Impact of Genetic Polymorphisms on Phenytoin Pharmacokinetics and Clinical Outcomes in the Middle East and North Africa Region
Bibliographic record
Abstract
BACKGROUND: Genetic polymorphisms are known to influence outcomes with phenytoin yet effects in the Middle East and North Africa region are poorly understood. OBJECTIVES: The objective of this systematic review was to evaluate the impact of genetic polymorphisms on phenytoin pharmacokinetics and clinical outcomes in populations originating from the Middle East and North Africa region, and to characterize genotypic and allelic frequencies within the region for genetic polymorphisms assessed. METHODS: MEDLINE (1946-3 May, 2017), EMBASE (1974-3 May, 2017), Pharmacogenomics Knowledge Base, and Public Health Genomics Knowledge Base online databases were searched. Studies were included if genotyping and analyses of phenytoin pharmacokinetics were performed in patients of the Middle East and North Africa region. Study quality was assessed using a National Institutes of Health assessment tool. A secondary search identified studies reporting genotypic and allelic frequencies of assessed genetic polymorphisms within the Middle East and North Africa region. RESULTS: Five studies met the inclusion criteria. CYP2C9, CYP2C19, and multidrug resistance protein 1 C3435T variants were evaluated. While CYP2C9*2 and *3 variants significantly reduced phenytoin metabolism, the impacts of CYP2C19*2 and *3 variants were unclear. The multidrug resistance protein 1 CC genotype was associated with drug-resistant epilepsy, but reported impacts on phenytoin pharmacokinetics were conflicting. Appreciable variability in minor allele frequencies existed both between and within countries of the Middle East and North Africa region. CONCLUSIONS: CYP2C9 decrease-of-function alleles altered phenytoin pharmacokinetics in patients originating from the Middle East and North Africa region. The impacts of CYP2C19 and multidrug resistance protein 1 C3435T variants on phenytoin pharmacokinetic and clinical outcomes are unclear and require further investigation. Future research should focus on the clinical outcomes associated with phenytoin therapy. PROSPERO 2017: CRD42017057850.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".