Total plasma protein effect on tacrolimus elimination in kidney transplant patients – Population pharmacokinetic approach
Graphical abstract
Introduction
Tacrolimus is a potent, calcineurin inhibitor widely used for the prevention of acute and chronic allograft rejections in kidney transplant recipients (Bowman and Brennan, 2008). It has a narrow therapeutic window with wide inter-individual variability in clearance and other pharmacokinetic parameters (Staatz and Tett, 2004). In blood, it is extensively bound to erythrocytes with a mean blood to plasma ratio of about 15, while in plasma, tacrolimus is associated principally with α1-acid glycoprotein (AAG), lipoproteins, globulins and albumin (Staatz and Tett, 2004, Venkataramanan et al., 1995, Warty et al., 1991). Haematocrit is one of the factors that influence tacrolimus blood to plasma ratio (Staatz and Tett, 2004).Tacrolimus is a highly metabolised drug, with only about 0.5% unchanged parent drug appearing in urine or feces (Staatz and Tett, 2004, Venkataramanan et al., 1995). The drug is metabolized mainly by P450 3A isoenzymes (CYP3A) which expression varies widely (Koch et al., 2002, Staatz and Tett, 2004). Additionally, tacrolimus is a substrate of P-glycoprotein (Jeong and Chiou, 2006). The significant relation between the high within-patient variability in the clearance of tacrolimus and long-term graft failure was shown (Borra et al., 2010). There is evidence that low trough blood tacrolimus concentrations correlate with increased risk of rejection, whereas higher trough levels are associated with increased risk of toxicity (Borobia et al., 2009, Kershner and Fitzsimmons, 1996, Staatz et al., 2001, Venkataramanan et al., 2001). Nevertheless, some studies failed to establish a relation between tacrolimus trough concentration and graft rejection (Gaber et al., 1997, Jain et al., 1991). In addition, the correlation between tacrolimus dose and concentration is poor (Venkataramanan et al., 2001). These findings limit optimal titrations of the dosage regimen, and require additional information on the factors that affect the pharmacokinetic characteristics of the drug. The influence of some factors such as time after transplantation, haematocrit, albumin, corticosteroid therapy, liver function, diurnal variation, race and genetic polymorphism were acknowledged (Antignac et al., 2007, Han et al., 2013, Hesselink et al., 2003, Li et al., 2007, Macphee et al., 2002, Staatz and Tett, 2004, Staatz et al., 2002, Undre and Schafer, 1998). However, the results are often contradictory. Some studies correlated increase of clearance with post transplant day, whereas other had opposite results (Antignac et al., 2007, Antignac et al., 2005, Han et al., 2013, Passey et al., 2011, Staatz et al., 2002). Furthermore, the effects of a variety of factors on tacrolimus elimination remain inconclusive. Therefore, we studied the effect of demographic and clinical factors such as graft origin, dialysis before transplantation, period after transplantation, serum creatinine, haematocrit, total proteins and hepatic enzymes, using data from routine therapeutic drug monitoring (TDM). Our objective was to define the significant factors of tacrolimus pharmacokinetic variability and develop a model for estimation of clearance to be used in transplant patient care.
Section snippets
Patients and data collection
A retrospective analysis of data from 105 adult kidney transplant recipients from the Nephrology Clinic, Clinical Center of Serbia, University of Belgrade, was performed. Patients’ data during TDM were retrospectively collected. Approval for the study was obtained from the Ethics Committee of Clinical Center of Serbia. All data were collected from the patients’ charts, and they included following covariates: gender (GEND), age, body weight (WT), day after transplantation (PDAY), graft origin
Patients characteristics
Data from 105 kidney transplant recipients (62 males and 43 females) were collected retrospectively during the maximum 6 months after transplantation. Seventy-five kidney grafts were taken from living donors and thirty from cadaveric donors. The mean time to initiation of tacrolimus treatment was 2.6 days. Patient and therapy characteristics are presented in Table 1, Table 2.
Population pharmacokinetics
Data for modeling included 1999 trough blood concentrations (Fig. 1). Interindividual variability was evaluated by an
Discussion
In the present study, we have evaluated tacrolimus population pharmacokinetic parameters in adult kidney transplant recipients, and identified the factors affecting its pharmacokinetics. An one-compartment open model with first-order absorption and elimination was optimal for data modeling, as previously reported (Antignac et al., 2007, Han et al., 2013, Staatz et al., 2002, Zhang et al., 2008).
The results of the study indicate that tacrolimus CL/F, and consequently average steady-state
Conclusion
The findings of this study explore various factors of tacrolimus pharmacokinetic variability. This is the first study that quantifies the effect of total plasma proteins on tacrolimus elimination. Our study demonstrates the feasibility of estimation of individual pharmacokinetics parameters of tacrolimus based on sparse TDM data. Furthermore, development of a Bayesian estimator based on our model would enable the accurate prediction of tacrolimus dose which would offer evidence based guidance
Acknowledgements
This work was conducted as a part of the project Experimental and Clinical-Pharmacological Investigations of Mechanisms of Drug Action and Interactions in Nervous and Cardiovascular System (No. 175023) funded by Ministry of Education, Science and Technological Development, Belgrade, Republic of Serbia.
We are very grateful to Dr. Radmila Blagojevic Lazic and the stuff from Nephrology Clinic, Clinical Centre of Serbia, University of Belgrade, Serbia for their assistance.
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