The effect of genetic variations on ribavirin pharmacokinetics and treatment response in HCV-4 Egyptian patients receiving sofosbuvir/daclatasvir and ribavirin
Bibliographic record
Abstract
PURPOSE: This study aimed to investigate the effect of single nucleotide polymorphisms (SNPs) of genes involved in ribavirin (RBV) transport (SLC28A2 gene, ABCB1 gene and ABCB11 gene) on the clinical outcome and pharmacokinetics of ribavirin in HCV- 4 Egyptian patients. METHOD: 100 patients treated with sofosbuvir/daclatasvir and ribavirin for 12 weeks. The SNP genotyping was performed by real-time PCR using high resolution melting analysis. Ribavirin plasma trough concentrations were determined at week 4 of therapy using a liquid chromatography/tandem mass spectrometry (LC-MS/MS). For clinical outcomes, sustained virological response (SVR), liver function tests (ALT and AST), total bilirubin, albumin, serum creatinine, hemoglobin, leukocyte count, and platelet count were measured. RESULTS: levels after 4 weeks of therapy. ABCB11 1331 T > C SNP revealed significant association with clinical outcomes (SVR). SLC28A2-146 A > T SNP has not showed any statistically significant association with RBV plasma levels or response. CONCLUSION: SNP genotyping for ABCB1 and ABCB11 genes can help in better personalized medicine for maximizing response for ribavirin as explored by the significant association between polymorphism in ABCB1 and ABCB11 genes and ribavirin pharmacokinetics and the significant association of ABCB11 1331 T > C SNP with clinical response.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".