3.8 Article

Progression of chronic periodontitis can be predicted by the levels of Porphyromonas gingivalis and Treponema denticola in subgingival plaque

期刊

ORAL MICROBIOLOGY AND IMMUNOLOGY
卷 24, 期 6, 页码 469-477

出版社

WILEY
DOI: 10.1111/j.1399-302X.2009.00544.x

关键词

bacterial pathogens; biomarkers; chronic periodontitis; clinical study; real-time PCR

资金

  1. NHMRC [219189]

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Introduction: Chronic periodontitis is an inflammatory disease of the supporting tissues of the teeth associated with bacteria. Diagnosis is achieved retrospectively by clinical observation of attachment loss. Predicting disease progression would allow for targeted preventive therapy. The aim of this study was to monitor disease progression in patients on a maintenance program and determine the levels of specific bacteria in subgingival plaque samples and then examine the ability of the clinical parameters of disease and levels of specific bacteria in the plaque samples to predict disease progression. Methods: During a 12-month longitudinal study of 41 subjects, 25 sites in 21 subjects experienced disease progression indicated by at least 2 mm of clinical attachment loss. Real-time polymerase chain reaction was used to determine the levels of Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, Fusobacterium nucleatum, and Prevotella intermedia in subgingival plaque samples. Results: No clinical parameters were able to predict periodontal disease progression. In sites undergoing imminent periodontal disease progression within the next 3 months, significant partial correlations were found between P. gingivalis and T. forsythia (r = 0.55, P < 0.001) and T. denticola and T. forsythia (r = 0.43, P = 0.04). The odds of a site undergoing imminent periodontal disease progression increased with increasing levels of P. gingivalis and T. denticola. Conclusion: Monitoring the proportions of P. gingivalis and T. denticola in subgingival plaque has the potential to help identify sites at significant risk for progression of periodontitis, which would assist in the targeted treatment of disease.

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