Clinical measurements of periodontitis

Abstract Clinical measurement of periodontitis has historically focused on the concept of periodontitis as a slow, continuous process which has emphasized measurements of the static condition of periodontal pockets. Observations based on longitudinal measurement of attachment loss in untreated subjects have indicated that periodontal destruction occurs in discrete episodes of short duration. Based on these studies, it has been suggested that chronic periodontal disease proceeds through a series of random episodic attacks. Periodontal sites are considered as existing in 2 states, either disease active or inactive. During periods of disease activity, sites increase in their probeable depth, whereas during the inactive state, no significant change in probing depth can be detected. The detection of changes at periodontal sites from time series data has been addressed by 3 analytical procedures: regression, running medians, and tolerance. The standard deviation of differences between replicate measurements of 48 , 064 sites for 56 subjects was 0.7727 mm. From this estimate, the computed standard deviation for a single measurement was 0.5464 mm and for the mean of 2 measurements was 0.386 mm. The expected error rates of each method have been estimated by computer simulation. The type‐I error for the regression ( p =0.028), running median ( p =0.000025), and tolerance ( p =0.00012) methods were all sufficiently low to consider it unlikely that reported observations could be accounted for by methodologic error. The estimated type‐II error for the regression ( p =0.446), running median p =0.152), and tolerance p =0.068) methods suggests that a substantial fraction of disease active sites was not detected by these methods. Several data set properties have been investigated. Intraclass correlation coefficients were computed from attachment level changes on 8 ,130 sites in 105 patients. By this analysis, 7% of the variation was associated with the subject and 93.3% with the individual sites, indicating that attachment level changes at periodontal sites exhibit a high degree of statistical independence. Autocorrelation within sequential attachment level measurements was computed and found low (0.081 in 22 subjects and 0.099 in 45 subjects), indicating that computed variance is not systematically underestimated due to autocorrelation within the data set. Clinical measurements which have failed to exhibit association with episodic attachment loss include gingival redness, bleeding on probing, suppuration, supragingival plaque, and darkfield microscopic bacterial counts. Clinical measurements which have been associated with episodic attachment loss include loss of alveolar crestal bone and the presence of specific bacterial species. In a study of treatment for rapidly advancing periodontitis, 97.3% of inactive sites failed to respond to therapy, whereas 37.3% of disease active sites gained 3 mm or more following Widman flap therapy with systemic tetracycline. This observation indicates that, in general, only disease active sites respond to treatment. Since inactive sites (95–97%) greatly outnumber active sites (3–5%), their inclusion in clinical trials serves to dilute the treatment response. Based on these findings, it seems desirable that clinical trials of the future be conducted on periodontal sites diagnosed as disease active. Detection of disease activity appears central to the clinical measurement of periodontitis. The use of radiographic methods to evaluate human clinical trials, although theoretically sound, has not yet been convincingly demonstrated. At this time, the only practical means to measure active disease is from differences between repeated attachment level measurements. Methodologic improvement in the measurement of attachment level and development of less complex detection systems are greatly needed. However, until these improvements become available and are adequately tested, clinical measurement of periodontitis will continue to place primary reliance on conventional attachment level measurements.