Prevalence of malignant neoplastic oral lesions among children and adolescents: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Malignant neoplasms that affect children and adolescents are predominantly embryonic and generally affect blood system cells and supporting tissues. AIM: This study aimed to summarize the scientific evidence about the prevalence of malignant lesions in the oral cavity of children and adolescents. DESIGN: In this systematic review and meta-analysis (PROSPERO CRD42020158338), data were obtained from seven databases and the gray literature. Cross-sectional observational studies on the prevalence of biopsied oral pediatric malignancies were included. The Newcastle-Ottawa Scale assessed the quality of the included studies, and the GRADE approach evaluated the evidence certainty. The meta-analysis prevalence was calculated using MedCalc® software, adopting a 95% confidence level (CI; random-effect model). RESULTS: Forty-two studies were included in the meta-analysis. Of the 64,522 biopsies, the prevalence of malignant lesions was 1.93% (n = 1,100; 95% CI = 1.21%-2.80%). Countries with a low socioeconomic profile showed the highest prevalence. The sample size did not influence the prevalence of oral malignancies, and unspecified lymphomas (12.08%; 95% CI = 5.73%-20.37%) and rhabdomyosarcoma (10.53%; 95% CI = 7.28%-14.30%) were the most common lesions. CONCLUSIONS: Oral malignant lesions biopsied in children and adolescents had a prevalence of <3%, and lymphomas and sarcomas were the most prevalent lesions.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.030 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".