Commentary: clinical implications of periodontal disease assessments using probing depth and bleeding on probing to measure the status of the periodontal-biofilm interface.

Periodontal disease has traditionally been classified based upon history and clinical presentation, but considerable heterogeneity persists within each diagnostic category. Clinical signs have relatively weak sensitivity and specificity for predicting disease outcomes in treated and untreated individuals, suggesting the need for improved periodontal classifications, prognosis, and treatment strategies. Data from an epidemiologic study that included full-mouth clinical periodontal measurements from more than 6700 community-dwelling subjects were analyzed to identify heterogeneity in disease presentation. These analyses were used to create periodontal disease classifications based upon probing depths (PD) and bleeding on probing (BOP) scores. Two distinct disease classifications emerged: i.e. moderate periodontitis (MP) and severe periodontitis (SP). MP was defined as 1 or more sites with a PD of 4 mm or greater and BOP extent scores less than 50%, and SP was defined as 1 or more sites with a PD of 4 mm or greater and BOP extent scores of 50% or higher. These definitions were used to retrospectively analyze data from a pilot study designed to determine the clinical effects of scaling and root planing (SRP) treatment. Examiners evaluated 58 subjects for potential differences in treatment response comparing MP with SP subjects at baseline and 6 weeks after SRP treatment. Plaque scores were associated with greater extent of pocketing (extent PD > or =4 mm) in the MP group, but not in the SP group. Significant clinical improvement in PD and BOP was detected at 6 weeks in the SP group but not in the MP group when using the presented classification to retrospectively compare patient response to SRP treatment using a separate clinical data set. Periodontal disease is a heterogeneous condition, and classifications based upon BOP and PD may be useful considerations in predicting patient clinical response to therapy.