A limited sampling strategy for cyclosporine area under the curve monitoring in lung transplant recipients

Immunosuppression in lung transplantation

Lung transplantation can be a life-saving procedure for those with end-stage lung diseases. Unfortunately, long term graft and patient survival are limited by both acute and chronic allograft rejection, with a median survival of just over 6 years. Immunosuppressive regimens are employed to reduce the rate of rejection, and while protocols vary from center to center, conventional maintenance therapy consists of triple drug therapy with a calcineurin inhibitor (cyclosporine or tacrolimus), antiproliferative agents [azathioprine (AZA), mycophenolate, sirolimus (srl), everolimus (evl)], and corticosteroids (CS). Roughly 50% of lung transplant centers also utilize induction therapy, with polyclonal antibody preparations [equine or rabbit anti-thymocyte globulin (ATG)], interleukin 2 receptor antagonists (IL2RAs) (daclizumab or basiliximab), or alemtuzumab. This review summarizes these agents and the data surrounding their use in lung transplantation, as well as additional common and novel therapies in lung transplantation. Despite the progression of the management of lung transplant recipients, they continue to be at high risk of treatment-related complications, and poor graft and patient survival. Randomized clinical trials are needed to allow for the development of better agents, regimens and techniques to address above mentioned issues and reduce morbidity and mortality among lung transplant recipients.

Immunosuppression and allograft rejection following lung transplantation: evidence to date

The enduring success of lung transplantation is built on the use of immunosuppressive drugs to stop the immune system from rejecting the newly transplanted lung allograft. Most patients receive a triple-drug maintenance immunosuppressive regimen consisting of a calcineurin inhibitor, an antiproliferative and corticosteroids. Induction therapy with either an antilymphocyte monoclonal or an interleukin-2 receptor antagonist are prescribed by many centres aiming to achieve rapid inhibition of recently activated and potentially alloreactive T lymphocytes. Despite this generic approach acute rejection episodes remain common, mandating further fine-tuning and augmentation of the immunosuppressive regimen. While there has been a trend away from cyclosporine and azathioprine towards a preference for tacrolimus and mycophenolate mofetil, this has not translated into significant protection from the development of chronic lung allograft dysfunction, the main barrier to the long-term success of lung transplantation. This article reviews the problem of lung allograft rejection and the evidence for immunosuppressive regimens used both in the short- and long-term in patients undergoing lung transplantation.

Validation of sparse sampling strategies to estimate cyclosporine A area under the concentration-time curve using either a specific radioimmunoassay or high-performance liquid chromatography method

INTRODUCTION

Area under the concentration-time curve (AUC) has been advocated as a better parameter to monitor cyclosporine A than trough concentrations. Up to now, more than 100 equations to estimate AUC using a limited sampling strategy have been published, but not all have been validated.

MATERIAL AND METHODS

Eight equations for AUC0-12h and two for AUC0-8h were validated. Concentrations of cyclosporine A were analyzed by high-performance liquid chromatography (HPLC) and a specific radioimmunoassay (RIA) method. Forty male renal transplant patients were included in the study. Blood samples were taken predose and at 0.5, 1, 1.5, 2, 3, 5, 8, and 12 hours after the morning dose when the patient was in steady state. The percentage prediction error (%pe) was used for an assessment of the performance of the equations. Mean %pe less than ± 15% and absolute %pe less than 30% in 95% of predictions were considered to be acceptable. Other possibilities such as %pe less than 25%, 20%, and 15% were also tested.

