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Effects of cross-linking agents on hydroxyproline release and root caries lesion size: Systematic review and network meta-analysis of in vitro studies

Monici Silva I, Barbosa CB, Cena JA, Ribeiro E, Garcia FCP, Stefani CM, Dame-Teixeira N

European journal of oral sciences, 2024

Abstract

A promising approach for managing root caries is the use of cross-linking agents to stabilize collagen. However, despite testing various natural and synthetic agents in vitro, their efficacy remains uncertain. The aim of this review was to examine which cross-linking agent performs better in reducing root caries lesion depth and the release of hydroxyproline, which is a marker of collagen degradation. Studies evaluating the impact of cross-linking agents on dentin were included, while studies performed on enamel surface/cell cultures and studies evaluating collagenase inhibitors were excluded, among others. A comprehensive search covered eight databases, and study quality was assessed using the QUINN Tool for in vitro dental studies. Synthesis of the results was done using a Bayesian network meta-analysis to compare agents. Fifty studies involving 31 cross-linking agents were included for qualitative synthesis. The network meta-analysis for lesion depth involved 284 samples across 36 comparisons and ranked cross-linking agents in terms of their caries lesion depth-reducing effect (from best to worst): naringin > quercetin > riboflavin > proanthocyanidins > hesperidin > glutaraldehyde > cranberry > grape seed extract > untreated controls. Only naringin, quercetin, proanthocyanidins, and glutaraldehyde showed statistically significant efficacy over untreated controls. Cranberry extract excelled in reducing hydroxyproline release, followed by proanthocyanidins. In conclusion,…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in cell cultures (in vitro), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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