Low etiologic fraction for high-risk human papillomavirus in oral cavity squamous cell carcinomas
Bibliographic record
Abstract
BACKGROUND: Human papillomavirus (HPV) is a cause of oropharyngeal cancer, but a role for HPV in the etiology of oral cavity squamous cell carcinomas (OCSCC) remains uncertain. METHODS: We sought to estimate the etiologic fraction for HPV among consecutive, incident OCSCC diagnosed from 2005 to 2011 at four North American hospitals. DNA and RNA purified from paraffin-embedded tumors were considered evaluable if positive for DNA and mRNA control genes by quantitative PCR. Fifteen high-risk (HR) HPV types were detected in tumors by consensus PCR followed by type-specific HR-HPV E6/7 oncogene expression by quantitative reverse-transcriptase PCR. P16 expression was evaluated by immunohistochemistry (IHC). A study of 400 cases allowed for precision to estimate an etiologic fraction of as low as 0% (97.5% confidence interval, 0-0.92%). RESULTS: Of 409 evaluable OCSCC, 24 (5.9%, 95%CI 3.6-8.2) were HR-HPV E6/7 expression positive; 3.7% (95%CI 1.8-5.5) for HPV16 and 2.2% (95%CI 0.8-3.6) for other HR-HPV types. HPV-positive tumors arose from throughout the oral cavity (floor of mouth [n=9], anterior tongue [6], alveolar process [4], hard palate [3], gingiva [1] and lip [1]) and were significantly associated with male gender, small tumor stage, poor tumor differentiation, and basaloid histopathology. P16 IHC had very good-to-excellent sensitivity (79.2%, 95%CI 57.9-92.9), specificity (93.0%, 95%CI 90.0-95.3), and negative-predictive value (98.6%, 95%CI 96.8-99.6), but poor positive-predictive value (41.3%, 95%CI 27.0-56.8) for HR-HPV E6/7 expression in OCSCC. CONCLUSION: The etiologic fraction for HR-HPV in OCSCC was 5.9%. p16 IHC had poor positive predictive value for detection of HPV in these cancers.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".