The statistically significant difference in CV between both CYP3A5 groups during Tac BID became numerically much smaller after conversion and was not statistically significant anymore (P=0.22). Changes in the CV for Cmin were in the same direction, although to a lesser extent.
Our study is the first designed to prospectively study the change in intrapatient variability in systemic tacrolimus exposure after converting from Tac BID to Tac QD in stable renal transplant patients. Five sequential PK profiles both during Tac BID and Tac QD were collected under steady-state conditions by means of the dried blood spot (DBS) method (11). This method is routinely used for measuring Tac levels in our outpatient clinical practice for more than 5 years.
We have proven that this method is very reliable for determining Tac levels, especially when performed by well-instructed and motivated patients (11). The low percentage of missing crucial samples and samples of low quality in this study is another proof that the DBS method is robust. Only 12 of the 400 profiles had to be repeated.
A significant improvement in the intrapatient variability in 24-hour exposure after converting from Tac BID to Tac QD was found, confirming previous post hoc analyses (1, 2). This improvement in CV can be caused either by improved adherence of the patients or by intrinsic differences in the PK properties of the two Tac formulations. Although nonadherence can never completely be excluded, it is very unlikely that it has occurred with these selected patients and with this strict protocol. Hence, the improvement in intrapatient CV after converting from Tac BID to Tac QD is most likely due to differences in the PK properties of Tac QD compared to those of Tac BID.
Although the AUC differed only by −2.7% between Tac BID and Tac QD, Cmin did so by −10.8%. Earlier phase 2 trials showed a 5% to 10% lower AUC for Tac QD in stable kidney transplant recipients compared to Tac BID (1, 2, 12), with a larger patient population compared to our study (60 and 67 vs. 40, respectively). It could be that so that our study was underpowered to detect a significant difference with respect to the AUC, but values and the corresponding confidential interval of the current study comply with those earlier reports. Our current study was not designed to compare the relative bioavailability of Tac BID and Tac QD. On the other hand, we also found an identical relationship between Cmin and AUC given the virtually identical slopes of the regression lines (Fig. 2).
Especially in the Cyp3A5*1/*3 group, the intrapatient CV decreased after conversion, although this did not reach statistical significance (P=0.062). It has been hypothesized that Cyp3A activities are generally decreased in the Cyp3A5*3/*3 genotype, and the chances of being influenced by environmental factors would then increase through induction of Cyp3A4 and Cyp3A5 by the pregnane X receptor (13). Cyp3A4 is postulated to be more prone to induction than Cyp3A5, and since, in Cyp3A5 expressors, the Cyp3A5 activity would be rather stable, different amounts of Cyp3A4 could cause substantial intra-individual variability.
On the contrary, Pashaee et al. (14) could not establish a relationship between the Cyp3A5 genotype and intrapatient variability. We found in our study that Cyp3A5*1/*3 carriers had a higher CV under Tac BID, which declined after converting to the once-daily formulation. This would be in line with the findings of Alloway et al. (1) and Wu et al. (7), at least if we assume that the African Americans and Chinese represent a high prevalence of the Cyp3A5*1 genotype (8, 9).
In our white population, we included only a limited number of patients with the CYP3a5*1 allele, and none of the patients were homozygous for this allele. Also in patients homozygous for the Cyp3A5*1 allele, a larger decrease in CV can be expected. Nevertheless, in our study, the CYP3A5*1/*3 group had a significantly higher intrapatient CV compared to the CYP3A5*3/*3 group under Tac BID, a difference that was not significant anymore after converting to Tac QD.
In conclusion, we confirmed the reduced intrapatient CV for Tac QD compared to Tac BID. This improvement does not merely result from improved adherence but reflects the intrinsic PK properties of Tac QD. The long-term clinical significance of a decreased variability in Tac drug exposure has yet to be determined. Thereafter, patients might profit from a drug with a reduced variability in systemic exposure. The reduction in intrapatient CV is numerically larger in patients with the Cyp3a5*1 allele. A limitation of our study is the relatively small number of patients carrying the Cyp3a5*1 allele and especially the absence of Cyp3a5*1 homozygotes. This should be explored in a future study.
