Detection of periodontal probing change by analysis of distribution mean and skew

A problem associated with probing measurement is that important site‐specific change may be obscured by measurement variability. Furthermore, if many sites are monitored there is an increasing likelihood that any particular “detected change” might be the result of this measurement error. Since error and multiplicity effects would tend to increase mouth‐wise false positive rate, demanding decision thresholds are often set. However, imposition of difficult criteria, increases site‐wise false negative rate and therefore reduces utility in the clinical setting. Evaluation of mean change might sometimes be a useful alternative, but also problematic as a few dramatic site‐level losses can be inconsequential among many stable or improving sites. A strategy is proposed for evaluating probing changes in a single patient, which is based on the statistical evaluation of two attributes of the change distribution. (1) Disease progression is concluded when mean probing loss increases over time, and (2) a clinically relevant asymmetry is concluded when the distribution tail corresponding to loss is skewed. Computerized simulation was used to determine α‐error for tests of mean and skew, for three different distributions of probing change. Actual α‐error was shown to be near nominal levels. Power was estimated as a function of the number and magnitude of sites with probing loss and as a function of whether there was change in both mean and skew or in skew alone. Under most conditions studied, simultaneous tests for skew and mean provided enhanced power relative to a test for loss alone and would appear to offer the clinician an additional statistical context for appraising disease status.