2021
DOI: 10.3390/jpm11121303
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Predictors of Efavirenz Plasma Exposure, Auto-Induction Profile, and Effect of Pharmacogenetic Variations among HIV-Infected Children in Ethiopia: A Prospective Cohort Study

Abstract: (1) Background: Efavirenz plasma concentration displays wide between-patient variability partly due to pharmacogenetic variation and autoinduction. Pediatric data on efavirenz pharmacokinetics and the relevance of pharmacogenetic variation are scarce, particularly from sub-Saharan Africa, where >90% of HIV-infected children live and population genetic diversity is extensive. We prospectively investigated the short- and long-term effects of efavirenz auto-induction on plasma drug exposure and the influence o… Show more

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Cited by 8 publications
(9 citation statements)
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References 43 publications
(63 reference statements)
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“…We also showed that cases had significantly elevated HOMA-IR, FSG, FSI, and TG levels than controls, indicating the presence of GMDs. The overall observed genotype and allele frequency proportions were similar to the findings of previous studies from Ethiopia [ 29 , 30 ].…”
Section: Discussionsupporting
confidence: 89%
“…We also showed that cases had significantly elevated HOMA-IR, FSG, FSI, and TG levels than controls, indicating the presence of GMDs. The overall observed genotype and allele frequency proportions were similar to the findings of previous studies from Ethiopia [ 29 , 30 ].…”
Section: Discussionsupporting
confidence: 89%
“…In contrast to the CYP2B6 polymorphisms, the selected ABCB1 SNP (rs3842, c.4036A > G), had no significant influence on [EFV] or [8‐OH‐EFV]. Previous studies in African and European HIV cohorts reported both higher 8,9,11–13 and lower [EFV] 10 in carriers of the minor rs3842 G allele.…”
Section: Discussionmentioning
confidence: 81%
“…OH-EFV]. Previous studies in African and European HIV cohorts reported both higher8,9,[11][12][13] and lower [EFV] 10 in carriers of the minor rs3842 G allele.Regression analysis for predictors of [EFV] and [8-OH-EFV]/[EFV] interindividual variation excluded the ABCB1 rs3842 SNP, demographic parameters and comedications as explanatory variables, retaining only CYP2B6 rs3745274 and rs28399499 genotypes or inferred CYP2B6 metabolic phenotypes in the final models. Since inference of CYP2B6 phenotypes was based on the combined CYP2B6 genotypes, regression models including either CYP2B6 genotypes or phenotypes, had similar predictive power, accounting for 48 and 35% of the interindividual variability of [EFV] and [8-OH-EFV]/[EFV], respectively.…”
mentioning
confidence: 93%
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