A Systematic Review of the Effect of CYP3A5 Genotype on the Apparent Oral Clearance of Tacrolimus in Renal Transplant Recipients
Bibliographic record
Abstract
Tacrolimus is a commonly used immunosuppressive agent in renal transplantation. Therapeutic drug monitoring of tacrolimus is recommended because it demonstrates wide pharmacokinetic interpatient variability. Part of that variability may be the result of metabolism by cytochrome P450 3A5 (CYP3A5), which is only expressed in some adult individuals. The expression of CYP3A5 has been linked to the CYP3A5 genotype, in which individuals with one or more wild-type allele (CYP3A5*1) are considered CYP3A5 expressors, and individuals homozygous for the mutant allele CYP3A5*3 are considered nonexpressors. An association has been established between CYP3A5 genotype (expressors versus nonexpressors) and tacrolimus dose requirements to achieve target concentrations. Tacrolimus pharmacokinetic variability is based on bioavailability and systemic clearance, which are represented by apparent oral clearance. The focus of this review was to use a systematic method to investigate whether the CYP3A5 genotype has an effect on the apparent oral clearance of tacrolimus in renal transplant recipients. A total of five studies were identified that reported apparent oral clearance in CYP3A5 expressors and CYP3A5 nonexpressors. The weighted mean apparent oral clearance was found to be 48% lower in CYP3A5 nonexpressors than CYP3A5 expressors (range, 26%-65%). This difference in apparent oral clearance could be used in future studies to guide initial dosing strategies of tacrolimus in renal transplant recipients based on genotype.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".