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Record W2158520906 · doi:10.1002/cpdd.189

Effect of lapatinib on oral digoxin absorption in patients

2015· article· en· W2158520906 on OpenAlexaff
Kevin M. Koch, Deborah A. Smith, Jeff Botbyl, Nikita Arya, Linda P. Briley, Leanne Cartee, Jane Holshouser White, J. Beyer, Mohammed M. Dar, Hyun Choel Chung, Quincy S. Chu, Yung‐Jue Bang

Bibliographic record

VenueClinical Pharmacology in Drug Development · 2015
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsAlberta Cancer Foundation
FundersGlaxoSmithKline
KeywordsLapatinibDigoxinMedicinePharmacokineticsPharmacologyTherapeutic indexOral administrationDrug interactionMetastatic breast cancerAbsorption (acoustics)ConcomitantBreast cancerDrugInternal medicineCancerTrastuzumabHeart failure

Abstract

fetched live from OpenAlex

The potential for an interaction between lapatinib and absorption of the P-glycoprotein (ABCB1) substrate digoxin at a therapeutic dose in breast cancer patients was characterized. Seventeen women with HER2-positive metastatic breast cancer received a single oral 0.5-mg dose of digoxin on days 1 and 9 and oral lapatinib 1500 mg once daily on days 2 through 9. Digoxin pharmacokinetic parameters were determined on day 1 (digoxin administration alone) and on day 9 (coadministration of lapatinib and digoxin), and parameters were compared to determine the effects of lapatinib on digoxin absorption. Concomitant medications that could affect ABCB1 were accounted for. Lapatinib 1500 mg/day increased digoxin absorption approximately 80%, implicating lapatinib inhibition of intestinal ABCB1-mediated efflux. In summary, coadministration of lapatinib with narrow therapeutic index drugs that are substrates of ABCB1 should be undertaken with caution and dose adjustment should be considered.

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)0.002
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 score0.038
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
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 head0.039
GPT teacher head0.394
Teacher spread0.355 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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