Journal Of Clinical Periodontology · 2020 · 13 citations · 32 references
DentistryPeriodonticsPeriodontologyOral ImmunologyPeriodontal BiologyPeriodontal MedicineMicrobiological AnalysisPeriodontal DiseasePeriodontal Disease Risk AssessmentPeriodontal InflammationPeriodontal PrognosisPeriodontal Status EvaluationClinical Attachment Level AssessmentClinical Attachment Level MonitoringClinical Periodontal AssessmentPorphyromonas Gingivalis In PlaquePorphyromonas SpeciesPrevotella IntermediaPrevotella SpeciesSalivary Immune Biomarkers
AIM: To explore the application of the combined use of baseline salivary biomarkers and clinical parameters in predicting the outcome of scaling and root planing (SRP). MATERIALS AND METHODS: Forty patients with advanced periodontitis were included. Baseline saliva samples were analysed for interleukin-1β (IL-1β), matrix metalloproteinase-8 and the loads of Porphyromonas gingivalis, Prevotella intermedia, Aggregatibacter actinomycetemcomitans and Tannerella forsythia. After SRP, pocket closure and further attachment loss at 6 months post-treatment were chosen as outcome variables. Models to predict the outcomes were established by generalized estimating equations. RESULTS: The combined use of baseline clinical attachment level (CAL), site location and IL-1β (area under the curve [AUC] = 0.764) better predicted pocket closure than probing depth (AUC = 0.672), CAL (AUC = 0.679), site location (AUC = 0.654) or IL-1β (AUC = 0.579) alone. The combination of site location, tooth loss, percentage of deep pockets, detection of A. actinomycetemcomitans and T. forsythia load (AUC = 0.842) better predicted further clinical attachment loss than site location (AUC = 0.715), tooth loss (AUC = 0.530), percentage of deep pockets (AUC = 0.659) or T. forsythia load (AUC = 0.647) alone. CONCLUSION: The combination of baseline salivary biomarkers and clinical parameters better predicted SRP outcomes than each alone. The current study indicates the possible usefulness of salivary biomarkers in addition to tooth-related parameters in predicting SRP outcomes.
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