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An economic evaluation of pit and fissure sealants and fluoride varnishes in preventing dental caries: a systematic review.

Bin ZhangMin ZhaoShaoying DuanJiangang TianLei LeiRuizhe Huang
Published in: The Journal of clinical pediatric dentistry (2023)
The aim was to systematically evaluate the cost-effectiveness of pit and fissure sealants (PFSs) compared with that of fluoride varnishes (FVs) in dental caries prevention. We searched four electronic databases including the Cochrane Oral Health Group's Trials Register (till 03 June 2022), Web of Science (from 1945 to 03 June 2022), PubMed (from 1996 to 03 June 2022), and EMBASE via Ovid (from 1980 to 03 June 2022) to identify the cost and effectiveness of PFSs and FVs in decreasing dental caries incidence. Two researchers independently screened search results, extracted data from the included studies, and conducted the risk of bias assessments. The main characteristics of the included studies were extracted and analyzed. The initial search produced 874 articles. After removing duplicates and full-text review, 19 studies were included. In this study: nine studies were on PFSs comparison with control; five on PFSs comparison with FVs; and five on FVs comparison with control. Regarding the type of economic evaluation (EE), 13 studies conducted cost-effectiveness analysis, five conducted cost-utility analyses, and one conducted both cost-effectiveness analysis and cost-utility analyses. The cost-effectiveness evaluation of PFSs and FVs in the available studies was limited. The prevalence of dental caries, payers' willingness to pay, length of follow-ups, delivery settings, retention rate of PFS, and application intervals of FV can affect the economic evaluation of these two methods for dental caries prevention. Therefore, more studies in the future are need to draw clear conclusions about which method is more cost-effective for the two preventive interventions in future.
Keyphrases
  • case control
  • risk factors
  • systematic review
  • public health
  • oral health
  • physical activity
  • big data
  • deep learning
  • current status