Assessing the predictive performance of probabilistic caries risk assessment models: the importance of calibration
Probabilistic caries risk assessment models (P-CRA), such as the Cariogram, are promising tools to planning treatments in order to control and prevent caries. The usefulness of these models for informing patients and medical decision-making depends on 2 properties known as discrimination and calibration. Current common assessment of P-CRA models, however, ignores calibration, and this can be misleading. The aim of this paper was to provide tools for a proper assessment of calibration of the P-CRA models and improve calibration when lacking.