CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention.

BACKGROUND: Cytochrome P450 2C19 (CYP2C19) intermediate and poor metabolizer patients exhibit diminished clopidogrel clinical effectiveness after percutaneous coronary intervention (PCI). However, outcome studies to date have lacked racial diversity. Thus, the impact of CYP2C19 genotype on cardiovascular outcomes in patients treated with clopidogrel who identify as Black or African American remains unclear. METHODS AND RESULTS: Adults among 5 institutions who self-identified as Black or African American, underwent PCI and clinical CYP2C19 genotyping, and were treated with clopidogrel were included. Data were abstracted from health records. Major atherothrombotic (composite of death, myocardial infarction, ischemic stroke, stent thrombosis, or revascularization for unstable angina) and bleeding event rates within 1 year after PCI were compared across CYP2C19 metabolizer groups using multivariable Cox regression adjusted for potential confounders and baseline variables meeting a threshold of P<0.10. The population included 567 Black patients treated with clopidogrel (median age, 62 years; 46% women; 70% with an acute coronary syndrome indication for PCI). Major atherothrombotic events rates were significantly higher among clopidogrel-treated intermediate and poor metabolizers (24 of 125 [19.2%]) versus patients treated with clopidogrel without a no function allele (43 of 442 [9.7%]; 35.1 versus 15.9 events per 100 person-years; adjusted hazard ratio, 2.00 [95% CI, 1.20-3.33], P=0.008). Bleeding event rates were low overall (23 of 567 [4.1%]) and did not differ among the metabolizer groups. CONCLUSIONS: Black patients with CYP2C19 intermediate and poor metabolizer phenotypes who are treated with clopidogrel exhibit increased risk of adverse cardiovascular outcomes after PCI in a real-world clinical setting. Bleeding outcomes should be interpreted cautiously. Prospective studies are needed to determine whether genotype-guided use of prasugrel or ticagrelor in intermediate and poor metabolizers improves outcomes in Black patients undergoing PCI.

Food-Drug Effects and Pediatric Drug Development Studies Submitted to the US Food and Drug Administration, 2012-2022.

Food effect (FE) studies characterize food-drug interactions that may alter the efficacy or safety of a drug, but these studies are not conducted in pediatric patients. Pediatric patients have substantial physiologic, anatomic, and dietary differences from adults, which may result in differences in their FE considerations. Therefore, the objective of this study was to identify oral drug products approved for use in pediatric patients aged <6 years with an FE observed in adults. Additional objectives were to summarize the therapeutic areas, pharmacokinetic effects, and labeling instructions that resulted from these studies. Publicly available data were searched for products studied in pediatric patients and approved for use by the United States Food and Drug Administration (FDA) from 2012 to 2022. Of the 102 oral drug products approved for use in patients aged <6 years, 43 recommended the consideration of food intake in the drug labeling. These included drug products recommended to be taken with food (n = 21, 49%) or without food (n = 14, 33%). Each of the 14 drug products recommended to be taken without food are approved for use in pediatric patients aged <2 years. The products approved for use in pediatric patients aged <2 years comprised the highest proportion with area under the plasma concentration-time curve extrapolated to infinity (AUCinf, n = 35, 75%) and maximum serum concentration (Cmax, n = 45, 80%) affected by food. Close monitoring is warranted during the postapproval period for products identified as having a significant FE in adults and that are approved for use in pediatric patients aged <6 years. Promising tools for predicting pediatric FE may include physiologically based pharmacokinetic absorption modeling.