A Novel, Dose-Adjusted Tacrolimus Trough-Concentration Model for Predicting and Estimating Variance After Kidney Transplantation.

BACKGROUND AND OBJECTIVE: Given that a high intrapatient variability (IPV) of tacrolimus whole blood concentration increases the risk for a poor kidney transplant outcome, some experts advocate routine IPV monitoring for detection of high-risk patients. However, attempts to estimate the variance of tacrolimus trough concentrations (TTC) are limited by the need for patients to receive a fixed dose over time and/or the use of linear statistical models. A goal of this study is to overcome the current limitations through the novel application of statistical methodology generalizing the relationship between TTC and dose through the use of nonparametric functional regression modeling. METHODS: With TTC as a response and dose as a covariate, the model employs an unknown bivariate function, allowing for the potentially complex, nonlinear relationship between the two parameters. A dose-adjusted variance of TTC is then derived based on standard functional principal component analysis (FPCA). To assess the model, it was compared against an FPCA-based model and linear mixed-effects models using prediction error, bias, and coverage probabilities for simulated data as well as phase III data from the Astellas new drug application studies for extended-release tacrolimus. RESULTS: Our numerical investigation indicates that the new model better predicts dose-adjusted TTCs compared with the prediction of linear mixed effects models. Estimated coverage probabilities also indicate that the new model accurately accounts for the variance of TTC during the periods of large fluctuation in dose, whereas the linear mixed effects model consistently underestimates the coverage probabilities because of the inaccurate characterization of TTC fluctuation. CONCLUSION: This is the first known application of a functional regression model to assess complex relationships between TTC and dose in a real clinical setting. This new method has applicability in future clinical trials including real-world data sets due to flexibility of the nonparametric modeling approach.

Pharmacokinetic profile of micafungin when co-administered with amphotericin B in healthy male subjects.

OBJECTIVE: Micafungin and amphotericin B are antifungal agents with potent activity against a broad spectrum of fungal spp., including Candida and Aspergillus. The objective of this study was to evaluate the potential pharmacokinetic (PK) interaction of the two drugs in healthy subjects. METHODS: PK were evaluated in healthy adults in an open-label, phase I clinical trial, following separate treatments with micafungin (200 mg; days 1 - 5) and conventional amphotericin B (0.25 mg/kg; days 8 - 13) alone, and following co-administration of both drugs (days 14 - 18). RESULTS: In 20 male subjects, systemic exposure to micafungin (measured using peak plasma micafungin concentration (Cmax) and area under the plasma micafungin concentration-time curve (AUC0-τ)) were similar following coadministration of micafungin and amphotericin B (day 18; Cmax 19.1 µg/mL, AUC0-τ 232 µg×h/mL) compared with administration of micafungin alone (day 5; Cmax 18.7 µg/mL, AUC0-τ 236 µg×h/mL), suggesting that administration of amphotericin B does not affect the PK of micafungin. The exposure to amphotericin B was ~ 30% greater following co-administration of both drugs (day 18; Cmax 704 µg/mL, AUC0-τ 9157 µg×h/mL) than after administration of amphotericin B alone (day 13; Cmax 621 µg/mL, AUC0-τ 7023 µg×h/mL). Concurrent treatment with micafungin and amphotericin B was less well tolerated than when either agent was administered alone. CONCLUSIONS: PK and safety-related observations during co-administration of micafungin and amphotericin B were considered to be a consequence of accumulation of amphotericin B to a steady state, indicating that co-administration of the two drugs does not affect the PK of micafungin.

Pharmacokinetics of micafungin in pediatric patients with invasive candidiasis and candidemia.

Although micafungin pharmacokinetic values were comparable between younger (<5 years) and older children (≥5 years) with candidemia and invasive candidiasis, younger children had a lower peak plasma micafungin concentration, lower micafungin exposure and larger micafungin clearance. Half-life remained unchanged with repeated dosing. Metabolite plasma concentrations remained low in older children; however, metabolite M-5 concentrations were higher in younger children.

Increase in tacrolimus trough levels after steroid withdrawal.