MATERIALS AND METHODS
All patients 18 years or older with a stable renal allograft function 6 months before inclusion and on stable Tac BID dosages were eligible for participation in our study. Because we were particularly interested in the Cyp3A5*1 genotype, patients with a daily dose at least twice as high as the average daily dose (i.e., ≥6 mg) were regarded as potential carriers of the cyp3A5*1 genotype and were preferentially selected. Patients were excluded if they had any organ other than kidney transplanted, had active malignancy, had renal replacement therapy, had signs of infection shortly before inclusion, or have chronic diarrhea. Patients were enrolled after they had given their informed consent. The study had been approved by the local medical ethics committee (METC 09-2-040) and was registered in the EudraCT trial register (registration no. 2009-010400-28).
The study was an investigator-driven, single-center, open-label, prospective, two-sequence conversion comparative study, in which PK parameters were evaluated with respect to their variability before and after converting from Tac BID to Tac QD. The study period started with a run-in period of 2 weeks during which the patients were instructed to take the Tac BID under fasting conditions, that is, 1 hour before or 2 hours after a meal. From the third week on, five weekly 24-hour blood concentration-time profiles to determine AUC0–24 were taken (Fig. 4), and if one of the profiles was not evaluable (see below), an additional profile was taken. After five evaluable profiles had been taken, patients were converted to Tac QD on a 1:1 (mg/mg) basis. After a stabilization period of 2 weeks, five additional evaluable 24-hour AUC profiles at weekly intervals were taken in the second phase of the study (Fig. 4). One week after conversion, a venous tacrolimus trough level was taken and Tac QD dose was adjusted if the trough level was less than 3.5 μg/L. Sampling of the first blood concentration-time profile was postponed up to 2 weeks after the last Tac QD adjustment.
Because no numerical data on the change in intrapatient variability in 24-hour drug exposure were available, no formal statistical power analysis could be performed. The study population was set at 40 patients based on common practice in other PK studies (12).
The primary objective of this study was to evaluate and compare the intrapatient variability of AUC0–24 of Tac BID and Tac QD in stable renal transplant patients. Secondary endpoints were correlation of the PK profiles with the CYP3A5 genotype and comparison of the intrapatient variability of the trough levels (Cmin).
Assessments and Assay
A total of five AUCs were arbitrarily considered adequate for the assessment of the intrapatient variability for each formulation. Each PK profile consisted of eight blood samples that were collected before dosing and at 2, 4, 8, 12, 14, 16, and 24 hours after dosing by means of the DBS method. This eight-point 24-hour PK profile was assumed to give a valid AUC for both Tac BID and Tac QD.
As for Tac BID, earlier reports guarantee prediction of the AUC0–12 when samples at t=0 hour, t=2 hours, and t=4 hours are included (15). For the AUC0–24, we added the corresponding time points after the evening dose, namely, t=12 hours, t=14 hours, and t=16 hours. We extended this six-point strategy to eight points by adding t=8 hours and t=24 hours to get more information about the elimination phase. For the patient’s convenience, we did not add t=20 hours.
As for the Tac QD profiles, our center has previously participated in a local board-approved phase 3 trial (METC code 03-102; EudraCT no. 2005-005714-20) in which 27 stable renal transplant patients provided a venous 24-hour PK profile under fasting conditions. This profile consisted of 10 time points at t=0, 1, 2, 3, 4, 6, 8, 10, 12, and 24 hours. The eight-point AUC was then validated by means of linear regression: this model revealed a maximum R2 of 0.995 when the samples at t=2, 4, 8, 12, and 24 hours were included. An AUC was regarded as adequate in case at least six valid blood spot samples were available and if none of the above-mentioned crucial sample or the trough level were missing.
