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Record W3170583146 · doi:10.1002/hed.26772

Bleeding complications in patients with squamous cell carcinoma of the head and neck

2021· review· en· W3170583146 on OpenAlexaff
Cristiana Bergamini, Robert L. Ferris, Jing Xie, Gabriella Mariani, Muzammil Ali, William C. Holmes, Kevin J. Harrington, Amanda Psyrri, Stefano Cavalieri, Lisa Licitra

Bibliographic record

VenueHead & Neck · 2021
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsInstitute of Cancer Research
FundersAstraZeneca
KeywordsMedicineHead and neck squamous-cell carcinomaOncologyInternal medicineEpidermal growth factor receptorHead and neck cancerChemotherapyCancer

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.579
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.323
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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".

Quick stats

Citations21
Published2021
Admission routes1
Has abstractyes

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