Effect of CYP3A5 Genotypes on the Pharmacokinetics of Carbamazepine when used as Monotherapy or Co-Administered with Phenytoin, Phenobarbital or Valproic Acid in Thai Patients
Bibliographic record
Abstract
PURPOSE: To determine the effects of CYP3A5 polymorphisms on carbamazepine (CBZ) pharmacokinetic parameters when CBZ is used either as monotherapy or co-administered with phenytoin (PHT), phenobarbital (PB) or valproic acid (VPA). METHODS: Retrospective data were collected from an electronic database and medical records. Blood samples were obtained and drug concentrations analyzed as a part of routine therapeutic drug monitoring (TDM). Screening for wild-type CYP3A5*1 and CYP3A5*3 single nucleotide polymorphism (rs776746) by allelic discrimination assay using real-time polymerase chain reaction technique (real-time PCR) was performed. Pharmacokinetic parameters of CBZ; clearance and dose-adjusted CBZ levels in patients with different genotypes were calculated and compared. RESULTS: Of the 70 patients assessed, 8 (11%) patients were homozygous CYP3A5*1/*1, 28 (40%) patients were heterozygous CYP3A5*1/*3, and 34 (49%) patients were homozygous CYP3A5*3/*3. The CBZ clearance and dose-adjusted CBZ levels did not significantly differ between patients with CYP3A5*1 and CYP3A5*3 alleles when CBZ was used as monotherapy. For patients who used CBZ in combination with an enzyme-inducing antiepileptic drug (AED: PHT or PB), individuals carrying the CYP3A5*1 allele (CYP3A5 expressers) showed a trend of having higher CBZ clearance and lower dose-adjusted CBZ level as compared to individuals carrying the CYP3A5*3 allele, even though no statistical significance was recorded. Nevertheless, it was observed that AEDs significantly increased CBZ clearance only in patients carrying the active CYP3A5*1 allele. CONCLUSIONS: When CBZ was used in combination with enzyme-inducing AED, CYP3A5 expressers yielded a trend toward greater susceptibility to change in CBZ clearance and showed lower dose-adjusted CBZ levels compared to CYP3A5 non-expressers. The dosage regimen should be adjusted accordingly to gain a better clinical outcome.This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".