Effect of atorvastatin on cyclosporine pharmacokinetics in liver transplant recipients

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.

Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

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).

Relationships of tacrolimus pharmacokinetic measures and adverse outcomes in stable adult liver transplant recipients

Alternative measures to trough concentrations [non-trough concentrations and limited area under the concentration-time curve (AUC)] have been shown to better predict tacrolimus AUC. The aim of this study was to determine if these are also better predictors of adverse outcomes in long term liver transplant recipients. The associations between tacrolimus trough concentrations (C-0), non-trough concentrations (C-1, C-2, C-4, C-6/8), and AUC(0-12) and the occurrence of hypertension, hyperkalaemia, hyperglycaemia and nephrotoxicity were assessed in 34 clinically stable liver transplant patients. The most common adverse outcome was hypertension, prevalence of 36%. Hyperkalaemia and hyperglycaemia had a prevalence of 21% and 13%, respectively. A sequential population pharmacokinetic/pharmacodynamic approach was implemented. No significant association between predicted C-0, C-1, C-2, C-4, C-6/8 or AUC(0-12) and adverse effects could be found. Tacrolimus concentrations and AUC measures were in the same range in patients with and without adverse effects. Measures reported to provide benefit, preventing graft rejection and minimizing acute adverse effects in the early post-transplant period, were not able to predict adverse effects in stable adult liver recipients whose trough concentrations were maintained in the notional target range.

Toward better outcomes with tacrolimus therapy: Population pharmacokinetics and individualized dosage prediction in adult liver transplantation

Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.

Liver transplantation for HCV-associated liver cirrhosis: Predictors of outcomes in a population with significant genotype 3 and 4 distribution

End-stage liver disease associated with hepatitis C virus (HCV) infection is now the leading indication for liver transplantation in adults. However, reinfection of the graft is universal. We aimed to determine predictors of outcome of HCV-Iiver transplant recipients in the Australian and New Zealand communities. The following variables were analysed: demographic factors, coexistent pathology at the time of transplantation, HCV genotype, and donor age. Outcomes measures were: 1. mortality; 2. development of HCV-related complications, which were stage 3 or 4 fibrosis, or mortality from HCV-related graft failure, or both. Between January 1989 and December 30, 1999, 182 patients were transplanted for HCV-associated cirrhosis. The median follow-up period was 4 years (range, 0 to 13 years). Genotype data were available on 157 patients. The distribution of genotypes among the 157 patients was as follows: 36 (23%) genotype la, 30 (19%) genotype 1b, 4 (9%) genotype 1, 17 (11%) genotype 2, 41 (26%) genotype 3a, and 16 (10%) genotype 4. Eight (5%) patients were HCV-polymerase chain reaction (PCR)-negative (but HCV-antibody positive). Donor age and genotype 4 were associated with an increased risk of retransplantation or death (P < .001 and.05, respectively). Meanwhile, donor age, genotype 4, and pretransplant excess alcohol were risk factors for the development of HCV-related complications (P = .004, .008, and .02, respectively). In contrast, patients with genotype 3a were less likely to develop HCV-related complications (P = .05). In a population of HCV liver transplant recipients with a heterogeneous genotype distribution, donor age, and genotype 4, were predictors of a worse outcome, whereas genotype 3 was associated with a more favorable outcome.

Increased mononuclear cell activation and apoptosis early after human liver transplantation is associated with a reduced frequency of acute rejection

Experimental models of orthotopic liver transplantation (OLT) have shown that the very early events post-OLT are critical in distinguishing immunogenic and tolerogenic reactions. In rodents, increased leukocyte apoptosis and cytokine expression have been demonstrated in tolerogenic strain combinations. Information from human OLT recipients is less abundant. The aim of this study was to determine the amount of early leukocyte activation and apoptosis following human OLT, and to correlate this with subsequent rejection status. Peripheral blood mononuclear cells (PBMC) were isolated from 76 patients undergoing OLT - on the day prior, 5 hrs after reperfusion (day 0), and 18-24 hrs post-OLT (day 1). The mean level of apoptotic PBMCs on post OLT day 1 was higher than healthy recipients (0.9% +/- 0.2 vs. 0.2% +/- 0.1, p = 0.013). Apoptosis was greater in nonrejecting (NR) (1.1% +/- 0.3) compared with acutely-rejecting (R) (0.3% +/- 0.1, p = 0.021) patients. On day 1, PBMC from NR patients had increased expression of IFN-gamma (p = 0.006), IL-10 (p = 0.016), and CD40 ligand (p = 0.02) compared with R. Donor cell chimerism on day 1 did not differ between the groups indicating that this was unlikely to account for increased PBMC apoptosis in the NR group. Interestingly, the level of chimerism on day 0 was significantly higher in NR (3.8% +/- 0.6) compared with R (1.2% +/- 0.4, p = 0.004) patients and there was a close correlation between chimerism on day 0 and cytokine expression on day 1. These results imply that similar mechanisms are occurring in the human liver to promote graft acceptance as in the experimental models of liver transplantation and suggest that strategies that promote liver transplant acceptance in rodents might be applicable to humans.

