Tariq S Ghazal1, Noel K Childers2, Steven M Levy3. 1. Dr. Ghazal is a pediatric dentist in private practice at the Rodeo Dental and Orthodontics, McAllen, Texas, USA;, Email: Tariq-ghazal@uiowa.edu. 2. Dr. Childers is an adjunct professor, Department of Pediatric Dentistry, School of Dentistry, University of Alabama at Birmingham, Birmingham, Ala., USA. 3. Dr. Levy is a professor, Department of Preventive and Community Dentistry, College of Dentistry, and Dr. Levy is a professor, Department of Epidemiology, College of Public Health, both at the University of Iowa, Iowa City, USA.
Abstract
Purpose: To assess permanent tooth caries incidence (ΔDMFS) among a cohort of African American children using the presence of any caries experience(decayed, missing, and filled surfaces-dmfs) in primary teeth and the presence of untreated primary tooth caries (ds) in two separate models. Methods: Data from a prospective study was used to apply two models with different clinical for predicting DMFS from ages six through 12 years. The first model used dmfs, and the second model used ds as predictors (both at age six years). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. Results: The first model resulted in sensitivity from 81.8 percent to 100 percent, specificity from 35.6 percent to 42.6, PPV from 5.8 percent to 38.1 percent, and NPV from 90.0 percent to 100 percent. In the second model, the predictive values were from 33.3 percent to 55.6 percent, 62.7 percent to 72.7 percent, 3.4 percent to 45.5 percent, and 80 percent to 95.9 percent, respectively. Conclusions: The proposed models for permanent tooth caries incidence prediction are easy, not time consuming, and clinically applicable; if validated, they have the potential to change the current paradigm for caries risk assessment.
Purpose: To assess permanent tooth caries incidence (ΔDMFS) among a cohort of African American children using the presence of any caries experience(decayed, missing, and filled surfaces-dmfs) in primary teeth and the presence of untreated primary tooth caries (ds) in two separate models. Methods: Data from a prospective study was used to apply two models with different clinical for predicting DMFS from ages six through 12 years. The first model used dmfs, and the second model used ds as predictors (both at age six years). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed. Results: The first model resulted in sensitivity from 81.8 percent to 100 percent, specificity from 35.6 percent to 42.6, PPV from 5.8 percent to 38.1 percent, and NPV from 90.0 percent to 100 percent. In the second model, the predictive values were from 33.3 percent to 55.6 percent, 62.7 percent to 72.7 percent, 3.4 percent to 45.5 percent, and 80 percent to 95.9 percent, respectively. Conclusions: The proposed models for permanent tooth caries incidence prediction are easy, not time consuming, and clinically applicable; if validated, they have the potential to change the current paradigm for caries risk assessment.
Authors: J Matejka; R Sinwell; P Cleaton-Jones; S Williams; J A Hargreaves; L P Fatti; M Docrat Journal: Int J Epidemiol Date: 1989-06 Impact factor: 7.196