Over 4000 first and fifth grade children from the areas surrounding Aiken, South Carolina, and Portland, Maine, participated in a 4-yr study to develop caries risk assessment models. The predictors used at baseline included detailed clinical examinations, salivary microbiological tests, and sociodemographic and dental behavior data. Mean 3-yr caries increments in South Carolina were twice those in Maine. For the four risk assessment models (two grade cohorts at two sites) specificity values averaged 0.83 and sensitivity values averaged 0.60. Clinical predictors such as prior DMFS, pit and fissure morphology, and predicted caries risk status were the major contributors to the models.

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This article presents the rationale and content of a current study that seeks to improve methods to identify children at high risk to dental caries. It summarizes the results of the development of a 12-factor, preliminary caries prediction model based on data derived from the National Preventive Demonstration Program. Despite data limitations, the model produced a sensitivity of .5 and specificity of .8 for four-year caries increment prediction in first- and fifth-grade children. Data on a number of additional potential predictors are being collected in two sites to expand and improve the existing model. These factors are identified.

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The development and validation of a caries prediction model comprising 13 sociodemographic and dental examination variables on Grade 1 and Grade 5 children in the National Preventive Dentistry Demonstration Program are described. The objective was to derive a method of predicting children at high risk to caries early in order that preventive measures might be undertaken. True high risk children were defined in two ways: highest 25% of children based on their 4-yr DMFS increment, and their total DMFS score at the end of the study. In both cases, children predicted to be at high risk were defined as the 25% with the highest discriminant score. Discriminant function and logistic regression analyses were used to determine the extent to which the 13 variables collectively discriminated between true high risk and non-high risk children so defined. Sensitivity was approximately 0.50 and specificity around 0.82, using the 4-yr increment as the criterion for defining true high risk, and approximately 0.64 and 0.88, respectively, using the final DMFS score for defining true high risk.