Biopsy for Suspicious Oral Lesions: A Review From the American Head and Neck Society‐Cancer Prevention Service
Bibliographic record
Abstract
BACKGROUND: Oral cancer is often preceded by a precursor lesion. This presents an opportunity for early diagnosis and intervention. Method of biopsy and interpretation are not well standardized and novel methods of analysis are now being investigated. METHODS: We conducted a narrative review of PubMed/MEDLINE (last search August 31, 2025), focusing on adult oral precancerous lesions evaluated in outpatient settings. RESULTS: Incisional punch biopsy is reproducible and often provides the diagnostic information needed. However, scalpel biopsy should be considered when initial biopsy is equivocal, depth of invasion is desired, or to minimize sampling bias. Limited studies show improved sensitivity of combining saliva and plasma sampling. Targeted fluorescent imaging may aid in future biopsy site selection. AI has shown encouraging results in both automated detection of dysplasia and prediction of malignant progression, achieving performance comparable to clinically validated grading systems. CONCLUSION: This update serves to further inform biopsy of oral suspicious lesions and provide a framework for future investigation.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".