Verification of high-risk patterns of allelic loss in prediction of cancer progression of primary oral premalignant lesions (OPLs) in a longitudinal study
Bibliographic record
Abstract
4471 In a previous retrospective study, we have shown that multiple allelic losses and specific patterns of allelic loss (loss of heterozygosity, LOH) were associated with markedly increased cancer risk for primary low-grade (mild/moderate) dysplasia. Lesions with LOH at 3p &/or 9p plus additional loss at 4q, 8p, 11q, 13q, or 17p had a ∼30-fold increase in risk of progression compared to morphologically similar low-grade lesions without such losses (Clin Cancer Res, 6:357, 2000; Editorial on the article: Clin Cancer Res, 6:321, 2000). The objective of this study was to verify the findings in a prospective longitudinal study. Method: This abstract describes interim LOH and outcome results from an ongoing prospective study of 200 consented patients with a history of biopsy-confirmed oral dysplasia being followed in Oral Dysplasia Clinics at the British Columbia Cancer Agency. The selection criteria for this study include (1) an oral biopsy (called target biopsy) had a histological diagnosis of low-grade dysplasia or no dysplasia; (2) the target biopsy had sufficient DNA for microsatellite analysis of LOH at loci on 7 chromosome arms (3p, 4q, 8p, 9p, 11q, 13q and 17p); and (3) the patient had at least 2 years follow up after the target biopsy. 102 patients fitted the criteria for this study. Results: Of the 104 OPLs with no or low-grade dysplasia, 28 progressed into either high-grade preinvasive lesions (severe dysplasia/carcinoma in situ, 12 lesions) or invasive cancer (16), and are called progressing lesions. Compared with the non-progressing lesions, the progressing lesions showed consistently higher rates of LOH at each of the 7 chromosome arms, and such increases were significant at 3p (54% vs. 28%, P = 0.0283), 9p (100% vs. 38%, P 1 arm lost (84% vs. 32%, P 2 arm lost (54% vs. 11%, P
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".