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A logistic regression model for the decision to perform access surgery
Author(s) -
Loesche Walter J.,
Taylor George,
Giordano James,
Hutchinson Rowland,
Ran Charles F.,
Chen YinMiao,
Schork M. Anthony
Publication year - 1997
Publication title -
journal of clinical periodontology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.456
H-Index - 151
eISSN - 1600-051X
pISSN - 0303-6979
DOI - 10.1111/j.1600-051x.1997.tb00487.x
Subject(s) - logistic regression , medicine , receiver operating characteristic , dentistry , statistics , confidence interval , orthodontics , mathematics
Access surgery may be recommended to about 80% of patients who present with advanced forms of periodontal disease. In this report, a multivariate logistic regression analysis which incorporated several clinical parameters for each tooth examined, i.e., tooth type, furcation involvement, bleeding on probing, attachment level, probing depth, mobility and BANA test score, was conducted using generalized estimating equations (GEE). This approach identified parameters that were significantly associated at p < 0.05 level with the need for access surgery or extraction for periodontal purposes. The estimated probabilities derived from the GEE model were plotted over the complete spectrum of operating conditions to obtain a receiver‐operator characteristic (ROC) curve. At a probability cutpoint of 0.8, the decision threshold for surgery/extraction at the pre‐treatment examination would have a sensitivity of 76.1% and a specificity of 75.3%. We have taken this 0.8 cut point to look at specific clinical decisions made by our examiners after the patients had received scaling and root planing plus 2 weeks unsupervised usage of systemic antimicrobials. The clinicians' decision was taken as the primary reference standard. The model's estimated decision agreed with the clinicians' decision in 226 of the 284 teeth, for an accuracy of 80%. The specificity was 90% and the sensitivity was 43%.