Question · asked by 1 review
Clear aligners (Invisalign / thermoformed aligners) vs Conventional orthodontic appliance treatment: Severity of white spot lesions (surface area and depth)
- Population
- Orthodontic patients undergoing comprehensive treatment (late mixed or permanent dentition, no active caries)
- Intervention
- Clear aligners (Invisalign / thermoformed aligners)
- Comparison
- Conventional orthodontic appliance treatment
- Outcome
- Severity of white spot lesions (surface area and depth)
White spot lesion severity was assessed narratively in a small number of studies and not meta-analyzed; evidence is limited (ungraded).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Clear aligners (CA) vs Conventional fixed orthodontic appliances (CF) Severity of white spot lesions (surface area and depth) · Orthodontic patients undergoing comprehensive treatment (late mixed or permanent dentition, no active caries) · Baseline to end of treatment (varying), University/hospital orthodontic clinics and private practice (multiple countries) White spot lesion severity was assessed narratively in a small number of studies and not meta-analyzed; evidence is limited (ungraded). White spot lesions, plaque accumulation and salivary caries-associated bacteria in clear aligners compared… (2023) All outcomes | Not meta-analyzed. 2 RCTs assessed WSL severity by lesion surface area (Albhaisi 2020 [12]; Alshatti 2017 [31]) and 1 (Albhaisi 2020 [12]) also by lesion depth; reported narratively with differing methods, generally… | 2 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| White spot lesions, plaque accumulation and salivary caries-associated bacteria in clear aligners compared to fixed orthodontic treatment.… 2023 All outcomes | May 2023 (searched January 2022 to May 2023; literature 1990-May 2023) | 14 | Critically Low / Low |
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.