Question · asked by 1 review
Dental caries (carious oral microbiome) vs Caries-free / healthy oral microbiome: Differential microbial abundance / taxa predictive of caries
- Population
- Individuals providing oral (saliva/supragingival plaque) 16S rRNA microbiome samples; 2016 samples from 19 studies (mixed children and adults)
- Intervention
- Dental caries (carious oral microbiome)
- Comparison
- Caries-free / healthy oral microbiome
- Outcome
- Differential microbial abundance / taxa predictive of caries
A group of genera/species (notably Selenomonas, Aggregatibacter, Actinomyces, Treponema) was predictive of caries, whereas Streptococcus was not (ungraded).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Dental caries (carious oral microbiome) vs Caries-free / healthy oral microbiome Differential microbial abundance / taxa predictive of caries · Individuals providing oral (saliva/supragingival plaque) 16S rRNA microbiome samples; 2016 samples from 19 studies… · Oral cavity microbiome (saliva and supragingival plaque samples); pooled across 19 international studies A group of genera/species (notably Selenomonas, Aggregatibacter, Actinomyces, Treponema) was predictive of caries, whereas Streptococcus was not (ungraded). Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes. (2022) All outcomes | Mean-decrease-accuracy discriminating taxa: Capnocytophaga HMT-338, Lactobacillus panis, Treponema HMT-230, Bifidobacterium longum, Delftia acidovorans, Staphylococcus schleiferi; higher log2FC in caries: Selenomonas HMT-146, Aggregatibacter actinomycetemcomitans, Actinomyces HMT-896, Treponema HMT-257; Streptococcus not predictive | 19 studies · 2016 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes. 2022 All outcomes | Not specified (studies published from 2012 onward included; no explicit search date reported) | 16 | Not applicable |
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.