Calcium-based caries preventive agents: A meta-evaluation of systematic reviews and meta-analysis

Abstract

Objective: This article aims to assess systematic reviews and/or meta-analyses on calcium-based caries preventive agents, evaluating reported evidence, thereby summarizing a critical appraisal on the subject. Materials and methods: A systematic search was done using PubMed, Cochrane Library, and Web of Science. Systematic reviews and/or meta-analyses addressing PICO: P: any age or gender; I: calcium-based caries preventive agents; C: with/without control; and O: any early caries lesion measures were included. Inter-reviewer reliability was assessed using Cohen's kappa coefficient. Results: One hundred sixty-four records were identified, of which 10 (κ = 1.00) were included for quality evaluation. Seven reviews were systematic reviews (only), whereas 3 were meta-analyses. None of the articles provided with an “a priori” review design. Majority of the reviews (7 of 10) were of high quality as assessed by Assessing the Methodological Quality of Systematic Reviews, whereas 3 articles were scored as moderate quality of evidence. All the included meta-analyses were of high-quality evidence as assessed by meta-evaluation of meta-analysis: 10 appraisal questions for biologists. Eight reviews addressed the intervention: casein phosphopeptide-amorphous calcium phosphate (CPP-ACP)/casein phosphopeptide-amorphous calcium fluoride phosphate (CPP-ACFP). Two reviews were performed on arginine-containing formulations. Majority of the high-quality systematic reviews were inconclusive over the effects of CPP-ACP/CPP-ACFP. Conclusion: This meta-evaluation suggests that CPP-ACP/CPP-ACFP can be considered as an adjunct to fluorides but not as an alternative until long-term well-designed clinical trials assessed by systematic reviews and meta-analysis are available. Arginine-containing dentifrice with an insoluble calcium base and fluoride seem to be a promising agent, but more well-designed non-industry–supported clinical trials can provide better insights in future. © 2017 Elsevier Inc.