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

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.
Pharmacology 2016;98:229-241

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