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Record W2157049259 · doi:10.3747/co.21.1661

Anticancer activity of combination targeted therapy using cetuximab plus vemurafenib for refractory BRAFV600E-mutant metastatic colorectal carcinoma

2013· article· en· W2157049259 on OpenAlexvenueno aff
K. Connolly, Daniel Brungs, E. Szeto, Richard J. Epstein

Bibliographic record

VenueCurrent Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsCetuximabMedicineVemurafenibKRASColorectal cancerTrametinibCancer researchDabrafenibTargeted therapyOncologyEpidermal growth factor receptorKinaseInternal medicineRefractory (planetary science)EGFR inhibitorsCancerMelanomaMAPK/ERK pathwayMetastatic melanomaBiology

Abstract

fetched live from OpenAlex

Mismatch-repair-deficient colorectal cancers often contain kinase-activating V600E BRAF mutations, but no clinical utility has yet been demonstrated in this setting for monotherapy using oral braf kinase inhibitors such as vemurafenib or dabrafenib. Recent studies have indicated that tumour resistance to braf inhibition is mediated by upregulated epidermal growth factor receptor (egfr) signalling, disruption of which is a routine treatment strategy in KRAS wild-type colorectal cancer. In this report, we describe the clinical course of a heavily pretreated patient who elected to receive off-label dual-targeted braf- and egfr-inhibitory therapy with good tolerance and apparent clinical benefit.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.169
GPT teacher head0.439
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations42
Published2013
Admission routes1
Has abstractyes

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