Bleeding complications in patients with squamous cell carcinoma of the head and neck
Bibliographic record
Abstract
Hemorrhage in recurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) may be attributed to chemotherapy and local tumor irradiation. Evidence of the relationship between hemorrhage in R/M HNSCC and targeted therapies, including epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) inhibitors, or immune checkpoint inhibitors, is limited. We aimed to identify epidemiological and clinical data related to the occurrence of hemorrhage in R/M HNSCC and to explore its relationship with various therapies. We describe information obtained from literature searches as well as data extracted from a commercial database and a database from the author's institution (Istituto Nazionale dei Tumori of Milan). Evidence suggests that most bleeding events in R/M HNSCC are minor. Clinical trial safety data do not identify a causal association between hemorrhage and anti-EGFR agents or immune checkpoint inhibitors. In contrast, anti-VEGF agents are associated with increased, and often severe/fatal, hemorrhagic complications.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".