COE with vital rinsing (toluidine blue/tolonium chloride) vs Conventional oral examination (COE) alone: Detection rate of oral pre-malignant and malignant lesions after referral (COE+vital rinsing vs COE alone)
- Population
- Oral cavity cancer or potentially malignant disorder symptom-free individuals with tobacco habits
- Intervention
- COE with vital rinsing (toluidine blue/tolonium chloride)
- Comparison
- Conventional oral examination (COE) alone
- Outcome
- Detection rate of oral pre-malignant and malignant lesions after referral (COE+vital rinsing vs COE alone)
COE with vital rinsing (toluidine blue/tolonium chloride) showed no clear difference in detection rate of oral pre-malignant and malignant lesions after… compared with conventional oral examination (COE) alone (moderate certainty).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
COE with vital rinsing (toluidine blue/tolonium chloride) vs Conventional oral examination (COE) alone Detection rate of oral pre-malignant and malignant lesions after referral (COE+vital rinsing vs COE alone) · OSCC or OPMD symptom-free individuals with tobacco habits COE with vital rinsing (toluidine blue/tolonium chloride) showed no clear difference in detection rate of oral pre-malignant and malignant lesions after… compared with conventional oral examination (COE) alone (moderate certainty). Clinical assessment for the detection of oral cavity cancer and potentially malignant disorders in… (2021) · Cochrane All outcomes | Rate ratio 1.05 [0.74, 1.41] | 1 study · 7975 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Clinical assessment for the detection of oral cavity cancer and potentially malignant disorders in apparently healthy adults 2021 · Cochrane All outcomes | 2020-10 | Not listed | Not assessed |
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.