If a profile did not fulfill these criteria, it had to be repeated 1 week later. In addition, patients visited our outpatient clinics before the start of the study, 1 week after conversion, and at the end of the study (Fig. 4). During these outpatient visits, regular venous blood and urine samples were drawn for routine posttransplantation medical care and safety reasons, including determination of a venous tacrolimus Cmin. These data were not included in the PK analysis. To rule out potential noncompliance, medication intake had to be registered and was controlled by pill count for both formulations.
The patients themselves collected the required blood samples by means of the DBS method at home, with strict recording of dosing and sampling time points. This method has been described and validated before (11). In brief, fingerprick blood samples were collected using a contact-activated lancet (Becton, Dickinson and Company, Franklin Lakes, NJ). The first two drops were collected from the lateral part of the fingertip to fill two 8-mm premarked circles, for duplicate sampling, on the sampling paper (Item No. 10535097; Whatman, Schleicher and Schuell, Dassel, Germany). The blood spots were allowed to dry at room temperature for at least 10 min before packaging and were stored in a sealed plastic bag containing silicone granules. After completion of the 24-hour profile, all samples were collectively sent by regular post to our laboratory where they were stored at 4°C until further analysis. It has been proven that tacrolimus in dry blood spot is stable during postal transport (16, 17). Before the start of the study, patients were trained in blood spot sampling, and the study was initiated only after all patients had repeatedly sent in a blood spot sample that had passed the quality control.
Each of the two blood spots on the sampling paper was analyzed on separate analytical runs, and the average value of both analyses was the reported value of the tacrolimus concentration. If the two results diverged by more than 30%, this value was reported as missing and was not considered. If one analytical run was invalid because of a poor quality control, we only disposed of one instead of two values. In case two runs had a missing noncrucial value at the same single time point, the average concentration at that particular time point was revealed by interpolation after natural logarithmic transformation. If more samples were missing because of analytical problems, the run was redone by analyzing the diluted extraction solution. In case a crucial sample was missing at a time point as defined above, the PK profile had to be repeated.
Analysis of the concentration of tacrolimus started with punching out the dried blood spots and adding an extraction solution. The prepared samples were analyzed in the same way as the routine tacrolimus assay in venous blood. The tacrolimus assay is validated according to, and complied with, the ‘“Bioanalytical Methods Validation, Guidance for Industry”’ (18), with a lower limit of quantification of 1.0 μg/L (11). The laboratory participated in the international tacrolimus proficiency testing scheme (www.bioanalytics.co.uk). The concentration of tacrolimus was determined by means of tandem mass spectrometry. Chromatography was performed using an Alliance 2795 system (Waters Ltd., Watford, UK). The mass spectrometer used in our study was a Quattro Micro (Micromass, Manchester, UK).
Each patient provided a venous blood sample at the screening visit of this study for genetic analysis. Genomic DNA was extracted according to the manufacturer’s instructions (Qiagen, Leusden, The Netherlands). Real-time polymerase chain reaction fluorescence resonance transfer assays were used for genotyping with the LightCycler (Roche Diagnostics, Almere, The Netherlands).
Demographic data were presented as mean and range and PK parameters were presented as geometric mean and 90% confidence interval (CI). AUC was calculated using the linear trapezoidal rule. Before statistical analysis, PK data were natural log-transformed and transformed back to the original scale for display of the data.
Intrapatient variability was calculated through the CV as follows:
where SWR is the within-subject standard deviation of the natural log-transformed values.
PK parameters were compared with the paired-measurements t test; Cyp3A5 polymorphism was analyzed with nonparametric tests (Wilcoxon signed rank test for paired measurements and Mann-Whitney U test for nonpaired measurements).
P<0.05 was considered statistically significant. Statistical analysis was performed using SPSS 16.0 for Windows (release 16.0.1).
The authors thank their research nurse, Mrs. Monique Mullens, for her support during the study. The study would not have been feasible otherwise.
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Keywords:© 2014 by Lippincott Williams & Wilkins
Tacrolimus; Pharmacokinetics; Therapeutic drug monitoring; Intra-patient coefficient of variability; Drug exposure; Formulation