Calcium Channel Blockers/blood ; Calcium Channel Blockers/pharmacokinetics* ; European Continental Ancestry Group ; Female ; Humans ; Male ; Metabolic Clearance Rate/genetics ; Nifedipine/blood ; Nifedipine/pharmacokinetics* ; Protein Binding ; Sex Factors
Abstract
OBJECTIVE:
To estimate oral clearance of nifedipine and to determine demographic and clinical covariates that affect nifedipine clearance in a clinical population.
METHODS:
Apparent oral clearance of nifedipine and protein binding were measured in 226 patients receiving sustained-release nifedipine formulations for hypertension and coronary artery disease (black men, n = 111; black women, n = 27; white men, n = 64; white women, n = 24). Mean age +/- SD was 71 +/- 11 years, and mean weight was 86 +/- 17 kg. Nifedipine concentrations were analyzed by HPLC, protein binding was measured by equilibrium dialysis, clearance and covariate effects were estimated by a nonlinear mixed effects population model, and statistical analyses were performed by a nonlinear mixed-effects model (clearance) and ANOVA (protein binding).
RESULTS:
Clearance was significantly slower in black subjects (8.9 +/- 0.7 mL/min/kg; mean +/- SE) compared with white subjects (11.6 +/- 0.8 mL/min/kg; P = .00004) and in men compared with women (9.3 +/- 0.6 versus 12.1 +/- 1.5 mL/min/kg; P = .0021). Reported alcohol use (alcohol, 8.6 +/- 1.1 versus no alcohol, 10.8 +/- 0.6 mL/min/kg; P = .0002) and smoking status (smoker, 8.8 +/- 2.0 versus nonsmoker, 10.2 +/- 0.6 mL/min/kg; P = .0362) also affected nifedipine clearance. Race and sex had no effect on protein binding of nifedipine (P = .29 and P = .44, respectively). No effects of age, stable coronary artery disease, or reported intake of beta-blockers on nifedipine clearance were detected in this primarily elderly population with hypertension.
CONCLUSIONS:
The data suggest that race, sex, and environmental factors are identifiable sources of interindividual variation in the oral clearance of nifedipine, a CYP3A substrate. Our experience also suggests that data from clinical populations may be biased with regard to age, sex, and formulation selection, and covariates may not be independently distributed, which can limit analyses.