Tacrolimus Pharmacokinetics in Lung Transplantation: New Strategies for Monitoring

Ragette, R.; Kamler, Markus; Weinreich, Gerhard; Teschler, Helmut; Jakob, Heinz

doi:10.1016/j.healun.2004.09.001

Cited by 27 publications

(26 citation statements)

References 19 publications

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“…Models from previous studies were tested by using the Chinese liver transplant patients data in the present study, we found there was good correlation between AUC 0-12Pred and AUC 0-12Obs (r 2 = 0.880-0.928) [19][20][21][23][24][25] . The percentage of profiles for which PE fell within ±15% was similar compared with our equations (31.9-70.2%).…”

Section: Models Compared With Other Studysupporting

confidence: 53%

“…The models obtained from previous studies including liver [24] , renal [19][20][21] , heart [22] and lung [23] transplant patients were tested using our data. There was good correlation between AUC 0-12 predicted by using models from references and AUC 0-12 observed in our study (r 2 = 0.880-0.928).…”

Section: Discussionmentioning

confidence: 99%

“…Besides, models from previous studies including 2-4 time points were used to test the prediction of concentration data from liver transplant patients in the present study. The models selected for testing were established based on data from pediatric [24] and adult [25] liver transplant recipients, renal transplant recipients [19][20][21] , heart transplant recipients [22] and lung transplant recipients [23] . The immunosuppressive regimens are similar, including TAC and mycophenolate mofetil (MMF) [21,23,24] ; TAC, MMF and steroid [19,20] ; TAC, MMF and azathioprine [22] .…”

Section: Cyp3a5 Abcb1 Genotypingmentioning

confidence: 99%

“…It is the most frequently used LSS method. Most of the studies on LSS of TAC through MRA assay were carried out in stable renal transplant patients [15][16][17][18][19][20][21] , the studies on heart [22] , lung [23] and liver [24,25] transplant patients are relatively minor. It has been suggested that patient demographics including patients' genetic background and transplant type, concomitant medications, biopharmaceutical drug formulation may influence the prediction performance of LSS model [26] .…”

Section: Introductionmentioning

confidence: 99%

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Limited Sampling Strategy for the Estimation of Tacrolimus Area Under the Concentration-Time Curve in Chinese Adult Liver Transplant Patients

Liu

Xu²,

Chen³

et al. 2016

Pharmacology

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Objectives: Limited sampling strategies (LSS) have been proposed as an alternative method for estimating area under concentration-time curve (AUC) of immunosuppressive agent tacrolimus (TAC). In this study, we aimed to develop the LSS models for predicting AUC of TAC in Chinese liver transplant patients. Methods: Twenty-eight adult liver transplant patients receiving immunosuppressive regimen including TAC were enrolled. A total of 47 pharmacokinetic profiles were obtained after 1 or 3 weeks therapy. TAC concentrations were determined before dose (0 h) and at 1, 1.5, 2, 2.5, 3, 4, 6, 8 and 12 h after dosing by LC-MS/MS assay. Optimal subset regression analysis was used to establish the models for estimating TAC AUC_0-12. Prediction error (PE) and absolute PE were calculated. The agreement between predicted and measured AUC_0-12 was investigated by Bland-Altman analysis. The obtained models were validated by bootstrap analysis. The prediction performance among various CYP3A5 and ABCB1 genotypes was compared. The models selected from previous published studies were also validated using our data. Results: Twenty-eight models including 1, 2, 3 and 4 blood time points sampling were established (r² = 0.653-0.979). The best model for prediction of TAC AUC_0-12 was 0.81 + 1.73C₁ + 1.32C₂ + 3.87C₄ + 3.75C₈ (r² = 0.979). Forty profiles (85.1%) had estimated TAC AUC_0-12 within ±15% of observed TAC AUC_0-12. Model with C₀-C₂ (r² = 0.880) can be used for outpatients who need monitoring to be carried out in a short period. We also found that ABCB1 genotype may be a reason of variation in the prediction performance. There was good correlation between predicted and measured AUC_0-12 (r² = 0.880-0.928) by using models from previous studies with sample collected within 4 h post dose. Conclusion: The LSS is an effective approach for estimation of full TAC AUC_0-12 in Chinese liver transplant patients.

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Section: Models Compared With Other Studysupporting

confidence: 53%

Section: Discussionmentioning

confidence: 99%

Section: Cyp3a5 Abcb1 Genotypingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Limited Sampling Strategy for the Estimation of Tacrolimus Area Under the Concentration-Time Curve in Chinese Adult Liver Transplant Patients

Liu

Xu²,

Chen³

et al. 2016

Pharmacology

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“…Based on our previous pilot study in stable patients on tacrolimus, AUC 0-12 value was kept at around 100-150 ng · h/ml in first 3 months and around 80-100 ng · h/ml after 3 months. Some centers also found very high coefficients of correlation between three time-point strategy and the complete AUC 0-12 [9][10][11][12][13]. The regression equation using three time-point derived in our group was: 13.3 + 1.2 · C 0 + 2.4 · C 2 + 5.6 · C 4 .…”

Section: Methodsmentioning

confidence: 53%

Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

et al. 2007

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Evaluation of limited sampling strategies for tacrolimus

Buijsch

Plas

Stolk

et al. 2007

Eur J Clin Pharmacol

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Objective In literature, a great diversity of limited sampling strategies (LSS) have been recommended for tacrolimus monitoring, however proper validation of these strategies to accurately predict the area under the time concentration curve (AUC 0-12 ) is limited. The aim of this study was to determine whether these LSS might be useful for AUC prediction of other patient populations. Methods The LSS from literature studied were based on regression equations or on Bayesian fitting using MWPHARM 3.50 (Mediware, Groningen, the Netherlands). The performance was evaluated on 24 of these LSS in our population of 37 renal transplant patients with known AUCs. The results were also compared with the predictability of the regression equation based on the trough concentrations C 0 and C 12 of these 37 patients. Criterion was an absolute prediction error (APE) that differed less than 15% from the complete AUC 0-12 calculated by the trapezoidal rule. Results Thirteen of the 18 (72%) LSS based on regression analysis were capable of predicting at least 90% of the 37 individual AUC 0-12 within an APE of 15%. Additionally, all but three LSS examined gave a better prediction of the complete AUC 0-12 in comparison with the trough concentrations C 0 or C 12 (mean 62%). All six LSS based on Bayesian fitting predicted <90% of the 37 complete AUC 0-12 correctly (mean 67%). Conclusions The present study indicated that implementation of LSS based on regression analysis could produce satisfactory predictions although careful evaluation is necessary.

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Tacrolimus Pharmacokinetics in Lung Transplantation: New Strategies for Monitoring

Cited by 27 publications

References 19 publications

Limited Sampling Strategy for the Estimation of Tacrolimus Area Under the Concentration-Time Curve in Chinese Adult Liver Transplant Patients

Limited Sampling Strategy for the Estimation of Tacrolimus Area Under the Concentration-Time Curve in Chinese Adult Liver Transplant Patients

Dried blood spot measurement: application in tacrolimus monitoring using limited sampling strategy and abbreviated AUC estimation

Evaluation of limited sampling strategies for tacrolimus

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