Bodyweight‐adjustments introduce significant correlations between CYP3A metrics and tacrolimus clearance

Tables of Links

TARGETS
Enzymes 2
CYP3

LIGANDS
Tacrolimus http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=3726	http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=388
Cholesterol http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=2352	http://www.guidetopharmacology.org/GRAC/LigandDisplayForward?ligandId=4998

These Tables list key protein targets and ligands in this article that are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY 1, and are permanently archived in the Concise Guide to PHARMACOLOGY 2015/16 2.

Vanhove et al. recently published results from an interesting study where bodyweight‐adjusted cytochrome P450 3A (CYP3A) metrics, including plasma 4β‐hydroxycholesterol:cholesterol (4βOHC/C/W), were found to explain a large part of the variability in weight‐adjusted tacrolimus oral clearance (TAC CL/F/W) in stable renal transplant recipients 3. A correlation coefficient between 4βOHC/C/W and TAC CL/F/W of 0.408 (P < 0.001) was reported, which appears promising for the potential clinical value of 4βOHC as a novel CYP3A metric and in tacrolimus dose individualization.

The authors have, without a clear rationale, chosen to weight‐adjust all the variables (/W). In their discussion, they justify this choice by ‘a strong correlation between weight and 4βOHC/C’ 3. However, the correlation between weight and 4βOHC/C is inverse, and dividing by weight will hence strengthen the correlation, not correct for it. Furthermore, there is no evidence in the literature for a linear relationship between weight and tacrolimus CL/F in renal transplanted adults, as implied by the fact that 20 out of the 22 published population pharmacokinetic studies failed to detect any relationship 4, and by that weight was not discussed as a relevant covariate for tacrolimus in the excellent review article from the same authors 5. The authors’ second argument to justify the weight‐adjustment is that ‘model fit was better when considering 4βOHC/C/W and MDZ CL/F/W as predictors of TAC CL/F/W compared with the uncorrected variables (data not shown)’. However, by nature, it is not surprising that one variable incorporating weight predicts another variable incorporating weight.

We have performed a similar study where we evaluated the ability of 4βOHC to predict tacrolimus CL/F early after renal transplantation (BJCP, submitted manuscript). We did not find a significant correlation between these variables (Figure 1A). Tacrolimus CL/F correlated poorly with weight (Figure 1B), whereas 4βOHC showed an inverse relationship with weight (Figure 1C). Had we chosen to weight‐adjust both variables in our analysis (Figure 1D, E), we would have identified a strong and clinically promising correlation between 4βOHC/W and tacrolimus CL/F/W (r = 0.46, P = 0.002, Figure 1F), similar to the results reported by Vanhove et al. This illustrates the potential pitfall of falsely detecting significant associations when transforming both axes into mathematical expressions using a joint third variable.

Figure 1.

Data from 43 renal transplant recipients at our center illustrate how a significant correlation is introduced between 4β‐hydroxycholesterol (4βOHC) and tacrolimus (Tac) apparent clearance (CL/F) by dividing both variables on bodyweight. (A) 4βOHC vs. Tac CL/F, (B) Weight vs. Tac CL/F, (C) Weight vs. 4βOHC, (D) Weight vs. weight‐adjusted (/W) Tac CL/F, (E) Weight vs. weight‐adjusted 4βOHC, (F) Weight‐adjusted 4βOHC vs. weight‐adjusted Tac CL/F

We would like to encourage Vanhove et al. to present their results without initially dividing all their variables by bodyweight. This would allow better insight into whether CYP3A metrics truly predict tacrolimus CL/F in stable renal transplant recipients and may be useful for individualizing tacrolimus dosing.

Competing Interests

All authors have completed the Unified Competing Interest form at http://www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare no competing interests.

Størset, E. , Hole, K. , Midtvedt, K. , Bergan, S. , Molden, E. , and Åsberg, A. (2017) Bodyweight‐adjustments introduce significant correlations between CYP3A metrics and tacrolimus clearance. Br J Clin Pharmacol, 83: 1350–1352. doi: 10.1111/bcp.13188.