A3 Refereed book chapter or chapter in a compilation book
Advances in periodontal healing biomarkers
Authors: Gürsoy, Ulvi Kahraman; Oikonomou, Ilias; Yilmaz, Mustafa; Gürsoy, Mervi
Editors: Makowski, Gregory S.
Publisher: Elsevier
Publication year: 2025
Journal: Advances in Clinical Chemistry
Book title : Advances in Clinical Chemistry: Volume 125
Journal name in source: Advances in Clinical Chemistry
Series title: Advances in Clinical Chemistry
Number in series: 125
Volume: 125
First page : 143
Last page: 167
ISBN: 978-0-443-41533-3
ISSN: 0065-2423
eISSN: 2162-9471
DOI: https://doi.org/10.1016/bs.acc.2024.11.007(external)
Web address : https://doi.org/10.1016/bs.acc.2024.11.007(external)
Abstract
Periodontitis is the infectious-inflammatory disease of tooth-supporting tissues. Periodontal treatment, either non-surgical or surgical, aims to remove infection, reduce inflammation, eliminate tissue loss, and gain clinical attachment. Clinical and radiographic recordings are widely used and accepted as gold-standard methods in periodontal diagnostics. While these traditional methods allow clinicians to monitor and diagnose periodontitis, they cannot be used to estimate the course of periodontal healing, or predict the disease recurrence or estimate the treatment outcome. Early prediction of the long-term consequences of periodontal treatment would be a crucial and valuable information not only for the clinicians, but also for the patients. Rapid advancements during past few decades boosted the periodontal biomarker studies and various microbe- or host-derived biochemical markers have been suggested as diagnostic biomarkers of periodontitis. Yet, there is no consensus regarding the accuracy of diagnostic biomarkers to monitor treatment response or to predict prognosis. The aim of this chapter will be to describe the healing patterns of periodontal tissues after treatment and present the available evidence on biomarkers that can indicate or predict successful treatment outcomes.
Periodontitis is the infectious-inflammatory disease of tooth-supporting tissues. Periodontal treatment, either non-surgical or surgical, aims to remove infection, reduce inflammation, eliminate tissue loss, and gain clinical attachment. Clinical and radiographic recordings are widely used and accepted as gold-standard methods in periodontal diagnostics. While these traditional methods allow clinicians to monitor and diagnose periodontitis, they cannot be used to estimate the course of periodontal healing, or predict the disease recurrence or estimate the treatment outcome. Early prediction of the long-term consequences of periodontal treatment would be a crucial and valuable information not only for the clinicians, but also for the patients. Rapid advancements during past few decades boosted the periodontal biomarker studies and various microbe- or host-derived biochemical markers have been suggested as diagnostic biomarkers of periodontitis. Yet, there is no consensus regarding the accuracy of diagnostic biomarkers to monitor treatment response or to predict prognosis. The aim of this chapter will be to describe the healing patterns of periodontal tissues after treatment and present the available evidence on biomarkers that can indicate or predict successful treatment outcomes.