RESULTS

Eight equations for AUC0-12h met the requirements using both assays, six in the HPLC set only and four in the RIA set only. The highest precision was obtained with AUC0-12h = 123.792 + 1.165*C1h + 3.021*C3h + 7.33*C8h proposed by de Mattos et al. The mean %pe was 1% ± 8% (-16 to 19) for HPLC (values given as mean ± standard deviation [range]) and -1 ± 5 (-17 to 10) for RIA. Mean absolute %pe was 7 ± 5 (0.0 to 19) for HPLC and 4 ± 4 (0.0 to 17) for RIA. For clinical use, the most suitable equation was AUC0-12h = 363.078 + 8.77*C1h + 3.07*C3h proposed by Wacke et al, which produced the second lowest %pe and used two sampling points in the period of 1 to 3 hours after dose. The mean %pe was -7 ± 10 (-25 to 25) for HPLC and 2.3 ± 6 (-10 to 17) for RIA. Mean absolute %pe was 10 ± 7 (0.4 to 25) for HPLC and 5 ± 4 (0.0 to 17) for RIA. The equation: AUC0-8h = 55.37 + 2.89*C0h + 1.08*C1h0.9*C2h + 2.23*C3h proposed by Foradori et al met the criteria with 95% of prediction with absolute %pe less than 15% in the HPLC set and 10% in the RIA set.

CONCLUSION

The validation of equations is of major importance for prediction precision, whereas the analytical method for limited sampling strategy proposals had no influence. Because of the wide interassay variability, it is also important to know which analytical method was used for AUC calculation when interpreting the results.

Pharmacokinetic optimization of immunosuppressive therapy in thoracic transplantation: part I

Although immunosuppressive treatments and therapeutic drug monitoring (TDM) have significantly contributed to the increased success of thoracic transplantation, there is currently no consensus on the best immunosuppressive strategies. Maintenance therapy typically consists of a triple-drug regimen including corticosteroids, a calcineurin inhibitor (ciclosporin or tacrolimus) and either a purine synthesis antagonist (mycophenolate mofetil or azathioprine) or a mammalian target of rapamycin inhibitor (sirolimus or everolimus). The incidence of acute and chronic rejection and of mortality after thoracic transplantation is still high compared with other types of solid organ transplantation. The high allogenicity and immunogenicity of the lungs justify the use of higher doses of immunosuppressants, putting lung transplant recipients at a higher risk of drug-induced toxicities. All immunosuppressants are characterized by large intra- and interindividual variability of their pharmacokinetics and by a narrow therapeutic index. It is essential to know their pharmacokinetic properties and to use them for treatment individualization through TDM in order to improve the treatment outcome. Unlike the kidneys and the liver, the heart and the lungs are not directly involved in drug metabolism and elimination, which may be the cause of pharmacokinetic differences between patients from all of these transplant groups. TDM is mandatory for most immunosuppressants and has become an integral part of immunosuppressive drug therapy. It is usually based on trough concentration (C(0)) monitoring, but other TDM tools include the area under the concentration-time curve (AUC) over the (12-hour) dosage interval or the AUC over the first 4 hours post-dose, as well as other single concentration-time points such as the concentration at 2 hours. Given the peculiarities of thoracic transplantation, a review of the pharmacokinetics and TDM of the main immunosuppressants used in thoracic transplantation is presented in this article. Even more so than in other solid organ transplant populations, their pharmacokinetics are characterized by wide intra- and interindividual variability in thoracic transplant recipients. The pharmacokinetics of ciclosporin in heart and lung transplant recipients have been explored in a number of studies, but less is known about the pharmacokinetics of mycophenolate mofetil and tacrolimus in these populations, and there are hardly any studies on the pharmacokinetics of sirolimus and everolimus. Given the increased use of these molecules in thoracic transplant recipients, their pharmacokinetics deserve to be explored in depth. There are very few data, some of which are conflicting, on the practices and outcomes of TDM of immunosuppressants after thoracic transplantation. The development of sophisticated TDM tools dedicated to thoracic transplantation are awaited in order to accurately evaluate the patients' exposure to drugs in general and, in particular, to immunosuppressants. Finally, large cohort TDM studies need to be conducted in thoracic transplant patients in order to identify the most predictive exposure indices and their target values, and to validate the clinical usefulness of improved TDM in these conditions. In part I of the article, we review the pharmacokinetics and TDM of calcineurin inhibitors. In part II, we will review the pharmacokinetics and TDM of mycophenolate and mammalian target of rapamycin inhibitors, and provide an overall discussion along with perspectives.

