80 resultados para TRANSPLANT RECIPIENTS
Resumo:
Aim To develop a population pharmacokinetic model for mycophenolic acid in adult kidney transplant recipients, quantifying average population pharmacokinetic parameter values, and between- and within-subject variability and to evaluate the influence of covariates on the pharmacokinetic variability. Methods Pharmacokinetic data for mycophenolic acid and covariate information were previously available from 22 patients who underwent kidney transplantation at the Princess Alexandra Hospital. All patients received mycophenolate mofetil 1 g orally twice daily. A total of 557 concentration-time points were available. Data were analysed using the first-order method in NONMEM (version 5 level 1.1) using the G77 FORTRAN compiler. Results The best base model was a two-compartment model with a lag time (apparent oral clearance was 271 h(-1), and apparent volume of the central compartment 981). There was visual evidence of complex absorption and time-dependent clearance processes, but they could not be successfully modelled in this study. Weight was investigated as a covariate, but no significant relationship was determined. Conclusions The complexity in determining the pharmacokinetics of mycophenolic acid is currently underestimated. More complex pharmacokinetic models, though not supported by the limited data collected for this study, may prove useful in the future. The large between-subject and between-occasion variability and the possibility of nonlinear processes associated with the pharmacokinetics of mycophenolic acid raise questions about the value of the use of therapeutic monitoring and limited sampling strategies.
Resumo:
Renal transplant recipients (RTRs) have elevated oxidative stress and a high incidence of cardiovascular morbidity and mortality. Although recent studies do not support the use of antioxidant supplements as a cardioprotectant in the general population, evidence suggests that RTRs may represent individuals that would benefit from this therapy. RTRs have elevated oxidative stress probably caused by the immunosuppressive therapy, and although only a small number of studies have examined the effects of antioxidant supplementation in these patients, most have reported beneficial findings. This review discusses these studies along with the rationale for the use of antioxidant supplements in RTRs and a call for more research to investigate this important topic.
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).
Resumo:
The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as greater than or equal to3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin less than or equal to 31 g/L), clinicians should consider monitoring the free MPA concentration.
Resumo:
Aim To explore relationships between sirolimus dosing, concentration and clinical outcomes. Methods Data were collected from 25 kidney transplant recipients (14 M/11 F), median 278 days after transplantation. Outcomes of interest were white blood cell (WBC) count, platelet (PLT) count, and haematocrit (HCT). A naive pooled data analysis was performed with outcomes dichotomized (Mann-Whitney U-tests). Results Several patients experienced at least one episode when WBC (n = 9), PLT (n = 12), or HCT (n = 21) fell below the lower limits of the normal range. WBC and HCT were significantly lower (P < 0.05) when sirolimus dose was greater than 10 mg day(-1), and sirolimus concentration greater than 12 mu g l(-1). No relationship was shown for PLT and dichotomized sirolimus dose or concentration. Conclusions Given this relationship between sirolimus concentration and effect, linked population pharmacokinetic-pharmacodynamic modelling using data from more renal transplant recipients should now be used to quantify the time course of these relationships to optimize dosing and minimize risk of these adverse outcomes.