Molecular targeted therapies in all histologies of head and neck cancers: an update
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: This article reviewed the recent developments in molecular targeted therapy in head and neck cancers. A brief summary of other pathways of interest is also enclosed. RECENT FINDINGS: The use of cetuximab in squamous cell head and neck cancer is associated with clinical benefit and, in some cases, survival. However, the use of targeted agents beyond cetuximab in this disease remains investigational. Combination therapy of molecular targeted agents with chemoradiation in the locally advanced setting of head and neck squamous cell carcinomas and nasopharyngeal cancer shows early promising results, but at the expense of increased toxicity. In malignant salivary gland tumors, the evaluation of targeted therapy has been disappointing. New therapeutic targets warrant further evaluation in these cancers. SUMMARY: Despite the encouraging results achieved with antiepidermal growth factor receptor therapy, particularly with cetuximab, targeted therapy trials conducted in head and neck cancers to date have largely lacked efficacy or are associated with significant toxicity. Further research into modulation of other aberrant pathways is needed. The recent identification of improved prognosis among head and neck squamous cell carcinoma patients whose tumors harbor the human papilloma virus may allow better treatment selection for these patients, while the identification of a hallmark gene fusion transcript in adenocystic carcinoma may herald new treatment promise.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it