Tohoku J. Exp. Med., 2018 October, 246(2)

Simplified Prediction Model for Accurate Assessment of Dental Caries Risk among Participants Aged 10-18 Years


1Gachon University Graduate School of Public Health, Incheon, Republic of Korea
2Department of Dental Hygiene, Gachon University College of Health Science, Incheon, Republic of Korea
3Department of Preventive Medicine, Gachon University College of Medicine, Incheon, Republic of Korea

Dental caries assessment needs to be targeted at specific age groups, as many risk factors are related to patient age. Pre-teen and teenage patients, who are still at risk of occurrence of new carious lesions, need more individualized caries management strategies. Therefore, this study aimed to identify caries-related risk factors and develop a simplified risk prediction model for dental caries. Risk factors for caries were assessed in 171 participants aged 10-18 years, based on a questionnaire survey, previous history of caries, oral hygiene, microorganism colonization, saliva secretion, saliva buffer capacity examinations, and the acidogenicity of dental biofilms. These risk factors were entered into a computer-based risk assessment program (the Cariogram), and correlations between these factors and Cariogram scores were investigated. Significant risk predictors were used to develop a simplified risk prediction model. The performance of this model in predicting dental caries incidence was evaluated using receiver operating characteristic analysis, to determine its applicability to the management of caries. Our simplified prediction model included three predictors that were significantly associated with caries incidence: use of fluoride-containing toothpaste, the acidogenicity of dental biofilms, and saliva secretion (p < 0.001). The resulting model had a sensitivity and specificity of 60.5 and 85.0%, respectively, with a cut-off value of 69.41 as the threshold. The area under the curve of this model was 0.782 (95% confidence interval = 0.681-0.884, p < 0.001). Our new caries risk prediction model is expected to allow clinicians to accurately and easily predict patients' risk of occurrence of new caries.

Key words —— acidogenicity; caries risk assessment; dental biofilm; fluoride; saliva


Tohoku J. Exp. Med., 2018, 246, 81-86

Correspondence: Hee-Eun Kim, Department of Dental Hygiene, College of Health Science, Gachon University, 191 Hambangmoe-ro, Yeonsu-gu, Incheon 21936, Republic of Korea.