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Keywords:

  • Biopsy-proven acute rejection;
  • pharmacodynamics;
  • tacrolimus concentration;
  • therapeutic drug monitoring;
  • transplantation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

Therapeutic drug monitoring (TDM) for tacrolimus (Tac) is universally applied. However, the concentration–effect relationship for Tac is poorly defined. This study investigated whether Tac concentrations are associated with acute rejection in kidney transplant recipients. Data from three large trials were pooled. We used univariate and multivariate analysis to investigate the relationship between biopsy-proven acute rejection (BPAR) and Tac predose concentration at five time points (day 3, 10 and 14, and month 1 and 6 after transplantation). A total of 136/1304 patients experienced BPAR, giving an overall incidence of 10.4%. We did not find any significant correlations between Tac predose concentrations and the incidence of BPAR at the different time points. In the multivariate analysis, only delayed graft function (DGF) and the use of induction therapy were independently correlated with BPAR, with an odds ratio of 2.7 [95% CI: 1.8–4.0; p < 0.001] for DGF and 0.66 [95% CI: 0.44–0.99; p = 0.049] for induction therapy. The other variables, including the Tac predose concentrations, were not statistically significantly associated with BPAR. We did not find an association between the Tac predose concentrations measured at five time points after kidney transplantation and the incidence of acute rejection occurring thereafter. Based on this study it is not possible to define the optimal target concentrations for Tac.


Abbreviations
BPAR

Biopsy Proven Acute Rejection

CsA

Cyclosporine A

DGF

Delayed Graft Function

DSA

Donor Specific anti-HLA Antibody

FDCC

Fixed Dose versus Concentration Controlled

HLA

Human Leukocyte Antigen

PBMCs

Peripheral Blood Mononuclear Cells

PRA

Panel Reactive Antibody

RCT

Randomized Controlled Trial

Tac

Tacrolimus

TDM

Therapeutic Drug Monitoring

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

Tacrolimus (Tac) has almost replaced cyclosporine A (CsA) as the drug of first choice for the prevention of graft rejection after kidney transplantation [1]. Therapeutic drug monitoring (TDM) for Tac is universally applied. Requirements for a drug to implement TDM in clinical practice include a high between-patient variability in pharmacokinetics, a relatively low within-patient variability and a concentration-effect relationship. In order to do TDM, assays to measure drug concentrations also need to be available and ideally, randomized trials should show an improvement in clinical outcome when a drug is dosed based on measured drug concentrations compared to a fixed-dose approach. For Tac several assays are available, but randomized trials showing a benefit of TDM are not available. However, it is not realistic to expect that for Tac such a trial will ever be performed.

Contrary to the belief of many physicians and surgeons, the concentration–effect relationship for Tac is poorly defined. As the most important reason to prescribe Tac to a transplant recipient is the prevention of acute rejection, it is surprising that there are so few data on the concentration–effect relationship of Tac. Based on the current literature there is little support to promote the use of a specific therapeutic window and aim for certain target concentrations.

Several investigators have attempted to identify the optimal Tac concentration range, that is, the one which is associated with the lowest incidence of rejection and with acceptable toxicity, as shown in Table 1. The findings of many of these reports are conflicting and limited by the fact that they were of a retrospective design, included limited numbers of patients and that the coimmunosuppressive medication used was different from that which is currently considered the gold standard. For the interpretation of the studies that are available, an important additional problem is the fact that not all investigators studied Tac concentrations at the same time point after transplantation.

Table 1. Literature
Author, yearNumber of patientsConclusion
Borobia et al. 2009 [2]57 kidneyThe Tac predose concentrations within the first postoperative week are important predictors of acute rejection
Staatz et al. 2001 [3]29 kidneySignificant relationship between acute rejection and median Tac predose concentrations in the first month
Bottiger et al. 1999 [4]14 kidneyConcentrations below 10 ng/mL seem to be beneficial with respect to side effects
Kershner et al. 1996 [5]92 kidneySignificant relationship between the Tac concentrations and toxicity
Undre et al. 1999 [6]56 kidneyMean 12-hour Tac area under the concentration versus time-curve (AUC0–12) on day 2 after transplantation was significantly lower in 17 patients who experienced acute rejection than in the 39 patients who remained rejection-free
Kershner et al. 1996 [5]721 liverNo relationship between the Tac concentrations and toxicity
Laskow et al. 1996 [7]92 kidneyNo significant difference among three different Tac-ranges (5–14 ng/mL, 15–25 ng/mL and 26–40 ng/mL) with respect to the incidence of rejection
Nashan et al. 2009 [8]60 liverTac predose concentrations of 5–8 ng/mL in the first month of transplantation resulted in the same rejection rates as Tac concentrations of 10–15 ng/mL

