A LOGISTIC-REGRESSION MODEL FOR THE DECISION TO PERFORM ACCESS SURGERY

Access surgery may be recommended to about 80% of patients who present with advanced forms of periodontal disease. In this report, a multiva riate logistic regression analysis which incorporated several clinical parameters for each tooth examined, i.e., tooth type, furcation invol vement, bleeding on probing, attachment level, probing depth, mobility and BANA test score, was conducted using generalized estimating equat ions (GEE). This approach identified parameters that were significantl y associated at p<0.05 level with the need for access surgery or extra ction for periodontal purposes. The estimated probabilities derived fr om the GEE model were plotted over the complete spectrum of operating conditions to obtain a receiver-operator characteristic (ROC) curve. A t a probability cutpoint of 0.8, the decision threshold for surgery/ex traction at the pretreatment examination would have a sensitivity of 7 6.1% and a specificity of 75.3%. We have taken this 0.8 cut point to l ook at specific clinical decisions made by our examiners after the pat ients had received scaling and root planing plus 2 weeks unsupervised usage of systemic antimicrobials. The clinicians' decision was taken a s the primary reference standard. The model's estimated decision agree d with the clinicians' decision in 226 of the 284 teeth, for an accura cy of 80%. The specificity was 90% and the sensitivity was 43%.