2 resultados para Trapezoidal rule
em University of Queensland eSpace - Australia
Resumo:
BACKGROUND: The development of hyperlipidemia after liver transplant is frequently treated with hydroxymethylglutaryl coenzyme A reductase inhibitors (statins) such as atorvastatin. As atorvastatin and the primary immunosuppressant drug, cyclosporine, are metabolized by the same pathway, there is the potential for an interaction. OBJECTIVE: To determine the effect of atorvastatin on cyclosporine pharmacokinetics in liver transplant recipients. METHODS: Six stable, long-term adult liver transplant recipients from a single center who developed posttransplant dyslipidemia were recruited to participate in a 14-day, open-label study of atorvastatin 10 mg/d coadministered with standard posttransplant immunosuppression using constant oral doses-of cyclosporine and corticosteroids. A 10-point pharmacokinetic profile was performed prior to and on day 14 after commencement of atorvastatin therapy. Cyclosporine concentrations were measured by HPLC-electrospray-tandem mass spectrometry. The AUC was calculated by the linear trapezoidal rule, with other parameters determined by visual inspection. RESULTS: Atorvastatin coadministration increased the cyclosporine AUC by 9% (range 0-20.6%; 3018 vs 3290 ng(.)h/mL; p = 0.04). No significant change was evident for other cyclosporine pharmacokinetic parameters. Total cholesterol and low-density lipoprotein cholesterol levels were significantly lower on day 14 than at baseline (p < 0.02). One patient developed a twofold increase in transaminases after 2 weeks of atorvastatin therapy, but no other clinical or biochemical adverse events were recorded. CONCLUSIONS: Atorvastatin coadministration increases the cyclosporine AUC by approximately 10% in stable liver transplant recipients. This change in systemic exposure to cyclosporine is of questionable clinical significance. Atorvastatin is effective in reducing cholesterol levels in liver transplant recipients.
Resumo:
The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).