Rodriguez et al. [9] recently performed a meta-analysis of 64 studies investigating the correlation between the Tac predose concentration and the incidence of rejection in liver transplant recipients. They concluded that the mean Tac predose concentration during the first month was not correlated with acute rejection. Nevertheless, they suggested that lower Tac predose levels would be more appropriate after liver transplantation to prevent Tac toxicity.

Despite limited evidence for performing TDM for Tac and the exact predose concentrations to aim for, in most transplant centers considerable time and effort is spent on the precise dosing of Tac in order to reach the predefined Tac target concentrations rapidly. Once on target, maintaining patients within the target concentration range also requires careful monitoring.

The aim of this study therefore was to investigate whether the currently used and empirically defined Tac target predose concentrations are indeed associated with the risk of developing acute rejection in kidney transplant recipients. We pooled the data of three large randomized-controlled trials (RCTs) and studied the relation between Tac exposure and the incidence of biopsy-proven acute rejection (BPAR).

Patients and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

Patients and clinical trials

For the present analysis we combined the data of three large, randomized-controlled clinical trials in kidney transplant recipients, the FDCC [10], Symphony [11] and OptiCept [12] trials. In brief, the main common elements of the three studies were the randomized, open-label, parallel-arm, multicenter design, and the fact that they included a broad spectrum of patients. In general, these patients had a low-to-medium immunological risk and were treated under the respective protocols for at least 1 year after kidney transplantation. In addition to adults, the FDCC and OptiCept studies enrolled pediatric patients, who were, however, not included in our analysis.

Tac target concentrations

For the present analysis we included only the patients from these three RCTs who received Tac as part of their immunosuppressive regimen from the day of transplantation and had a minimum of one known Tac level. The Tac levels were targeted differently between the studies. For the FDCC study, Tac dosing was according to each center's protocol, and on average was between 10 and 14 ng/mL in the first month, with gradual tapering thereafter. In the Symphony study, Tac levels were targeted at 3–7 ng/mL for the study period. In the OptiCept trial, the Tac predose concentrations were 8–12 ng/mL within the first month, 4–6 or 8–10 ng/mL in the second and third months (depending on the randomization group), and 3–5 or 6–8 ng/mL from the fourth month onwards. Data on Tac dose and predose concentrations, as well as other demographic and clinical characteristics were collected from the databases of the three RCTs and pooled. Tac predose concentrations were studied at day 3 (±2 days), day 10 (±2 days), day 14 (±3 days), month 1 (±7 days) and month 6 (±4 weeks). We changed the Tac levels that were higher than 30 ng/mL (24 measuring points in total) into missing values, to prevent that non-predose Tac concentrations would be included in the analysis. However, we also performed the analysis with all the Tac levels (including the ones that were higher than 30 ng/mL).

Acute rejection

BPAR was defined as any histologically confirmed episode for which a Banff score of 1 (mild, grades IA and IIA), 2 (moderate, grades IB and IIB) or 3 (severe, grade III) was recorded. In all three trials, all biopsy samples were assessed by a local pathologist, and rejection was classified according to the revised Banff grading system [13]. For the present analysis, only the first episode of BPAR was investigated. Ongoing or recurrent rejections were not studied.

