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Development and validation of a novel public prediction platform for deciduous caries in preschool children: an
Zhidong Zhang1,2, Zhihao Dou1,2, Xu Zhang3
1School (Hospital) of Stomatology, Lanzhou University, Lanzhou, China.
Insights
A new caries risk assessment model effectively screens preschool children for early childhood caries (ECC) in rural China. This accessible online platform aids community-level dental health management.
Area of Science:
- Public Health
- Pediatric Dentistry
- Health Informatics
Background:
- Early childhood caries (ECC) poses a significant global health challenge, requiring effective early screening methods.
- Underdeveloped regions, particularly in Northwest China, face unique barriers to managing ECC in preschool populations.
Purpose of the Study:
- To develop and validate a caries risk assessment (CRA) platform tailored for community preschool children in underdeveloped areas of Northwest China.
- To establish an accessible tool for early detection and management of ECC.
Main Methods:
- Data collection included clinical examinations and questionnaires from 3-5-year-old children across six regions in Gansu Province.
- Least Absolute Shrinkage and Selection Operator (LASSO) regression identified key predictive variables, followed by multivariate logistic regression for model construction.
- Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration, and clinical decision/impact analyses.
Main Results:
- The validated CRA model incorporates age, residence, infant feeding patterns, toothache history, and dental visit history.
- The model demonstrated excellent discriminatory performance with an Area Under the ROC Curve (AUC) of 0.804 and good predictive accuracy.
- An online prediction platform was developed for public accessibility and practical application.
Conclusions:
- The developed CRA model provides a novel public platform for screening and managing deciduous caries in community settings.
- This tool is particularly valuable for addressing ECC in underdeveloped regions of Northwest China.
- The platform facilitates community-level dental health management and early intervention for ECC.
Background:
Early childhood caries (ECC) is a major global public health concern, necessitating its early screening. This study aimed to establish a caries risk assessment (CRA) platform for managing caries in community preschool children in underdeveloped regions of Northwest China.
Methods:
We collected clinical examination and questionnaire data of children aged 3 to 5 years in six regions of Gansu Province. Then we selected variables using least absolute shrinkage and selection operator (LASSO) regression and constructed a CRA model utilizing multivariate logistic regression analyses. The predictive performance was assessed by the receiver operating characteristic (ROC), calibration, clinical decision and impact curves. The subgroup application was analyzed on the basis of the residence of children.
Results:
The CRA model included age, residence, feeding pattern within six months of birth, history of toothache, and history of dental visits as predictors. The Hosmer-Lemeshow test showed that the model fitting was acceptable (χ2 = 7.049, P = 0.531). And the model exhibited an excellent discriminatory performance in external cohort, as evidenced by the ROC curve parameters, with an area under the ROC curve (AUC) of 0.804 (95% CI: 0.765-0.844), sensitivity of 0.807, and specificity of 0.660. The calibration curves showed that the model exhibited good predictive accuracy, and the clinical decision and impact curves showed that the model was useful within reasonable threshold probabilities. Finally, we created an online prediction platform to ensure public use of the CRA model.
Conclusions:
The presented CRA model offers a novel public platform with the potential to serve as an effective tool for the screening and management of deciduous caries at the community level in underdeveloped regions of Northwest China.
