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Multicenter Study
. 2011 Dec;72(6):948-57.
doi: 10.1111/j.1365-2125.2011.04039.x.

Dosing Equation for Tacrolimus Using Genetic Variants and Clinical Factors

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Free PMC article
Multicenter Study

Dosing Equation for Tacrolimus Using Genetic Variants and Clinical Factors

Chaitali Passey et al. Br J Clin Pharmacol. .
Free PMC article

Abstract

Aim: To develop a dosing equation for tacrolimus, using genetic and clinical factors from a large cohort of kidney transplant recipients. Clinical factors and six genetic variants were screened for importance towards tacrolimus clearance (CL/F).

Methods: Clinical data, tacrolimus troughs and corresponding doses were collected from 681 kidney transplant recipients in a multicentre observational study in the USA and Canada for the first 6 months post transplant. The patients were genotyped for 2,724 single nucleotide polymorphisms using a customized Affymetrix SNP chip. Clinical factors and the most important SNPs (rs776746, rs12114000, rs3734354, rs4926, rs3135506 and rs2608555) were analysed for their influence on tacrolimus CL/F.

Results: The CYP3A5*1 genotype, days post transplant, age, transplant at a steroid sparing centre and calcium channel blocker (CCB) use significantly influenced tacrolimus CL/F. The final model describing CL/F (l h(-1)) was: 38.4 ×[(0.86, if days 6-10) or (0.71, if days 11-180)]×[(1.69, if CYP3A5*1/*3 genotype) or (2.00, if CYP3A5*1/*1 genotype)]× (0.70, if receiving a transplant at a steroid sparing centre) × ([age in years/50](-0.4)) × (0.94, if CCB is present). The dose to achieve the desired trough is then prospectively determined using the individuals CL/F estimate.

Conclusions: The CYP3A5*1 genotype and four clinical factors were important for tacrolimus CL/F. An individualized dose is easily determined from the predicted CL/F. This study is important towards individualization of dosing in the clinical setting and may increase the number of patients achieving the target concentration. This equation requires validation in an independent cohort of kidney transplant recipients.

Figures

Figure 1
Figure 1
Tacrolimus doses and troughs by CYP3A5 genotype (○ CYP3A5*3/*3, ▵ CYP3A5*1/*3, □ CYP3A5*1/*1) over the first 6 months post transplant. (A) Total daily doses by CYP3A5 genotype. (B) Trough concentrations by CYP3A5 genotype (mean ± SE)
Figure 2
Figure 2
Goodness-of-fit plots for the final tacrolimus model: IPRED, individual predicted concentrations (ng ml−1); WRES, weighted residuals
Figure 3
Figure 3
Post hoc estimates of tacrolimus CL/F from the final model over the first 6 months post transplant by CYP3A5 genotype (○ CYP3A5*3/*3, ▵ CYP3A5*1/*3, □ CYP3A5*1/*1)

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