Statistical analyses

The correlations between Tac concentrations and BPAR were done for BPARs occurring after the time of the Tac concentration measurement, within the remainder of the first posttransplant year tested with the nonparametric Mann–Whitney U test at the five different time points. We also did the same analysis for BPARs occurring within the month following the Tac concentration measurement, again for all five time points. We also performed a similar analysis categorizing the patients as high-risk if they had one or more of the following characteristics: delayed graft function (DGF), second or third transplantation, panel reactive antibodies (PRA) of more than 15%, four or more human leukocyte antigen (HLA) mismatches, or were of African descent (black). All other patients were considered as low-risk. We have previously used the same definition for high and low risk [14]. The significance level was stated at 5%. Induction therapy (yes/no; either ATG of anti ILR monoclonal antibody induction), HLA mismatches (<4 / ≥4), DGF (yes/no), PRA (<15 / ≥15) and number of transplant (first / ≥second transplant) were correlated with the occurrence of BPAR within 1 month and 1 year after transplantation by using the Chi-square test. To identify independent risk factors for the development of BPAR, a binary logistic regression was performed, including all the above-mentioned variables, plus median levels of Tac predose concentrations. Statistical analysis was carried out using SPSS version 19 (SPSS / IBM Inc., Chicago, IL, USA).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

Patient characteristics

In the three clinical trials a total of 1363 renal transplant patients were treated with Tac after transplantation. Of these patients, 1304 met the inclusion criteria and were used for further analysis (Figure 1). Of these 1304 patients, 358 (27%) participated in the FDCC study, 385 (30%) in the Symphony study and 561 (43%) in the Opticept study. The patient characteristics are listed in Table 2. A total of 4953 Tac predose concentrations of 1304 patients were available for the analysis (total predose concentrations of 818 on day 3; 1127 on day 10; 804 on day 14; 1167 on month 1 and 1019 on month 6). The Tac predose concentrations show a substantial range and are depicted in Figure 2(A). Twenty-four Tac concentrations were >30 ng/mL (n = 13 on day 3; n = 4 on day 14, n = 4 on month 1 and n = 3 on month 6). As we were unable to check whether these concentrations were truly predose concentrations or in fact postdose concentrations, these values were classified as “missing values” and excluded from the primary analysis.

Table 2. Patient characteristics
  1. a

    For transplantation and PRA there were missing values in 1 and 6 patients, respectively.

Gender (female/male):450 (34%)/854 (66%)
Age (year; mean [SD]):48 (13.8)
Ethnicity (%): 
Black161 (12%)
Non-Black1143 (88%)
Transplantation (first/ ≥2):1219 (94%)/84 (6%)a
Delayed graft function: Yes/No238 (18%)/1066 (82%)
Panel reactive antibodies: (<15% / ≥15%)1124 (91.5%)/105 (8.5%)a
HLA mismatches (<4 / ≥4):709 (54%)/595 (46%)
Living related donor338 (26%)
Living unrelated donor183 (14%)
Deceased donor783 (60%)
Induction therapy: Yes / No890 (68%)/414 (32%)
image

Figure 1. Included patients from the three clinical trials and reasons for exclusion from the study.

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image

Figure 2. (A) Boxplots depicting the Tac predose concentrations of all patients at the five different time points after transplantation. (B) Boxplots depicting the Tac predose concentrations of patients experiencing BPAR (black boxes) and patients without BPAR (white boxes) at the five different time points after transplantation. Bottom, middle and top lines of each box correspond to the 25th percentile, the 50th percentile (median) and the 75th percentile, respectively. The caps show the 5th and 95th percentiles. The points represent the outliers and the asterisks represent the extreme outliers (more than three times the height of the boxes).

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Relationship between Tac and BPAR

In this cohort the overall incidence of BPAR was 10.4% (n = 136) within 1 year after transplantation. The vast majority of BPARs occurred within the first month after transplantation (91/136 = 7%). We univariately tested the relationship between median Tac predose concentrations and the occurrence of BPAR within the first posttransplant year at five different time points, as shown in Table 3(A) and Figure 2(B). We did not find any significant relationship between the Tac concentration and the incidence of BPAR. The results for BPAR within the first month after the Tac measurements did show similar results: again patients who developed a BPAR had Tac predose concentrations that were not different compared to patients without a BPAR, as shown in Table 3(B). As for only 61% of the patients a Tac predose concentration was available for day 3 (Table 3A), we have studied the mean Tac predose concentration for each patient, based on samples drawn between day 3 and day 14 and correlated this to BPAR. Again, these Tac concentrations were not significantly different between patients with BPAR and patients without BPAR (10.02 vs. 9.97; p = 0.90).

Table 3. Median Tac predose concentrations and their association with BPAR occurring: (A) within the remainder of the first posttransplant year after the Tac concentration measurement and (B) within 1 month after the Tac concentration measurement
Posttransplant time pointMedian predose Tac concentration (ng/mL) in patients with BPARMedian predose Tac concentration (ng/mL) in patients without BPAR
  1. a

    The numbers show the 25th percentile, 75th percentile and the range, respectively. For all comparisons no statistically significant differences were found, all p-values were >0.05.

