Bayesian Meta-Analysis with Application in Dental Studies
Sara Antonijevic (1), Danielle Sitalo (1), Brani Vidakovic (1) ((1) Texas A&M University)

TL;DR
This study applies Bayesian hierarchical modeling to synthesize clinical trial evidence, confirming fluoride varnish's effectiveness in reducing dental caries and demonstrating the robustness of Bayesian methods in meta-analysis.
Contribution
It introduces a Bayesian meta-analytic framework with multiple prior distributions, enhancing robustness and uncertainty quantification in dental intervention research.
Findings
Fluoride varnish reduces caries by approximately 43%.
Bayesian methods provide richer uncertainty estimates than classical approaches.
Results are consistent across diverse prior assumptions, indicating robustness.
Abstract
Dental caries remain a persistent global health challenge, and fluoride varnish is widely used as a preventive intervention. This study synthesizes evidence from multiple clinical trials to evaluate the effectiveness of fluoride varnish in reducing Decayed-Missing-Filled (DMF) surfaces. The principal measure of efficacy is the Prevented Fraction (PF), representing the proportional reduction in caries relative to untreated controls. A comprehensive meta-analysis was conducted using fixed-effect and random-effects models, complemented by hierarchical Bayesian inference. The Bayesian framework incorporated multiple prior distributions on between-study variance, including Pareto, half-normal, uniform, beta, and scaled chi-square forms, to assess robustness under alternative heterogeneity assumptions. Across all specifications, the pooled estimate indicated an approximate 43% reduction in…
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Taxonomy
TopicsDental Health and Care Utilization · Fluoride Effects and Removal · Dental Erosion and Treatment
