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Modelling changes in clinical attachment loss to classify periodontal disease progression
Author(s) -
Teles Ricardo,
Benecha Habtamu K.,
Preisser John S.,
Moss Kevin,
Starr Jacqueline R.,
Corby Patricia,
Genco Robert,
Garcia Nathalia,
Giannobile William V.,
Jared Heather,
Torresyap Gay,
Salazar Elida,
Moya Julie,
Howard Cynthia,
Schifferle Robert,
Falkner Karen L.,
Gillespie Jane,
Dixon Debra,
Cugini MaryAnn
Publication year - 2016
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/jcpe.12539
Subject(s) - clinical attachment loss , periodontitis , medicine , dentistry , longitudinal data , longitudinal study , periodontal disease , orthodontics , demography , pathology , sociology
Aim The goal of this study was to identify progressing periodontal sites by applying linear mixed models ( LMM ) to longitudinal measurements of clinical attachment loss ( CAL ). Methods Ninety‐three periodontally healthy and 236 periodontitis subjects had their CAL measured bi‐monthly for 12 months. The proportions of sites demonstrating increases in CAL from baseline above specified thresholds were calculated for each visit. The proportions of sites reversing from the progressing state were also computed. LMM were fitted for each tooth site and the predicted CAL levels used to categorize sites regarding progression or regression. The threshold for progression was established based on the model‐estimated error in predictions. Results Over 12 months, 21.2%, 2.8% and 0.3% of sites progressed, according to thresholds of 1, 2 and 3 mm of CAL increase. However, on average, 42.0%, 64.4% and 77.7% of progressing sites for the different thresholds reversed in subsequent visits. Conversely, 97.1%, 76.9% and 23.1% of sites classified as progressing using LMM had observed CAL increases above 1, 2 and 3 mm after 12 months, whereas mean rates of reversal were 10.6%, 30.2% and 53.0% respectively. Conclusion LMM accounted for several sources of error in longitudinal CAL measurement, providing an improved method for classifying progressing sites.