  2. b

    The percentage of patients of whom the Tac levels were available for analysis at this posttransplant time point. Tac concentrations were related to BPAR occurring after the date of the Tac concentration measurement.

A:
Day 3Tac: 10.3 [6.5; 17.1; 27.6]aTac: 9.5 [6.0; 14.5; 29.5]a
 n = 135 (61%)bn = 1168 (63%)b
Day 10Tac: 9.0 [7.0; 11.8; 25.8]aTac: 9.1 [6.6; 12.2; 28.2]a
 n = 92 (85%)bn = 1013 (87%)b
Day 14Tac: 7.8 [5.6; 10.4; 26.2]aTac: 8.1 [6.2; 11.4; 29.7]a
 n = 65 (72%)bn = 722 (62%)b
Month 1Tac: 8.7 [5.8; 12.7; 20.2]aTac: 9.7 [7.0; 12.5; 27.6]a
 n = 45 (84%)bn = 1050 (90%)b
Month 6Tac: 7.5 [6.3; 10.5; 11.0]aTac: 6.8 [5.3; 8.6; 23.6]a
 n = 15 (80%)bn = 924 (79%)b
B:
Day 3Tac: 11.1 [6.3; 10.5; 11.0]aTac: 9.5 [6.3; 10.5; 11.0]a
 N = 60 (66%)bN = 1212 (62%)b
Day 10Tac: 9.0 [6.3; 10.5; 11.0]aTac: 9.1 [6.3; 10.5; 11.0]a
 N = 51 (86%)bN = 1047 (87%)b
Day 14Tac: 8.5 [6.3; 10.5; 11.0]aTac: 8.1 [6.3; 10.5; 11.0]a
 N = 24 (71%)bN = 1209 (62%)b
Month 1Tac: 8.0 [6.3; 10.5; 11.0]aTac: 9.7 [6.3; 10.5; 11.0]a
 N = 7 (71%)bN = 1206 (90%)b
Month 6Tac: 7.4 [6.3; 10.5; 11.0]aTac: 6.8 [6.3; 10.5; 11.0]a
 N = 5 (100%)bN = 1178 (79%)b

The data were further analyzed by stratification into two groups: patients with a predose concentration <5 ng/mL versus patients with a predose concentration >5 ng/mL, and patients with a predose concentration <10 ng/mL versus patients with a predose concentration >10 ng/mL. The results are shown in Table 4. There were no statistically significant associations between the Tac predose concentrations and the occurrence of BPAR within 1 month after the measurement or throughout the rest of the first year after transplantation.

Table 4. Numbers of patients with: (A) Tac concentrations below or above 5 ng/mL and (B) Tac concentrations below or above 10 ng/mL at five posttransplant time points, and incidence of BPAR in these patients following that time point
A: Tac predose concentrations below or above 5 ng/mL
Time pointTac < 5 ng/mLBPARTac > 5 ng/mLBPARP-value
Day 314610 (6.8%)67173 (10.9%)0.14
Day 101297 (5.7%)96271 (7.4%)0.42
Day 14928 (8.7%)67739 (5.8%)0.27
Month 1862 (2.3%)100236 (3.6%)0.54
Month 61852 (1.1%)75110 (1.3%)0.79
B: Tac predose concentrations below or above 10 ng/mL
Time pointTac < ng/mLBPARTac > 10 ng/mLBPARP-value
Day 342640 (9.4%)39143 (11%)0.48
Day 1061949 (7.9%)47229 (6.7%)0.26
Day 1449532 (6.5%)27415 (5.5%)0.58
Month 157322 (3.8%)51516 (3.1)0.58
Month 67979 (1.1%)1393 (2.2%)0.32

To analyze the risk of BPAR further, we divided the group into high and low immunological risk patients according to the definition described earlier. The total number of patients defined as being low-risk was 499 (39%) whereas 786 (61%) patients were considered to be high-risk. Nineteen patients were not included in this analysis, because one or more of the variables needed to define their immunological risk were not known. The incidence of BPAR was higher in patients in the high-risk group (100/786 = 12.7%) compared to the low-risk group (36/499 = 7.2%), with an odds ratio of 1.9 for patients in the high-risk group versus the low-risk patients [95% CI: 1.3–2.8; p < 0.05]. First we analyzed the Tac concentrations at the different time points for the high-risk group versus the low-risk group. At all the time points the median Tac predose concentrations were not statistically significantly different between the high- and low-risk groups. We further analyzed the Tac concentrations at the different time points within the high- and low-risk group separately, as shown in Table 5. Again no significantly differences could be found between the patients who developed BPAR and patients without BPAR for the low (Table 5A) as well as for the high-risk patients (Table 5B).

