Longitudinal follow-up over time (natural caries progression; no assigned intervention) vs Within-cohort change from baseline to follow-up (>=3 y): Caries incidence rate (first D3 lesion) per person-year at risk (permanent dentition)
In the permanent dentition, the pooled caries incidence rate was 0.11 per person-year at risk (95% CI 0.09 to 0.13; random-effects meta-analysis of 15 studies), i.e., about 11 of every 100 caries-free persons develop dentine caries each year (ungraded).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Longitudinal follow-up over time (natural caries progression; no assigned intervention) vs Within-cohort change from baseline to follow-up (>=3 y) Caries incidence rate (first D3 lesion) per person-year at risk (permanent dentition) · Children and adolescents (permanent dentition, D3, up to 21 y), Western or comparable populations · Per person-year at risk, Western Europe, North America, Australia, New Zealand (or comparable Western populations) In the permanent dentition, the pooled caries incidence rate was 0.11 per person-year at risk (95% CI 0.09 to 0.13; random-effects meta-analysis of 15 studies), i.e., about 11 of every 100 caries-free persons develop dentine caries each year (ungraded). Caries Progression Rates Revisited: A Systematic Review. (2019) All outcomes | Incidence rate (per person-year at risk) 0.11 [0.09, 0.13] | 15 studies · 10768 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Caries Progression Rates Revisited: A Systematic Review. 2019 All outcomes | 16 April 2018 | 43 | Not applicable |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
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.