Assessing the Predictive Performance of Probabilistic Caries Risk Assessment Models: The Importance of Calibration

A mixed methods approach to obtaining health care provider feedback for the development of a Canadian pediatric dental caries risk assessment tool for children <6 years

Introduction

Early childhood caries (ECC) is a chronic but preventable disease affecting young children worldwide. Many young children face access to care barriers to early preventive dental visits for a variety of reasons, which can increase their risk for ECC. Non-dental primary health care providers are well positioned to assist in assessing a child's risk for ECC by performing caries risk assessment (CRA). The purpose of this project was to report on primary health care provider and stakeholder feedback in order to refine a drafted CRA tool for Canadian children &lt;6 years of age intended for use by non-dental primary health care providers.

Methods

In this mixed methods project, we conducted six focus groups with primarily non-dental primary health care providers followed by a short paper-based survey to quantify preferences and feedback. Data were thematically and descriptively analyzed.

Results

Participants’ feedback on the drafted CRA tool included the need for it to be relatively quick to complete, easy and practical to score, easy to implement into practitioners’ clinic schedules, and to include anticipatory guidance information to share with parents and caregivers. All participants (100%) welcomed a CRA tool. Many (85.4%) liked a layout that could be added to tools they already utilize. Most (73.2%) wanted the tool to be in colour, and many (90.2%) wanted the tool to include pictures.

Conclusion

Non-dental primary health care providers informed the final development and layout of the newly released Canadian CRA tool. Their feedback resulted in a user-friendly CRA tool with provider-patient dynamics and preferences.

Caries risk assessment using different Cariogram models. A comparative study about concordance in different populations—Adults and children

This methodological survey aimed to verify whether there is concordance among several Cariogram different risk models at different thresholds, comparing both children and adult populations and how each risk/protective factor weight on the overall caries risk profile. Three groups’ data (two in children and one in adults) were obtained from previous studies, while a fourth, in young adults, was ad hoc enrolled. Different caries risk levels were assessed: a) three risk categories with two different thresholds as: “low risk”  =  61–100% or 81–100% chance to avoid caries, “moderate risk”  =  41–60% or 21–80% and “high risk”  =  0–40% or 0–20%, named model 1 and 2; b) four risk categories with two different thresholds as: “low risk”  =  61–100% or 76–100%, “moderate/low risk” = 41–60% or 51–75%; “moderate/high risk” = 21–40% or 26–50% and “high risk” = 0–20% or 0–25%, model 3 and 4; c) five risk categories as: “very low risk”  =  81–100%; “low risk”  =  61–80% “moderate risk” = 41–60%; “high risk” = 21–40% and “very high risk” = 0–20%, model 5. Concordance of the different Cariogram risk categories among the four groups was calculated using Cohen’s kappa. The weight of the association between all Cariogram models toward the Cariogram risk variables was evaluated by ordinal logistic regression models. Considering Cariogram model 1 and 2, Cohen’s Kappa values ranged from 0.40 (SE = 0.07) for the young adult group to 0.71 (SE = 0.05) for the adult one. Cohen’s Kappa values ranged from 0.14 (SE = 0.03 p<0.01) for the adult group to 0.62 (SE = 0.02) for the two groups of children in models 3 and 4. Statistically significant associations were found for all Cariogram risk variables excepting Fluoride program in models 4 and 5 and the overall risk on children’s samples. Caries experience showed a quite variable weight in the different models in both adult groups. In the regression analyses, adult groups’ convergence was not always achievable since variations in associations between caries risk and different risk variables were narrower compared to other samples. Significant differences in caries risk stratification using different thresholds stands out from data analysis; consequently, risk assessments need to be carefully considered due to the risk of misleadingly choosing preventive and research actions.