Table 5. Median Tac predose concentrations at different time points after transplantation in patients with BPAR and in patients without BPAR divided into: (A) low-risk patients and (B) high-risk patients
 A: Low-risk patients (n = 499)
 Total BPAR incidence: 36/499 (7,2%)
Posttransplant Time pointMedian predose Tac concentration (ng/mL) in patients with BPARMedian predose Tac concentration (ng/mL) in patients without BPARp-Value
Day 3Tac: 10.3 [6.3; 10.5; 11.0]aTac: 10.1 [6.3; 10.5; 11.0]a0.46
 n = 17bn = 269b 
Day 10Tac: 9.5 [6.3; 10.5; 11.0]aTac: 9.0 [6.3; 10.5; 11.0]a0.68
 n = 20bn = 394b 
Day 14Tac: 8.9 [6.3; 10.5; 11.0]aTac: 7.9 [6.3; 10.5; 11.0]a0.73
 n = 11bn = 302b 
Day 3- day 14Tac: 9.2 [6.3; 10.5; 11.0]aTac: 9.2 [6.3; 10.5; 11.0]a0.63
 n = 36bn = 454b 
Month 1Tac: 10.1 [6.3; 10.5; 11.0]aTac: 9.3 [6.3; 10.5; 11.0]a0.64
 n = 10bn = 421b 
 B: High-risk patients (n = 786)
 Total incidence of BPAR: 100/786 (12,7%)
  1. a

    The numbers show the 25th percentile, 75th percentile and the range, respectively.

  2. b

    The patients from whom the Tac levels were available for analysis at this posttransplant time point. For month 6 after transplantation the number of patients was too low to perform the analysis and this time point is therefore excluded from the analysis.

Day 3Tac: 10.6Tac: 9.40.26
 n = 66bn = 454b 
Day 10Tac: 8.7Tac: 9.10.98
 n = 58bn = 600b 
Day 14Tac: 7.8Tac: 8.10.28
 n = 36bn = 402b 
Day 3- day 14Tac: 9.1Tac: 9.30.63
 n = 99bn = 673b 
Month 1Tac: 8.7Tac: 9.90.24
 n = 28bn = 614b 

We have changed the Tac levels that were higher than 30 ng/mL (24 measuring points in total) into missing values, to prevent that non predose Tac concentrations would be included in the analysis. However, we have also performed the analysis with all the Tac levels (including the ones that were higher than 30 ng/mL), but the results did not change (data not shown).

Explaining BPAR

Next to the Tac predose concentrations, in the univariate analysis, induction therapy, HLA mismatches, DGF, PRA and number of transplants were tested with the occurrence of BPAR within 1 year after transplantation. Of all 1304 patients 68% used induction therapy, and 9.6% of these patients suffered from a BPAR whereas this percentage was 12.3% in patients who did not use induction therapy after transplantation (p = 0.13). We also correlated the incidence of BPAR and the mean Tac concentration of day 3 to day 14 only within patients who did not use induction therapy. The Tac concentration in this group was not statistically different between patients with BPAR and patients without BPAR (p = 0.53). To test the influence of HLA mismatching we divided the group into patients who had 0–3 HLA mismatches versus patients who had more than three HLA mismatches. There was a significant correlation between the number of HLA mismatches and the occurrence of BPAR. In patients with more than three HLA mismatches 12.3% had BPAR versus 8.9% in patients who had 0–3 HLA mismatches (p = 0.046). Also for DGF we found a significant correlation with the occurrence of BPAR (19.7% in patients with DGF versus 8.3% in those without DGF, p < 0.001). The PRA status was not significantly related to the development of BPAR. PRA was separated into patients who had a PRA <15% and patients with a PRA >15%, in the first group 10.5% developed BPAR and in the last group 8.6% (p = 0.54). We have also studied the development of BPAR within patients who had a first kidney transplantation and compared this to patients who had one or more transplants before. Patients who had been transplanted before had a higher risk of developing BPAR (17.9%) compared with patients who received their first kidney allograft (9.9%; p = 0.021). The variables are listed in Table 6(A). Because of the different designs of the studies we have also tested the incidence of BPAR within the different studies (Symphony, Opticept and FDCC). The patients in the Opticept trial suffered significantly less from a BPAR than in the other studies (7.5% vs. 12.2% (Symphony) and 13.1% (FDCC); p = 0.01.

