Pentoxifylline vs Placebo or no active treatment: Maximal mouth opening (interincisal distance)
- Population
- People of any age with a confirmed diagnosis, by clinical examination and biopsy, of oral submucous fibrosis (OSF)
- Intervention
- Pentoxifylline
- Comparison
- Placebo or no active treatment
- Outcome
- Maximal mouth opening (interincisal distance)
It is very uncertain whether pentoxifylline changes maximal mouth opening (interincisal distance) compared with placebo or no active treatment (very low certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Pentoxifylline vs Placebo or no active treatment Maximal mouth opening (interincisal distance) · People of any age with a confirmed diagnosis, by clinical examination and biopsy, of oral submucous fibrosis (OSF) · 3 to 6 months It is very uncertain whether pentoxifylline changes maximal mouth opening (interincisal distance) compared with placebo or no active treatment (very low certainty). Interventions for managing oral submucous fibrosis (2024) · Cochrane All outcomes | MD -0.15 [-5.04, 4.74] | 2 studies · 136 participants | Very low |
Pentoxifylline vs Placebo or no active treatment Maximal mouth opening (interincisal distance) · People of any age with a confirmed diagnosis, by clinical examination and biopsy, of oral submucous fibrosis (OSF) · Less than 3 months Pentoxifylline may leads to higher maximal mouth opening (interincisal distance) compared with placebo or no active treatment (low certainty). Interventions for managing oral submucous fibrosis (2024) · Cochrane All outcomes | MD 1.80 [1.02, 2.58] | 1 study · 106 participants | Low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Interventions for managing oral submucous fibrosis 2024 · Cochrane All outcomes | 2022-09 | Not listed | Not assessed |
Related questions
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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.