Single time point measurement by C2 or C3 is highly predictive in cyclosporine area under the curve estimation immediately after lung transplantation

BACKGROUND

The two h post-dose cyclosporine (CsA) concentration has been advocated as the optimal time point measurement for CsA area under the curve (AUC) estimation after solid organ transplantation. The aim of the study was to investigate whether intensified CsA monitoring is necessary, or if a single time point measurement is accurate to estimate the AUC in the very early period following lung transplantation (LuTX).

METHODS

Within the first two wk following transplantation, daily AUCs were calculated by serial CsA measurements at zero, one, two, three, four, and six h (C0-C6) in 12 consecutive lung transplant recipients. Correlation of single CsA measurements and AUC as well as linear regression analysis was performed to evaluate the most predictive single CsA blood level regarding the AUC.

RESULTS

A total of 606 CsA concentration measurements were performed and the 101 corresponding AUCs were calculated for each patient. Mean AUC was 3443 +/- 1451 microg/L. C0: 361 +/- 118 microg/L, C1: 481 +/- 231 microg/L, C2: 682 +/- 314 microg/L, C3: 715 +/- 347 microg/L, C4: 658 +/- 271 microg/L, C6: 571 +/- 260 microg/L. The correlation of CsA serum levels with AUC was the lowest at trough levels (C0) with a correlation coefficient (r = 0.31) and highest at three h (C3: r = 0.89) and two h (C2: r = 0.88).

CONCLUSIONS

Similar to a stable post-transplant period, CsA trough levels turned out to have poor correlation with the corresponding AUC early after LuTX. The highest correlation of C3 with the AUC may be explained by delayed intestinal resorption immediately post-operative, however C2 is a peer parameter. Optimum AUCs and corresponding C2 or C3 levels in the immediate post-operative phase however remain to be determined.

Monitoring C2 level predicts exposure in maintenance lung transplant patients receiving the microemulsion formulation of cyclosporine (Neoral)

BACKGROUND

Dosing of the microemulsion formulation of cyclosporine (Neoral) is conventionally based on trough levels (C(0)). However, experience in renal transplantation has shown that cyclosporine exposure during the absorption phase (AUC(0-4)) is critical for optimizing immunosuppression, and that cyclosporine (CsA) concentration at 2 hours post-dose (C(2)) shows the closest correlation with AUC(0-4). This study evaluated whether C(2) values correlate more closely with AUC(0-4) than C(0) in lung transplant patients.

METHODS

Pharmacokinetic data were collected prospectively from 20 clinically stable adult lung allograft recipients receiving CsA, mycophenolate mofetil and steroids. Indications for transplantation were emphysema (n = 15), idiopathic fibrosis (n = 2), primary pulmonary hypertension (n = 1), cystic fibrosis (n = 1) and lymphangioleiomyomatosis LAM (n = 1). Blood samples were collected at 0, 1, 2, 3 and 4 hours after administration of CsA, and then AUC(0-4) was calculated. The Correlation between cyclosporine concentration at each time-point and AUC(0-4) was also calculated.

RESULTS

C(2) showed the closest correlation with AUC(0-4) (r(2) = 0.85). C(0) had the poorest correlation of all time-points (r(2) = 0.64). Two patients with radiologic signs of gastroparesis had no peak cyclosporine levels at all and were excluded from the correlation analysis. Mean AUC(0-4) was 3,700 ng . h/ml during Year 1 post-transplant, 2,400 ng . h/ml during Years 1 to 3, and 1,500 ng . h/ml thereafter. Mean C(2) values were 1.2 microg/ml during Year 1, 0.8 microg/ml during Years 1 to 3, and 0.5 microg/ml thereafter.

CONCLUSIONS

C(2) is the single time-point that correlates most closely with AUC(0-4) in lung transplant recipients without gastroparesis. It remains to be demonstrated whether monitoring CsA based on C(2) levels results in a lower incidence of rejection without additional toxicity.