Table 6. Other variables related to BPAR: (A) univariate analysis and (B) multivariate analysis
A: Univariate analysis
 Patients (%)Patients with BPAR (%)p-Value
DGF18.319.7< 0.001
No DGF81.78.3 
HLA mismatches >44612.30.046
HLA mismatches <4548.9 
Number transplantation >1 6.417.90.021
Number transplantation = 193.69.9 
PRA > 15%13.88.60.54
PRA < 15%86.210.5 
Induction therapy689.60.13
No Induction therapy3212.3 
B: Multivariate analysis
 OR (95% CI)p-Value
  1. DGF = delayed graft function; PRA = panel reactive antibody.

DGF2.7 (1.8 – 4.0)0.0001
Induction0.66 (0.44 – 0.99)0.049
Mean Tac concentration day 3–day 140.98 (0.94 – 1.03)0.48
HLA mismatches <41.47 (1.02 – 2.13)0.07
Number transplantation >11.71 (0.91 – 3.23)0.09
PRA > 15%0.51 (0.17 – 1.53)0.23

In order to exclude the possibility that some of the other factors associated with the incidence of BPAR have confounded the relationship between Tac concentrations and BPAR we have adjusted for observed confounders and we performed a multivariate analysis, which included these variables, as well as the Tac concentrations. Multivariate analysis demonstrated that only DGF and the use of induction therapy were independently correlated to BPAR, with an odds ratio of 2.7 [95% CI: 1.8–4.0; p < 0.001] for DGF, and 0.66 [95% CI: 0.44–0.99; p = 0.049] for the use of induction therapy. The other variables, including the Tac predose levels, were not significantly associated with the risk of developing BPAR as shown in Table 6(B).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

We did not find a correlation between the Tac predose concentration measured at five time points after transplantation and the occurrence of acute rejection in the period thereafter, within the first posttransplant year. The same was true for BPARs within the first month following the Tac measurement. We investigated a large and heterogeneous study population, and the Tac concentrations measured showed a substantial range, despite rather tight target concentrations defined in the protocols.

The situation for Tac seems to be quite different from mycophenolic acid (MPA). For MPA, a concentration–effect relationship has been shown repetitively [15, 16] and for MPA it was also shown that in contrast to patients at low-risk for BPAR for high-risk patients there was a significant difference in the incidence of BPAR depending on the MPA concentrations reached [14]. In this study, in neither the high-risk nor in the low-risk patients the incidence of acute rejection was dependent on the Tac concentrations. A bit to our surprise the mean Tac concentrations in high-risk patients were not different from the Tac concentrations found in the low-risk population. We had expected that physicians responsible for dosing Tac would aim for higher Tac concentrations in patients considered to be at presumed higher risk for BPAR, and that they would allow for lower concentrations in patients with a lower risk of rejection. Also in the multivariate analysis the Tac concentrations did not surface as predictor for BPAR.

TDM is generally considered to be required for managing Tac therapy. Often transplant centers have specified the target concentrations for Tac, depending on time posttransplant, on comedication and presumed risk of rejection. One would think that for a drug so extensively used the evidence for the optimal Tac concentration would be compelling. We show that this is not the case. In the past 15 years we have seen a substantial change in the target Tac concentrations, with targets as high as 20 ng/mL in the early years, and with targets as low as 3–7 ng/mL in the Symphony study. This change in target concentrations was largely reached empirically, and there is only limited evidence for the different targets. This does not imply that TDM for Tac is useless. Without TDM the large between-patient variability in Tac pharmacokinetics would go unnoticed, and extremes in Tac exposure would occur, exposing some patients to toxic levels and others to very low levels. Based on our analysis however it is not possible to conclude that the Tac target concentrations should be above, for example, 5 or 10 ng/mL. Possibly the threshold for efficacy is at a concentration that is even lower than the currently applied targets, and it is possible that only when concentrations reach values as low as 1 or 2 ng/mL the incidence of BPAR starts to increase. The same was suggested by Rodriguez [9] who proposed to further lower the Tac concentration in liver transplantation. They even recommended the regulatory authorities and pharmaceutical industry to change the regulatory drug information for lowering the target levels.

