Malignant Transformation Rate of Oral Submucous Fibrosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Oral submucous fibrosis (OSF) is a chronic progressive condition affecting the oral cavity, oropharynx and upper third of the oesophagus. It is a potentially malignant disorder. The authors collated and analysed the existing literature to establish the overall malignant transformation rate (MTR). A retrospective analysis of medical and dental scientific literature using online indexed databases was conducted for the period 1956 to 2021. The quality of the enrolled studies was assessed by the Newcastle-Ottawa Scale (NOS). A meta-analysis using a random effects model of a single proportion was performed along with statistical tests for heterogeneity. The overall proportion of malignancy across all studies was 0.06 (95% CI, 0.02-0.10), indicating an overall 6% risk of malignant transformation across all studies and cohorts. Sub-group analyses revealed strong differences in proportion of malignancy according to ethnicity/cohort; Chinese = 0.02 (95% CI 0.01-0.02), Taiwanese = 0.06 (95% CI, 0.03-0.10), Indian = 0.08 (95% CI, 0.03-0.14) and Pakistani = 0.27 (95% CI 0.25-0.29). Overall, the MTR was 6%; however, wide heterogeneity of the included studies was noted. Geographic variations in MTR were noted but were not statistically significant. Further studies are required to analyse the difference between cohort groups.
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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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.033 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".