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Record W1983440297 · doi:10.1177/0091270010395940

Anti‐EGFR Monoclonal Antibodies for Treatment of Colorectal Cancers: Development of Cetuximab and Panitumumab

2011· review· en· W1983440297 on OpenAlexaff
Benoît You, Eric X. Chen

Bibliographic record

VenueThe Journal of Clinical Pharmacology · 2011
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsPanitumumabCetuximabMedicineBevacizumabColorectal cancerEpidermal growth factor receptorMonoclonal antibodyClinical trialOncologyInternal medicineAdjuvantEGFR inhibitorsPharmacologyCancerAntibodyImmunologyChemotherapy

Abstract

fetched live from OpenAlex

Over the last decade, anti-epidermal growth factor receptor (EGFR) monoclonal antibodies (mAbs) have been firmly established as essential drugs for the treatment of metastatic colorectal cancer (CRC). Cetuximab and panitumumab have been approved by American and European drug agencies. This review aims at exploring the main outcomes of clinical studies performed during their clinical development, from phase I to III trials, and hence at giving a comprehensive review of the scientific rational and up-to-date evidence sustaining the use of these drugs. Many areas are still under active investigation such as administration schedules, their efficacy in comparison with bevacizumab, their role in adjuvant therapy, molecular predictors, and management of side effects.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.266
GPT teacher head0.515
Teacher spread0.250 · 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 designNot applicable
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

Citations52
Published2011
Admission routes1
Has abstractyes

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