This study is a combined analysis of three large clinical trials, and a large number of kidney transplant recipients was included. In spite of the considerable number of patients studied, we could not show an association between the development of acute rejection in 1 month or 1 year after transplantation and the Tac whole blood concentrations. Also adjusting for confounders in a multivariate analysis the results stayed negative. Recently Capron et al. [17] also showed that there is no correlation between Tac whole blood concentrations and rejection after liver transplantation. However, they did find a strong correlation between Tac concentrations within peripheral blood mononuclear cells (PBMCs), the site of action of Tac and the staging of rejection in liver transplant recipients. However, as indicated, the currently clinically employed assays measure the Tac concentration in whole blood, which is determined to a large extent by the Tac concentration in the erythrocyte fraction. Tac concentrations in PBMCs are not 1:1 correlated with whole blood (or erythrocyte) concentrations, for example, due to the presence of drug transporting enzymes in the cell membranes of PBMCs. Therefore Tac concentration within PBMCs might be a better marker of immunosuppressive efficacy than the whole blood predose concentration. Future studies should study the relationship between intracellular Tac concentrations and rejection risk in kidney transplant recipients in more detail.

A limitation to this study is that donor-specific anti-HLA antibodies were not routinely measured, and therefore we have no data on correlations between Tac exposure and DSA. Next to this, we had only access to Tac concentrations drawn at predefined time points. These Tac concentrations might not be the last measured concentration prior to diagnosing BPAR and we cannot exclude the possibility that a similar analysis with the last levels drawn would show an association. However, intrapatient variability of Tac is limited and we do not think that we would have achieved another outcome by using the last levels drawn. Another limitation is that the predose concentrations that were investigated in this study do not adequately reflect the exposure to Tac. Kuypers et al. in 2004 showed that in contrast to Tac predose concentrations the Tac area under the concentration curve from 0 to 12 hours [AUC(0–12)] was correlated with clinical efficacy, at different time points after transplantation [18]. However, a good correlation between Tac predose concentrations and AUC has been demonstrated. In clinical practice predose concentrations are the preferred method to monitor Tac treatment [19]. In a multivariate analysis also Australian investigators [20] did not find a correlation between Tac predose concentrations or Tac AUC and incidence of acute rejection, whereas in their study MPA-AUC was correlated to BPAR.

Another explanation might be that other mechanisms, such as innate immunity, which are not calcineurin driven might play a role in the development of acute rejections. These rejections could not be prevented by the use of calcineurin inhibitors, such as Tac and for these type of rejections it is therefore not useful to aim for a specific Tac target. Although T cells, inhibited by Tac, have a critical role in acute rejection it is known that there is an upregulation of proinflammatory mediators in the allograft before the T cell response, this is due to innate immunity and it is independent of the adaptive immune system [21].

In this study we have focused only on efficacy, as the incidence of nephrotoxicity was not prospectively collected. Therefore it is not possible from this study to define the upper threshold for Tac treatment.

In conclusion, we did not find an association between the Tac predose concentrations and the incidence of acute rejection after kidney transplantation. Even though it is generally accepted that TDM is essential to maintain the efficacy of Tac, the analysis in this study does not show that TDM, at the used whole blood target ranges, adds to lowering the risk of acute rejection. We do not want to suggest that TDM for Tac can be abolished, but a more critical perception on the relevance of the presumed optimal target concentrations is recommended.

Disclosure

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References

The authors of this manuscript have conflicts of interest to disclose as described by the American Journal of Transplantation.  Dr. D. A. Hesselink and Dr T. van Gelder have received lecture fees from Astellas Pharma. The FDCC, the Opticept study and the Symphony study were all financially supported by F. Hoffmann – la Roche.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Disclosure
  8. References