Promise of Neoral C2, basiliximab, and everolimus in lung transplantation

Immunosuppressive therapy to prevent rejection of allografts is continually evolving in terms of development of new medications and the application of established ones. This review summarizes current knowledge regarding monitoring blood cyclosporine microemulsion (Neoral) levels 2 hours postdose (C2), as well as the relatively new immunosuppressants basiliximab and everolimus, with a particular view to lung transplantation. C2 monitoring appears to have merit over the traditional method of trough-level monitoring. Based on short-term studies in various solid organ transplant systems, C2 seems better able to predict the area under the time-concentration curve for Neoral, a benefit that extends to improved clinical outcomes. Further studies are needed to verify the robustness of clinical improvement, particularly in lung transplant recipients. Basiliximab and everolimus target stages of the immune response distinct from that targeted by Neoral. Studies conducted to date in various solid organ transplant systems suggest that use of Neoral concomitantly with one or both of these drugs provides enhanced protection from allograft rejection while improving the tolerability of immunosuppressive therapy. If these results are confirmed in lung transplant patients, improvements in lung transplantation outcomes are to be expected.

Cyclosporine C2 monitoring improves renal dysfunction after lung transplantation

BACKGROUND

Cyclosporine (CyA) toxicity is a potential cause of renal dysfunction, which occurs in 38% of lung transplant (LTx) recipients within 5 years. Reducing CyA to "sub-therapeutic" trough (C0) levels increases the risk of rejection. The 2-hour post-dose concentration (C2) is favored as the best single-point surrogate measure of CyA area under the curve (AUC), which reflects drug exposure. In this investigation we assess the effect of conversion to CyA C2 monitoring on renal dysfunction after LTx.

METHODS

Fifteen patients (M:F = 12:3), aged 47 +/- 14 years (range 28 to 62), 3.5 +/- 2.7 (0.2 to 9.0) years post-LTx, with C0 in the therapeutic range (maintenance 100 to 200 microg/liters) (Behring/EMIT immunoassay) and abnormal renal function, were converted from C0 monitoring to C2 monitoring with dose reductions targeting C2 levels of 300 to 600 microg/liter over a 12-month period.

RESULTS

CyA dose was reduced from 6.4 +/- 7.3 (1.2 to 27.9) to 3.1 +/- 2.7 (0.8 to 9.0) mg/kg/day (p = 0.04), with a reduction in C2 levels from 799 +/- 341 (299 to 1,466) to 390 +/- 148 (195 to 675) microg/liter (p < 0.001). Improvements in serum creatinine (0.20 +/- 0.07 [0.12 to 0.35] vs 0.16 +/- 0.04 [0.11 to 0.22] mmol/liter [p = 0.005]) were maintained during the study follow-up period of 1 year. Only 1 patient developed acute rejection and group mean forced expiratory volume in 1 second (FEV(1)) remained stable (2.4 +/- 1.0 [1.1 to 4.0] vs 2.4 +/- 1.2 [1.1 to 4.6] liters).

CONCLUSIONS

C2 monitoring is a practical method of improving renal dysfunction that allows safe dose reductions of CyA when formal AUC monitoring is not feasible. Extended use of this strategy is associated with long-term benefits.

Enhanced clinical utility of De Novo cyclosporine C2 monitoring after lung transplantation

BACKGROUND

The 2-hour post-cyclosporine (CyA) dose concentration (C2) is favored as the best single-point correlate of CyA area-under-the-concentration curve. CyA nephrotoxicity is a prominent cause of renal dysfunction that affects 38% of lung transplant (LTx) recipients at 5 years.

METHODS

We assessed the utility of de novo C2 monitoring after LTx by comparing 2 sequential groups of 18 bilateral LTx recipients followed with traditional de novo trough CyA (C0) monitoring and de novo C2 monitoring, respectively. Target C0 levels were 450 microg/liter and 250 microg/liter at 1 week and 3 months (3/12). Target C2 levels were 1,200 microg/liter and 800 microg/liter. Groups were matched for anthropometrics and diagnoses. Baseline serum creatinine (Cr) was lower in the C0 group than in the C2 group (65 +/- 17 vs 81 +/- 21 micromol/liter, p = 0.02).

