Abstract
Background: Periodontitis is a prevalent oral disease with bone loss being it's hallmark. Clinical parameters used to measure periodontitis are retrospective and do not indicate active inflammation nor prognosis. GCF can be easily collected chairside and bone turnover biomarkers found in GCF can be evaluated to check for active inflammation and disease progression. This systematic review aims to evaluate the literature for association and predictive value of bone turnover biomarkers in GCF during periodontal disease.
Materials and Methods: This review was conducted and reported according to the PRISMA guidelines. The online databases Google Scholar and PubMed were used for data search. MeSH terms were used for PubMed search. All original studies from 1990 to 2017 conducted on human subjects in the English language were included in the review. Studies on non-human subjects, reviews and studies conducted in languages other than English were not considered. Reference lists of qualified articles were also searched.
Results: The search generated 2300 results whose titles were screened and 1571 articles were retreived. 23 articles were accepted in the review and full texts were accessed. These included 1 randomized controlled trial, 12 cross-sectional studies, five pre-post interventional studies, 4 longitudinal and 1 in-vitro in-vivo experimental study. The studies were conducted on patients of both genders ranging from 10 to 81 years in age. A total of 37 biomarkers were evalueted in the studies included in this review. Majority of the studies reported interleukin-1 beta (IL-1 beta) while receptor activated nuclear factor-kappa B ligand (RANKL) and matrix metalloproteinase-8 (MMP-8) were the other frequently reported biomarkers. Most of the studies evaluated more than two biomarkers. ELISA was the most commonly used biochemical test used for detection.
Conclusion: A wide range of biomarkers have been established as indicators of alveolar bone resorption. Few of the biomarkers have also shown positive correlation with disease progression and outcome of periodontal therapies thus underscoring their predictive value in periodontal diagnosis and prognosis. Not one single biomarker has been reported to have a predictive advantage over another and a combination of two or more biomarkers along with clinical evaluation is recommended.