HPV Associated Head and Neck Cancer
Bibliographic record
Abstract
Head and neck cancers (HNCs) are a highly heterogeneous group of tumours that are associated with diverse clinical outcomes. Recent evidence has demonstrated that human papillomavirus (HPV) is involved in up to 25% of HNCs; particularly in the oropharyngeal carcinoma (OPC) subtype where it can account for up to 60% of such cases. HPVs are double-stranded DNA viruses that infect epithelial cells; numerous HPV subtypes, including 16, 18, 31, 33, and 35, drive epithelial cell transformation and tumourigenesis. HPV positive (HPV+) HNC represents a distinct molecular and clinical entity from HPV negative (HPV-) disease; the biological basis for which remains to be fully elucidated. HPV positivity is strongly correlated with a significantly superior outcome; indicating that such tumours should have a distinct management approach. This review focuses on the recent scientific and clinical investigation of HPV+ HNC. In particular, we discuss the importance of molecular and clinical evidence for defining the role of HPV in HNC, and the clinical impact of HPV status as a biomarker for HNC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".