies on host periodontal markers exhibit serious limitations regarding clinical and validation standards, being the main cause for lack of progress in clinical implementation of biomarkers in periodontal classification. Disease-specific markers such as bone markers showed better diagnostic performance (from limited number of studies) for the diagnosis of periodontitis when compared to cytokines and MMPs.

Keywords: accuracy; biomarker; diagnosis; periodontitis.

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References

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    1. Abdullameer, M. A., and A. A. Abdulkareem. 2023b. “Salivary Interleukin‐1β as a Biomarker to Differentiate Between Periodontal Health, Gingivitis, and Periodontitis.” Minerva Dental and Oral Science 72: 221–229. https://doi.org/10.23736/S2724‐6329.23.04778‐2.
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    1. Afacan, B., V. O. Ozturk, G. Emingil, T. Kose, and N. Bostanci. 2018. “Alarm Anti‐Protease Trappin‐2 Negatively Correlates With Proinflammatory Cytokines in Patients With Periodontitis.” Journal of Periodontology 89: 58–66. https://doi.org/10.1902/jop.2017.170245.
    1. Afacan, B., V. O. Ozturk, G. Emingil, T. Kose, K. Mitsakakis, and N. Bostanci. 2022. “Salivary Secretory Leukocyte Protease Inhibitor Levels in Patients With Stage 3 Grade C Periodontitis: A Comparative Cross‐Sectional Study.” Scientific Reports 12: 21267. https://doi.org/10.1038/s41598‐022‐24295‐2.

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