MétaCan
Menu
Back to cohort

Metabolic Activation and Inactivation of Irinotecan when Combined with the Human Monoclonal Antibody Bevacizumab

2013· article· en· W2101957484 on OpenAlexvenueno aff
Martin Czejka, Andreas Kiss, Eva Ostermann, Johannes Schueller, Mansoor Ahmed, Najia Mansoor, Tasneem Ahmad

Bibliographic record

VenueJournal of Analytical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacokineticsIrinotecanMedicineBevacizumabPharmacologyMonoclonal antibodyRegimenChemotherapyDrug interactionInternal medicineColorectal cancerCancerAntibodyImmunology

Abstract

fetched live from OpenAlex

Purpose: This pharmacokinetic study was designed to investigate whether the co-administration of the monoclonal antibody bevacizumab (BVC) shows potential to modulate the plasma disposition of irinotecan (CPT-11) and its metabolites. Patients and Methods: Ten patients suffering from advanced colorectal cancer entered this pharmacokinetic study. Patients received CPT-11 as a 60 min i.v. - infusion (180 mg/m2, total dose 339 ± 32 mg) weekly for six weeks. BVC was administered biweekly as an intravenous 90 min infusion containing 5 mg BVC per kg body weight in 100 ml balanced sodium chloride solution. Pre-medication consisted of tropisetrone (3 mg i.v. push) and atropine (0.5 mg i.v.) one hour before CPT-11 infusion. Plasma samples were analysed during / after the first (MONO) and after the third CPT-11 infusion (BVC regimen). Results: BVC did not alter plasma disposition and pharmacokinetics of the parent compound CPT-11, but in contrary BVC appeared to lower the plasma concentrations of the metabolites SN-38, SN-38gluc and APC. Conclusion: Overall, our findings indicate that administration of BVC prior to chemotherapy showed no clinically significant impact on the pharmacokinetics and metabolic activation of CPT-11.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.336
Teacher spread0.313 · 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
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Analytical OncologySame topicColorectal Cancer Treatments and StudiesFrench-language works237,207