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Record W2059358140 · doi:10.1158/1538-7445.am2012-761

Abstract 761: Phase I interaction study of docetaxel with supplementation of St. John's wort

2012· article· en· W2059358140 on OpenAlexaboutno aff
Andrew K.L. Goey, Irma Meijerman, Hilde Rosing, Marianne Keessen, Jos H. Beijnen, Jan H.M. Schellens

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
Fundersnot available
KeywordsDocetaxelHyperforinHypericum perforatumPharmacokineticsPharmacologyMedicineCYP3A4MidazolamCancerInternal medicineMetabolismCytochrome P450

Abstract

fetched live from OpenAlex

Abstract Introduction St. John's wort (SJW, Hypericum perforatum) is a herbal antidepressant, which is often used by cancer patients. In healthy volunteers, SJW has previously been shown to induce hepatic CYP3A4 using the selective CYP3A4 substrate midazolam (Wang et al., 2001). In cancer patients, CYP3A4 induction by SJW could result in a decreased exposure to anticancer drugs metabolized by CYP3A4 (e.g. docetaxel), possibly resulting in a decreased therapeutic effect. Induction of docetaxel metabolism by the SJW constituent hyperforin has already been established in vitro (Komoroski et al., 2005). This pharmacokinetic interaction, however, has never been studied before in a clinical setting. Therefore, the aim of this study was to assess the effects of SJW on the pharmacokinetics of docetaxel in cancer patients. Methods In a one-sequence crossover study performed at the Netherlands Cancer Institute and approved by the Institute's Medical Ethical Committee, ten cancer patients received two cycles of docetaxel (135 mg, 60 min IV infusion). Seven days after cycle 1 (docetaxel alone), a commercial SJW extract in a recommended dose of one tablet (containing 300 mg SJW extract) three times daily was supplemented for fourteen days. After this supplementation period, cycle 2 of docetaxel was administered. During cycle 1 and cycle 2, blood samples were collected from 0-48 h after the start of the docetaxel infusion for pharmacokinetic analysis of docetaxel. Docetaxel plasma concentrations were determined by a validated LC-MS/MS assay (Kuppens et al., 2005). The pharmacokinetic endpoint for docetaxel was the area under the plasma concentration-time curve from time 0 to 48 h (AUC0-48), reflecting systemic exposure to docetaxel. By comparing the AUC0-48 of docetaxel in cycle 1 and 2, the effect of SJW on docetaxel pharmacokinetics was determined. Statistical analysis was performed with a paired Student's t test (α = 0.05). Differences in AUC0-48 between cycle 1 and 2 were considered clinically relevant if the 90% CI of the geometric mean ratio was not completely within no-effect limits of 0.80-1.25. Results (preliminary) In eight evaluable patients, supplementation of SJW decreased the mean docetaxel AUC0-48 from 2745 ± 650 to 2364 ± 483 ng/mL*h (p = 0.048, geometric mean ratio 0.86 (90% CI: 0.81-0.92)). Conclusion In this study, the observed decrease of docetaxel AUC0-48 after SJW administration was statistically significant, possibly even clinically relevant. This result indicates that concomitant use of the present SJW formulation in the recommended dose may decrease the therapeutic efficacy of docetaxel and presumably also other anticancer drugs primarily metabolized by CYP3A4. Acknowledgements This study was supported by the Dutch Cancer Society grant UU 2007-3795. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 761. doi:1538-7445.AM2012-761

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.202
GPT teacher head0.572
Teacher spread0.369 · 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".

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Citations1
Published2012
Admission routes1
Has abstractyes

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