Caries risk trajectories in a changing oral health landscape. A longitudinal study of orthodontic patients across four decades.

OBJECTIVES

This study aimed to characterise caries risk trajectories in orthodontic patients starting treatment from the late 1980s to the present and to evaluate whether the predictive value of risk factors for incident caries experience has changed across decades (≤1995, 1996-2005, 2006-2015, ≥2016).

MATERIALS AND

METHODS

Panoramic radiographs taken before treatment, at debonding, and at follow-up from 710 patients treated with Herbst appliances were analysed. Outcome variables included incident caries experience; predictor variables were age, sex, caries (D3/4), and missing/filled teeth (MFT). Analyses employed univariate logistic regression, multiple supervised machine learning models, and k-means clustering.

RESULTS

The proportion of patients presenting with caries at treatment start declined from 32.9 % in the earliest decade to 19.5 % in the most recent, accompanied by a significant reduction in incident caries during treatment (from 59.8 % to 27.4 %). Present caries and MFT consistently predicted incident caries experience, although their relative importance varied across decades. Machine learning models yielded moderate predictive accuracy, with performance differing over time. Unsupervised clustering identified distinct patient risk profiles that remained stable in character but shifted in prevalence across decades.

CONCLUSIONS

Both caries prevalence/incidence and the predictive value of present caries and MFT changed over time. Machine learning and clustering approaches provided refined insights into risk trajectories, emphasising the need for temporally adaptive models in preventive care.

CLINICAL SIGNIFICANCE: Despite overall declines, caries remains a relevant challenge in orthodontic patients. Identifying high-risk individuals in an era of a low overall caries prevalence requires vigilant, individualised monitoring.