Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2020 Jan;47(1):2-18.
doi: 10.1111/jcpe.13202. Epub 2019 Nov 20.

Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta-analysis

Nora Arias-Bujanda  1 , Alba Regueira-Iglesias  1 , Carlos Balsa-Castro  1 , Luigi Nibali  2 , Nikos Donos  3 , Inmaculada Tomás  1
Affiliations
Meta-Analysis

Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta-analysis

Nora Arias-Bujanda et al. J Clin Periodontol. 2020 Jan.

Abstract

Aim: To analyse, using a meta-analytical approach, the diagnostic accuracy of single molecular biomarkers in saliva for the detection of periodontitis in systemically healthy subjects.

Materials and methods: Articles on molecular biomarkers in saliva providing a binary contingency table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. Searches for candidate articles were conducted in six electronic databases. The methodological quality was assessed through the tool Quality Assessment of Diagnostic Studies. Meta-analyses were performed using the Hierarchical Summary Receiver Operating Characteristic model.

Results: Meta-analysis was possible for 5 of the 32 biomarkers studied. The highest values of sensitivity for the diagnosis of periodontitis were obtained for IL1beta (78.7%), followed by MMP8 (72.5%), IL6 and haemoglobin (72.0% for both molecules); the lowest sensitivity value was for MMP9 (70.3%). In terms of specificity estimates, MMP9 had the best result (81.5%), followed by IL1beta (78.0%) and haemoglobin (75.2%); MMP8 had the lowest specificity (70.5%).

Conclusions: MMP8, MMP9, IL1beta, IL6 and Hb were salivary biomarkers with good capability to detect periodontitis in systemically healthy subjects. MMP8 and IL1beta are the most researched biomarkers in the field, both showing clinically fair effectiveness for the diagnosis of periodontitis.

Keywords: diagnostic accuracy; meta-analysis; molecular biomarkers; periodontitis; predictive values; prevalence; saliva; sensitivity; specificity; systematic review.

PubMed Disclaimer

References

REFERENCES

    1. Afacan, B., Öztürk, V. Ö., Emingil, G.,D Kose, T., & Bostanci, N. (2017). Alarm anti-protease Trappin-2 negatively correlates with proinflammatory cytokines in patients with periodontitis. Journal of Periodontology, 1-13, https://doi.org/10.1902/jop.2017.170245
    1. Alassiri, S., Parnanen, P., Rathnayake, N., Johannsen, G., Heikkinen, A.-M., Lazzara, R., … Sorsa, T. (2018). The ability of quantitative, specific, and sensitive point-of-care/chair-side oral fluid immunotests for aMMP-8 to detect periodontal and peri-implant diseases. Disease Markers, 2018(5), 1306396-1306405. https://doi.org/10.1155/2018/1306396
    1. AlMoharib, H. S., AlMubarak, A., AlRowis, R., Geevarghese, A., Preethanath, R. S., & Anil, S. (2014). Oral fluid based biomarkers in periodontal disease: Part 1. Saliva. Journal of International Oral Health, 6(4), 95-103.
    1. Al-Sabbagh, M., Alladah, A., Lin, Y., Kryscio, R. J., Thomas, M. V., Ebersole, J. L., & Miller, C. S. (2012). Bone remodeling-associated salivary biomarker MIP-1α distinguishes periodontal disease from health. Journal of Periodontal Research, 47(3), 389-395. https://doi.org/10.1111/j.1600-0765.2011.01445.x
    1. Al-Tarawneh, S. K., Border, M. B., Dibble, C. F., & Bencharit, S. (2011). Defining salivary biomarkers using mass spectrometry-based proteomics: A systematic review. Omics: A Journal of Integrative Biology, 15(6), 353-361. https://doi.org/10.1089/omi.2010.0134

Publication types

LinkOut - more resources