Although there are experimental reports of cytochrome P450 3A4 iso-enzyme (CYP3A4) induction by glucocorticoids, there are no clinical reports about an interaction between tacrolimus and steroids. Therefore, tacrolimus trough level and dose were compared after dose-normalization before and after withdrawal of prednisolone. After withdrawal of 5 mg prednisolone, the median tacrolimus dose-normalized level increased by 14% in the retrospective ( n=54), and by 11% in the prospective ( n=8) part of the study. After withdrawal of 10 mg, this increase was 33% ( n=30) and 36% ( n=14), respectively. An additional pharmacokinetic part of the study ( n=8) revealed an 18% increase in AUC ( P=0.05) after withdrawal of 5 mg prednisolone, which is compatible with a reduced metabolism after steroid withdrawal. The significant increase in tacrolimus exposure after steroid withdrawal may on the one hand counteract the reduction in immunosuppression intended by steroid withdrawal, and, on the other hand, may result in an increase of serum creatinine which could be misinterpreted as rejection.

Pharmacokinetics of tacrolimus-based combination therapies.

This paper reviews the pharmacokinetics of tacrolimus, with special reference to its combination with adjunctive immunosuppressants. Oral bioavailability of tacrolimus, which is variable between patients, averages approximately 25%. This is largely due to extrahepatic metabolism of tacrolimus in the gastrointestinal epithelium. Nevertheless, intra-patient variability is low, as evidenced by the small number of dose changes required to maintain patients within the recommended tacrolimus target levels. Tacrolimus is distributed extensively in the body with most partitioned outside the blood compartment. Concentrations of tacrolimus in blood are used as a surrogate marker of clinically relevant concentration of the drug at the site(s) of action. Convenient whole-blood sampling within a +/-2-h window around 12 h post-dose (C(min)) is highly predictive of systemic exposure to tacrolimus and is thus used to optimise therapy. Sampling at other time-points offers no advantage over C(min) monitoring. The interactions of tacrolimus with other immunosuppressive agents are well characterized. After cessation of concomitant corticosteroid treatment, exposure to tacrolimus increases by approximately 25%. In contrast, there is no pharmacokinetic interaction between mycophenolate mofetil (MMF) and tacrolimus. Therefore, systemic exposure to the active metabolite of MMF, mycophenolic acid, is higher with MMF-tacrolimus combination than with MMF-cyclosporin combination. Therefore, 1 g/day MMF may be an adequate maintenance dose in tacrolimus-based regimens. Co-administration of tacrolimus and sirolimus, while having no effect on exposure to sirolimus, results in reduced exposure to tacrolimus at sirolimus doses of 2 mg/day and above. In conclusion, tacrolimus levels should be monitored when sirolimus is co-administered at doses >2 mg/day and after cessation of corticosteroid treatment.

A late episode of post-transplant diabetes mellitus during active hepatitis C infection in a renal allograft recipient using tacrolimus.

BACKGROUND: An association between hepatitis C virus and (post-transplant) diabetes mellitus has been reported. METHODS: We report a patient on tacrolimus-based immunosuppression who developed an episode of post-transplant diabetes mellitus (PTDM) 2 years after renal transplantation, after contracting a hepatitis C infection. Her glucose metabolism was evaluated regularly by intravenous glucose tolerance tests before and after the PTDM episode. RESULTS: Before contracting hepatitis C, the patient's insulin resistance and insulin secretion were normal. After contracting hepatitis C, tacrolimus exposure increased, insulin resistance increased, and insulin secretion decreased markedly. Despite low tacrolimus exposure in the last 4 years, glucose metabolism did not recover completely. Although PTDM resolved and insulin resistance normalized, pancreatic beta cell secretion remained impaired by approximately 50% compared with the period before hepatitis C infection. CONCLUSION: After an initial increase in insulin resistance, insulin secretion decreased markedly in a patient who contracted hepatitis C 12 to 22 months after renal transplantation. This change resulted in an episode of PTDM. Increased tacrolimus exposure secondary to reduced cytochrome P-450 metabolism as a result of impaired hepatocellular function at the time of the development of PTDM seems a likely explanation for the marked decrease in insulin secretion. Viral toxicity to the beta cell might be an additional explanation. The latter might be suspected from several reports about an association between diabetes mellitus and hepatitis C in patients who do not use drugs that interfere with glucose metabolism.