Patient and graft survival after liver transplantation for hereditary hemochromatosis: Implications for pathogenesis

The clinical outcome of patients who have undergone liver transplantation for hereditary hemochromatosis (HH) or who have received iron-loaded donor grafts is unclear. We reviewed 3,600 adult primary orthotopic liver transplants and assessed the outcomes in 22 patients with HH. We also evaluated graft function and iron mobilization in 12 recipients of iron-loaded donor grafts. All 22 subjects who received liver transplants for HH were male; 13 had other risk factors for liver disease. HH patients had comparatively poor outcomes following transplantation: survival at 1, 3, and 5 years posttransplantation were 72%, 62%, and 55%, respectively. Recurrent hepatocellular cancer was the most common cause of death. There was no convincing evidence of reaccumulation of iron in the grafted liver in HH; however, 1 subject demonstrated increased serum ferritin concentration and grade 2 hepatic siderosis. Liver iron stores were slow to mobilize in 7 of the 12 recipients of iron-loaded grafts. These recipients had appropriate early graft function, but 2 patients with heavy iron loading and increased hepatic iron developed hepatic fibrosis. In conclusion. (1) HH is an uncommon indication for liver transplantation, and the majority of patients requiring transplantation had other risk factors for chronic liver disease; (2) reaccumulation of liver iron in HH patients is very unusual, but increased iron stores may be slow to mobilize in normal recipients of iron-loaded grafts, potentially compromising late graft function; (3) post-liver transplant survival is reduced in HH, and affected patients require careful clinical evaluation of perioperative and postoperative risk factors. Our data suggest that iron excess in HH does not wholly depend on intestinal iron absorption but is also influenced by liver factors that moderate iron metabolism.

Pharmacokinetic considerations relating to tacrolimus dosing in the elderly

Relaxation of the upper age limits for solid organ transplantation coupled with improvements in post-transplant survival have resulted in greater numbers of elderly patients receiving immunosuppressant drugs such as tacrolimus. Tacrolimus is a potent agent with a narrow therapeutic window and large inter- and intraindividual pharmacokinetic variability. Numerous physiological changes occur with aging that could potentially affect the pharmacokinetics of tacrolimus and, hence, patient dosage requirements. Tacrolimus is primarily metabolised by cytochrome P450 (CYP) 3A enzymes in the gut wall and liver. It is also a substrate for P-glycoprotein, which counter-transports diffused tacrolimus out of intestinal cells and back into the gut lumen. Age-associated alterations in CYP3A and P-glycoprotein expression and/or activity, along with liver mass and body composition changes, would be expected to affect the pharmacokinetics of tacrolimus in the elderly. However, interindividual variation in these processes may mask any changes caused by aging. More investigation is needed into the impact aging has on CYP and P-glycoprotein activity and expression. No single-dose, intense blood-sampling study has specifically compared the pharmacokinetics of tacrolimus across different patient age groups. However, five population pharmacokinetic studies, one in kidney, one in bone marrow and three in liver transplant recipients, have investigated age as a co-variate. None found a significant influence for age on tacrolimus bioavailability, volume of distribution or clearance. The number of elderly patients included in each study, however, was not documented and may have been only small. It is likely that inter- and intraindividual pharmacokinetic variability associated with tacrolimus increase in elderly populations. In addition to pharmacokinetic differences, donor organ viability, multiple co-morbidity, polypharmacy and immunological changes need to be considered when using tacrolimus in the elderly. Aging is associated with decreased immunoresponsiveness, a slower body repair process and increased drug adverse effects. Elderly liver and kidney transplant recipients are more likely to develop new-onset diabetes mellitus than younger patients. Elderly transplant recipients exhibit higher mortality from infectious and cardiovascular causes than younger patients but may be less likely to develop acute rejection. Elderly kidney recipients have a higher potential for chronic allograft nephropathy, and a single rejection episode can be more devastating. There is a paucity of information on optimal tacrolimus dosage and target trough concentration in the elderly. The therapeutic window for tacrolimus concentrations may be narrower. Further integrated pharmacokinetic-pharmaco-dynamic studies of tacrolimus are required. It would appear reasonable, based on current knowledge, to commence tacrolimus at similar doses as those used in younger patients. Maintenance dose requirements over the longer term may be lower in the elderly, but the increased variability in kinetics and the variety of factors that impact on dosage suggest that patient care needs to be based around more frequent monitoring in this age group.