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Record W2028238072 · doi:10.1111/bcpt.12365

The Adverse Effects of Sorafenib in Patients with Advanced Cancers

2014· review· en· W2028238072 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBasic & Clinical Pharmacology & Toxicology · 2014
Typereview
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsMcGill University
FundersMcGill University Health CentreCapital Medical UniversityNational Natural Science Foundation of ChinaMcGill University
KeywordsSorafenibMedicineAdverse effectOncologyInternal medicineThyroid cancerCancerAngiogenesisTyrosine-kinase inhibitorPharmacologyHepatocellular carcinoma

Abstract

fetched live from OpenAlex

Sorafenib is the first multi-kinase inhibitor (TKI) approved for the treatment of advanced hepatocellular cancer (HCC) and metastatic renal cell cancer (RCC) and is increasingly being used to treat patients with well-differentiated radioiodine-resistant thyroid cancer (DTC). Sorafenib demonstrates targeted activity on several families of receptor and non-receptor tyrosine kinases that are involved in angiogenesis, tumour growth and metastatic progression of cancer. Sorafenib treatment results in long-term efficacy and low incidence of life-threatening toxicities. Although sorafenib has demonstrated many benefits in patients, the adverse effects cannot be ignored. The most common treatment-related toxicities include diarrhoea, fatigue, hand-foot skin reaction and hypertension. Most of these toxicities are considered mild to moderate and manageable to varying degrees; however, cardiovascular events might lead to death. In this MiniReview, we summarize the adverse effects of sorafenib that commonly occur in patients with advanced cancers.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.409
Teacher spread0.384 · 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