RESULTS

At 3 months, survival for both groups was 100%, but the C0 group had a greater increase in Cr from baseline (90 +/- 54% vs 33 +/- 23%, p < 0.001) despite similar CyA dosage (6.6 +/- 3.8 vs 6.5 +/- 2.9 mg/kg/day, p = 0.94). There was no difference in forced expiratory volume in 1 second (% predicted) (71 +/- 16 vs 69 +/- 14, p = 0.68), mean acute vascular rejection score per patient (2.61 +/- 2.12 vs 1.44 +/- 1.72, p = 0.079), mean bronchial rejection score per patient (3.72 +/- 1.81 vs 2.83 +/- 1.58, p = 0.126) or rate of infection (1.85 vs 1.79 events per 100 patient-days).

CONCLUSIONS

De novo C2 monitoring, which reduces both the risk of CyA toxicity and the risk of sub-therapeutic dosing, is a safe and effective technique for short-term preservation of renal function after LTx.

Cyclosporine pharmacokinetics and dose monitoring after lung transplantation: comparison between cystic fibrosis and other conditions

BACKGROUND

In cystic fibrosis (CF), absorption of cyclosporine A (CsA) through the gastrointestinal tract is often impaired because of fat malabsorption. The aim of this study was to compare the steady-state pharmacokinetics of CsA and the inter- and intrasubject variability of CsA exposure in stable lung transplant recipients with and without CF and to determine the best single-time predictors of the area under the curve (AUC).

METHODS

Ten lung transplant recipients without CF and 10 lung transplant recipients with CF were studied. All patients received Neoral twice daily. Blood samples were obtained predose and at 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 6, 8, and 12 h postdose on three separate days within a 5-day period.

RESULTS

CsA exposure and pharmacokinetic variables were similar in the two groups, although exposure-per-milligram-per-dose was approximately 25% lower in CF patients. Coefficients of intersubject variability were numerically higher in CF patients, but the difference between groups did not reach significance. On the other hand, the maximum concentration (Cmax), the concentration 2 hours after administration (C2), AUC0-12, and AUC0-4 showed a twofold greater intrasubject variability in CF patients. CsA trough concentration did not predict accurately the AUC, but C2 was a good predictor of the AUC0-4 in both CF (r2=0.90) and non-CF (r2=0.78) patients.

CONCLUSION

Compared to patients without CF, patients with CF show a lower bioavailability of CsA and a greater intrasubject variability of Cmax, C2, and AUC. C2 is the best single-point predictor of the AUC0-4 in lung transplant recipients with and without CF.

Bayesian forecasting of oral cyclosporin pharmacokinetics in stable lung transplant recipients with and without cystic fibrosis

The aims of the current study were (1) to study Neoral pharmacokinetics (PK) in stable lung recipients with or without cystic fibrosis (CF), (2) to compare Neoral PK between these two groups, and (3) to design Bayesian estimators for PK forecasting and dose adjustment in these patients using a limited number of blood samples. The individual PK of 19 adult lung transplant recipients, 9 subjects with CF and 10 subjects without CF, were retrospectively studied. Three profiles obtained within 5 days were available for each patient. A PK model combining a gamma distribution to describe the absorption profile and a two-compartment model were applied. Different exposure indices were estimated using nonlinear regression and Bayesian estimation. The PK model developed reliably described the individual PK of Neoral in lung transplant patients with and without CF, and the values of the first and second half-lives were different in these two populations (lambda(1) = 4.14 +/- 3.01 vs. 2.16 +/- 1.75 h(-1); P < 0.01; lambda(2) = 0.36 +/- 0.11 vs. 0.49 +/- 0.12 h(-1); P < 0.01), while the mean absorption time and standard deviation of absorption time tended to be less in patients with cystic fibrosis (P < 0.1). Also, the patients with CF required higher doses than those without CF to achieve similar drug exposure. Consequently, population modeling was performed in CF and non-CF patients separately. Bayesian estimation allowed accurate prediction of AUC(0-12), AUC(0-4), C(max), and T(max) using three blood samples collected at T0h, T1h, and T3h in both groups. This study demonstrated the applicability and good performance of the PK model previously developed for oral cyclosporin and of the MAP Bayesian estimation of cyclosporin systemic exposure in CF and non-CF patients. Moreover, it is the first to propose a monitoring tool specifically designed for cyclosporin monitoring in patients with CF.