Prevalence of oral submucous fibrosis across diverse populations: a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose: The aim is to offer a comprehensive overview of oral submucous fibrosis (OSF) prevalence and explore its epidemiological characteristics across various demographic groups and geographical locations, thereby helping the formulation of public health management policies. Methods: Studies reporting OSF prevalence were identified from electronic databases including the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE via PubMed, EMBASE via OVID, and Web of Science. Pooled prevalence and quality assessment using the New-Ottawa Scale were conducted. Two reviewers screened and selected records, assessed quality, and independently extracted data. This systematic review and meta-analysis followed the PRISMA guidelines and was registered on PROSPERO (CRD42024532975). Results: Sixty-three studies, encompassing 11,434 cases in a total population of 769,860, reported OSF prevalence. The majority of studies (forty-one) were from India. The pooled prevalence of OSF across all populations was 3.0% (95% CI [2.8-3.2]%). In non-risk populations, risk populations, and consecutive dental patients, the pooled prevalence stood at 2.4% (95% CI [2.1-2.6]%), 4.5% (95% CI 3.5-5.6%), and 5.6% (95% CI [3.8-7.5]%), respectively. Subgroup analysis by age, sex, and geographical region revealed higher prevalence rates among those aged 50 and above (4.2%, 95% CI [3.0-5.4]%), males (3.3%, 95% CI [2.9-3.7]%), and in India (4.0%, 95% CI [3.7-4.3]%). As the exposure to risk factors exceeded 50% in the surveyed population, the prevalence of OSF notably increased. Most studies met satisfactory quality standards. Conclusions: Our research findings reveal a comprehensive prevalence of OSF across all populations at 3.0% (95% CI [2.8-3.2]%). And, existing evidence indicates a relatively low prevalence of OSF associated with tobacco, alcohol, and Areca (betel) nut use. However, further large-scale studies are recommended to validate these findings. Understanding the prevalence and distribution patterns of OSF may assist in healthcare intervention planning and alleviate the oral cancer burden associated with OSF.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.043 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".