OBJECTIVES: Since 2007, a number of transplantation centers have been routinely using an expert system for tacrolimus (TAC) dose adjustment in kidney allograft recipients, based on PK modeling and Bayesian estimation for area-under-the-curve (AUC) determination. This has allowed the setting up of a large database of TAC pharmacokinetic profiles and AUC values, a part of which was analyzed here. METHODS: We retrospectively studied 2030 requests posted by 21 different centers for routine TAC dose adjustment in 1000 different adult renal transplant patients (not enrolled in any kind of concentration-controlled clinical trial). For each request, the following information was obtained: time elapsed since transplantation, TAC daily dose, calculated AUC, and trough concentration (C0). RESULTS: The dose-standardized exposure to TAC significantly and progressively increased in the months after transplantation: from month (M) 1 to M9 C0/dose increased from 2.33 to 3.44 mcg·L(1)·mg(1) and AUC/dose from 43.1 to 64.2 mcg·h(1)·L(1)·mg(1), respectively. On the contrary, in patients beyond the first year whose C0 or AUC was in the target range, the odds of remaining in this range were high for a long time period, suggesting a low intrapatient variability in the stable phase. Regression analyses showed that the correlation between C0 and AUC was better in the first 3-month period (r(2) = 0.76) than later on (r(2) ≤ 0.67). Using the regression equations obtained, AUC ranges corresponding to different applicable C0 targets were calculated. CONCLUSIONS: From a large number of kidney graft recipients, we have estimated the relationships between C0 and AUC, modeled the evolution of TAC exposure with time and defined AUC targets that could be useful to lead further controlled-concentration trials and improve routine TAC therapeutic drug monitoring.
OBJECTIVES: Since 2007, a number of transplantation centers have been routinely using an expert system for tacrolimus (TAC) dose adjustment in kidney allograft recipients, based on PK modeling and Bayesian estimation for area-under-the-curve (AUC) determination. This has allowed the setting up of a large database of TAC pharmacokinetic profiles and AUC values, a part of which was analyzed here. METHODS: We retrospectively studied 2030 requests posted by 21 different centers for routine TAC dose adjustment in 1000 different adult renal transplant patients (not enrolled in any kind of concentration-controlled clinical trial). For each request, the following information was obtained: time elapsed since transplantation, TAC daily dose, calculated AUC, and trough concentration (C0). RESULTS: The dose-standardized exposure to TAC significantly and progressively increased in the months after transplantation: from month (M) 1 to M9 C0/dose increased from 2.33 to 3.44 mcg·L(1)·mg(1) and AUC/dose from 43.1 to 64.2 mcg·h(1)·L(1)·mg(1), respectively. On the contrary, in patients beyond the first year whose C0 or AUC was in the target range, the odds of remaining in this range were high for a long time period, suggesting a low intrapatient variability in the stable phase. Regression analyses showed that the correlation between C0 and AUC was better in the first 3-month period (r(2) = 0.76) than later on (r(2) ≤ 0.67). Using the regression equations obtained, AUC ranges corresponding to different applicable C0 targets were calculated. CONCLUSIONS: From a large number of kidney graft recipients, we have estimated the relationships between C0 and AUC, modeled the evolution of TAC exposure with time and defined AUC targets that could be useful to lead further controlled-concentration trials and improve routine TAC therapeutic drug monitoring.
Authors: Nynke M Kannegieter; Dennis A Hesselink; Marjolein Dieterich; Gretchen N de Graav; Rens Kraaijeveld; Carla C Baan Journal: Sci Rep Date: 2017-11-09 Impact factor: 4.379