Toward better outcomes with tacrolimus therapy: population pharmacokinetics and individualized dosage prediction in adult liver transplantation.
Patient outcomes in transplantation would improve if dosing of immunosuppressive agents was individualized. The aim of this study is to develop a population pharmacokinetic model of tacrolimus in adult liver transplant recipients and test this model in individualizing therapy. Population analysis was performed on data from 68 patients. Estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F) using the nonlinear mixed effects model program (NONMEM). Factors screened for influence on these parameters were weight, age, sex, transplant type, biliary reconstructive procedure, postoperative day, days of therapy, liver function test results, creatinine clearance, hematocrit, corticosteroid dose, and interacting drugs. The predictive performance of the developed model was evaluated through Bayesian forecasting in an independent cohort of 36 patients. No linear correlation existed between tacrolimus dosage and trough concentration (r(2) = 0.005). Mean individual Bayesian estimates for CL/F and V/F were 26.5 +/- 8.2 (SD) L/hr and 399 +/- 185 L, respectively. CL/F was greater in patients with normal liver function. V/F increased with patient weight. CL/F decreased with increasing hematocrit. Based on the derived model, a 70-kg patient with an aspartate aminotransferase (AST) level less than 70 U/L would require a tacrolimus dose of 4.7 mg twice daily to achieve a steady-state trough concentration of 10 ng/mL. A 50-kg patient with an AST level greater than 70 U/L would require a dose of 2.6 mg. Marked interindividual variability (43% to 93%) and residual random error (3.3 ng/mL) were observed. Predictions made using the final model were reasonably nonbiased (0.56 ng/mL), but imprecise (4.8 ng/mL). Pharmacokinetic information obtained will assist in tacrolimus dosing; however, further investigation into reasons for the pharmacokinetic variability of tacrolimus is required.
Staatz
Christine E
CE
School of Pharmacy, University of Queensland, Princess Alexandra Hospital, Queensland, Australia. c.staatz@pharmacy.uq.edu.au
Willis
Charlene
C
Taylor
Paul J
PJ
Lynch
Stephen V
SV
Tett
Susan E
SE
D000328:Adult; D001499:Bayes Theorem; D004305:Dose-Response Relationship, Drug; D006801:Humans; D007166:Immunosuppressive Agents / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use*; D016031:Liver Transplantation; D008875:Middle Aged; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D016559:Tacrolimus / Q000008:administration & dosage / Q000493:pharmacokinetics / Q000627:therapeutic use*; D016896:Treatment Outcome
D007166:Immunosuppressive Agents; D016559:Tacrolimus