Microbial biomarkers as a predictor of periodontal treatment response: A systematic review

Abstract

To evaluate the prognostic accuracy of microbial biomarkers and their associations with the response to active periodontal treatment (APT) and supportive periodontal therapy (SPT). Microbial dysbiosis plays a crucial role in the disease processes of periodontitis. Biomarkers based on microbial composition may offer additional prognostic value, supplementing the limitations of current clinical parameters. While these microbial biomarkers have been clinically evaluated, there is a lack of consensus regarding their prognostic accuracy. A structured search strategy was applied to MEDLINE (PubMed), Cochrane Library, and Embase on 1/11/2022 to identify relevant publications. Prospective clinical studies involving either APT or SPT, with at least 3-month follow-up were included. There were no restrictions on the type of microbial compositional analysis. 1918 unique records were retrieved, and 13 studies (comprising 943 adult patients) were included. Heterogeneity of the studies precluded a meta-analysis, and none of the included studies had performed the sequence analysis of the periodontal microbiome. Seven and six studies reported on response to APT and SPT, respectively. The prognostic accuracy of the microbial biomarkers for APT and SPT was examined in only two and four studies, respectively. Microbial biomarkers had limited predictive accuracy for APT and inconsistent associations for different species across studies. For SPT, elevated abundance of periodontal pathogens at the start of SPT was predictive of subsequent periodontal progression. Similarly, persistent high pathogen loads were consistently associated with progressive periodontitis, defined as an increased pocket probing depth or clinical attachment loss. While there was insufficient evidence to support the clinical use of microbial biomarkers as prognostic tools for active periodontal treatment outcomes, biomarkers that quantify periodontal pathogen loads may offer prognostic value for predicting progressive periodontitis in the subsequent supportive periodontal therapy phase. Additional research will be required to translate information regarding subgingival biofilm composition and phenotype into clinically relevant prognostic tools.

Keywords: biomarkers; periodontitis; precision medicine; prognosis; treatment outcome.