Systematic Review and Meta-analysis of Pharmacogenetic Allele and Genotype Frequencies in the Vietnamese Population Compared With Global Populations
Bibliographic record
Abstract
Background: Genetic variability plays a crucial role in drug metabolism, treatment response, and the risk of adverse drug reactions. Allele frequencies of pharmacogenetically relevant genes such as CYP2C19, CYP2D6, CYP2C9, CYP3A5, NAT2, SLCO1B1, UGT1A1, and ABCB1 vary significantly across populations. In Vietnam, existing studies remain scattered and limited in sample size, lacking a comprehensive synthesis. A systematic comparison between the Vietnamese population and major global populations is essential for precision medicine and rational drug policy development. Objectives: (1) To systematically collect and estimate allele and genotype frequencies of pharmacogenetically relevant genes in the Vietnamese population. (2) To compare allele/genotype distributions between Vietnamese and major global populations, including East Asian, South Asian, European, African, and Admixed American populations. (3) To generate pooled estimates and genetic distribution maps informing personalized medicine and drug regulatory policies. Methods: A systematic search will be conducted across PubMed, Embase, Scopus, Web of Science, Google Scholar, and Vietnamese national journals. Additional population data will be retrieved from the 1000 Genomes Project, gnomAD, and ALFA databases. Eligible study designs include cross-sectional, cohort, population genetic, and clinical studies reporting allele or genotype frequencies. Data extraction will include SNP identifiers, genotype counts (AA, Aa, aa), allele frequency, sample size, ethnic subgroup, and genotyping methods. Risk of bias will be assessed using a modified Newcastle–Ottawa Scale appropriate for genetic epidemiology. Meta-analysis of proportions will be performed using random-effects models (Freeman–Tukey transformation). Subgroup analyses will be stratified by gene, ethnic group (Kinh vs. minorities), and genomic dataset. Heterogeneity will be evaluated using I² and Q statistics. Expected Outcomes: This review will provide pooled allele and genotype frequencies for major pharmacogenes in Vietnam and comparative data across global populations. The findings will support clinical pharmacogenetics implementation, personalized dosing strategies, and national drug regulation policies. Registration Purpose: This protocol is preregistered on OSF to ensure transparency, prevent selective reporting, and strengthen methodological rigor prior to conducting data extraction and meta-analysis.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.001 | 0.026 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".