Question · asked by 1 review

Fluoride-free nano-/micro-hydroxyapatite (nHA) dentifrice vs Control (regular fluoride) dentifrice: Caries lesion initiation/progression (ICDAS score, laser fluorescence/DIAGNOdent, photographic pixels, enamel acid resistance)

No meta-analysis was possible for the 5 in vivo RCTs (high heterogeneity); narratively nHA showed generally no significant difference versus fluoridated dentifrice, and the evidence was not graded (ungraded).

What each review found

Include earlier review versions
FindingEffectStudiesGRADE certainty
Fluoride-free nano-/micro-hydroxyapatite (nHA) dentifrice vs Fluoride-containing (fluoridated) dentifrice control
Caries lesion initiation/progression (ICDAS score, laser fluorescence/DIAGNOdent, photographic pixels, enamel acid resistance) · Patients (children and adults, age 3-40 years) with initial enamel caries lesions (non-orthodontic and orthodontic) · Median follow-up 6 months (range 6-12 months), In vivo (clinical); non-orthodontic and orthodontic patients
No meta-analysis was possible for the 5 in vivo RCTs (high heterogeneity); narratively nHA showed generally no significant difference versus fluoridated dentifrice, and the evidence was not graded (ungraded).
Efficacy of nano-hydroxyapatite on caries prevention-a systematic review and meta-analysis. (2022) All outcomes
No meta-analysis was performed for the in vivo studies owing to high heterogeneity (population, control group, outcomes, follow-up periods, risk of bias) and differing statistical designs (e.g., non-inferiority);…5 studies · 420 participantsGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Efficacy of nano-hydroxyapatite on caries prevention-a systematic review and meta-analysis.
2022 All outcomes
Databases searched up to 30 April 2021 (CENTRAL up to 30 Apr 2021; MEDLINE/PubMed 1946 to 30 Apr 2021; Ovid EMBASE 1947 to 30 Apr 2021)10Low / Critically Low

Studies behind the findings

The primary studies the full-text reviews tie to this outcome. Reviews with headline outcomes only do not list them here.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.