Emerging monoclonal antibody therapy for head and neck squamous cell carcinoma
Bibliographic record
Abstract
INTRODUCTION: The incidence of head and neck squamous cell carcinoma (HNSCC) is increasing, particularly among younger populations. It is projected that the number of new cases will increase by almost 50% by 2040, with market revenues expected to triple in the same period. Despite the recent introduction of immune checkpoint inhibitors (ICIs) into the therapeutic armamentarium, the vast majority of patients with recurrent and/or metastatic (R/M) HNSCC fail to derive durable benefits from systemic therapy. AREAS COVERED: This article aims to review the multiple monoclonal antibodies (mAbs) regimens currently under development, targeting various growth factors, immune checkpoints, immune costimulatory receptors, and more. EXPERT OPINION: So far, the combination of anti-EGFR and ICI appears to be the most promising, especially in HPV-negative patients. It will be interesting to confirm whether the arrival of antibody-drug conjugates and bispecific mAb can surpass the efficacy of anti-EGFR, as they are also being tested in combination with ICI. Furthermore, we believe that immune costimulatory agonists and various ICIs combination are worth monitoring, despite some initial setbacks.
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 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) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".