Does Mouthwash Use Affect Oral Cancer Risk? A Comprehensive Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Studies indicate a strong correlation between the length and degree of alcohol and tobacco use and the risk of oral cancer (OC). However, there has been debate concerning the usage of mouthwashes and associated higher risk of OC for many years. The purpose of this study was to gain insight into how using mouthwash influenced the risk of OC. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was used when searching the PubMed/MEDLINE, Scopus, and Web of Science databases. Observational studies that addressed the relationship between mouthwash use and OC and involved adult or older adult populations were included. The Newcastle-Ottawa Scale was employed to check the methodological quality, and random effects meta-analysis, along with other subgroup analyses and meta-regression, were utilized to synthesize quantitative data. Out of 5,132 papers identified, 15 case-control studies comprising 6,515 cases and 17,037 controls were included in the review. Seventeen effect measures from these 15 studies were included in the meta-analysis. For individuals who used mouthwash three or more times a day, the pooled OR for OC was 1.00 (95% CI: 0.79-1.26; n = 17 studies). Among those who had used mouthwash for more than 40 years, the OR was 1.30 (95% CI: 1.58-4.82; p = 0.05; n = 2 studies). Some studies suggest that frequent mouthwash use may increase the risk of OC. Given the biological plausibility of this link, we exercise caution in interpreting these findings. It is important to note the limited research on the frequency and duration of mouthwash use. Thus, for the strengthening of the evidence for a possible dose-response effect of mouthwashes on OC risk, we suggest that future research should be focused on the frequency, duration, and substance of mouthwashes in depth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.046 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".