Abstract
Background: There is a need for risk prediction tools in caries research. This investigation aimed to estimate and evaluate a risk score for prediction of dental caries. Materials and Methods: This case-cohort study included a random sample of 177 cases (with dental caries) and 220 controls (randomly sampled from the study population at baseline), followed for 3 years. The risk ratio (RR) for each potential predictor was estimated using a logistic regression model. The level of significance was 5%. Results: The risk model for dental caries included the predictors: “presence of bacterial plaque/calculus” (RR = 4.1), “restorations with more than 5 years” (RR = 2.3), “>8 teeth restored” (RR = 2.0), “history/active periodontitis” (RR = 1.7) and “presence of systemic condition” (RR = 1.4). The risk model discrimination (95% confidence interval) was 0.78 (0.73; 0.82) (p < 0.001, C-statistic). Patients were distributed into three risk groups based on the pre-analysis risk (54%): low risk (<half the pre-analysis risk; caries incidence = 6.8%), moderate risk (half-to-less than the pre-analysis risk; caries incidence = 20.4%) and high risk (≥the pre-analysis risk; caries incidence = 27%). Conclusions: The present study estimated a simple risk score for prediction of dental caries retrieved from a risk algorithm with good discrimination.
Highlights
Dental caries is the most prevalent disease worldwide
The negative impact of dental caries on quality of life is significant both in the short and long term, with edentulism in senior patients reaching as high as 26–50% in North America and 13–78% in Europe [1]
Dental caries are dependent on lifestyle and dietary factors [4,5], with diet and smoking suggested as potential risk factors in a recent consensus [5]
Summary
The negative impact of dental caries on quality of life is significant both in the short and long term, with edentulism in senior patients reaching as high as 26–50% in North America and 13–78% in Europe [1]. Considered a multifactorial disease, several variables were proposed as potential risk factors/indicators for dental caries, including the previous or current presence of caries, number of teeth present, or plaque index [6]. Results: The risk model for dental caries included the predictors: “presence of bacterial plaque/calculus” (RR = 4.1), “restorations with more than 5 years” (RR = 2.3), “>8 teeth restored” (RR = 2.0), “history/active periodontitis” (RR = 1.7) and “presence of systemic condition” (RR = 1.4). Conclusions: The present study estimated a simple risk score for prediction of dental caries retrieved from a risk algorithm with good discrimination
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