Epidermal Growth Factor Receptor Targeting in Head and Neck Cancer: Have We Been Just Skimming the Surface?
Bibliographic record
Abstract
Despite extensive research in squamous cell carcinoma of the head and neck (SCCHN), the epidermal growth factor receptor (EGFR) remains the only nonchemotherapeuticmolecular target that has been successfully translated into a biologic therapy with clinical benefit. Targeting this transmembrane tyrosine kinase growth factor receptor in SCCHN is an attractive and rational strategy given that more than 90 % of these tumors overexpress EGFR. The potential value of EGFR as a therapeutic target is also supported by the obser-vation that poor prognostic outcomes have been correlated with in-creased EGFR protein expression or EGFR gene copy number amplification.1-3 Traditional anti-EGFR strategies include monoclo-nal antibodies (MABs) that block the extracellular ligand-binding domain and small molecule inhibitors that reversibly inhibit activa-tion of the cytoplasmic tyrosine kinase. Currently, the only approved targeted therapy in SCCHN is cetuximab, the chimeric immunoglob-
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".