High intra-patient variability (IPV) of tacrolimus levels is associated with poor long-term outcome after transplantation. We aimed to evaluate whether the number of regularly prescribed medications is associated with the tacrolimus IPV. We have studied 152 kidney transplant recipients (KTRs) with mean post-transplant time of 6.0 ± 3.1 years. The coefficient of variation (CV) as a measure of IPV was calculated in each individual patient. Data concerning the type and number of currently prescribed medications were collected. The participants were divided into four groups, based on the number of regularly prescribed drugs (≤3, 4–6, 7–9, ≥10 drugs, respectively). There was an increasing trend for median CV, proportional to the increasing number of medications [group 1: 0.11 (interquartile range, 0.08–0.14), group 2: 0.14 (0.01–0.17), group 3: 0.17 (0.14–0.23), group 4: 0.17 (0.15–0.30); p value for trend = 0.001]. Stepwise backward multivariate regression analysis revealed that the number of medications [partial correlation coefficient (r_partial) = 0.503, p < 0.001] independently influenced the tacrolimus IPV. Concomitant steroid or diuretics use increased IPV only in Advagraf-treated KTRs, whereas proton-pump inhibitor or statin use increased IPV in the Prograf group but not in the Advagraf group. A large number of concomitant medications significantly increases the tacrolimus IPV in stable KTRs.

In kidney transplant recipients (KTRs), uraemia-induced central nervous system damage partly subsides, while the long-lasting exposure to tacrolimus may cause pathologic visual evoked potentials (VEP) findings, which have not been investigated yet. Thus, the aim of the present study was to assess the effect of tacrolimus maintenance treatment on bioelectrical function of optic nerves in stable KTRs. Sixty-five stable KTRs were enrolled, including 30 patients treated with twice-daily (Prograf) and 35 patients treated with prolonged once-daily (Advagraf) tacrolimus formulation. In all patients, pattern and flash VEP measurements were performed. Tacrolimus dosing and exposure were also analyzed. Overall, 129 eyes were analyzed. In pattern VEP, both (1°) and (15′) latencies of P100 waves were significantly longer, whereas (1°) and (15′) amplitudes were lower in the Advagraf group as compared with the Prograf group. Multivariate regression analyses revealed that the use of Advagraf (vs. Prograf) was independently associated with longer (1°) and (15′) P100 latencies and lower corresponding amplitudes, whereas log tacrolimus daily dose was only related to amplitudes in a whole study group. In flash VEP, log tacrolimus trough level was associated with negative changes in P2 wave amplitude irrespective of tacrolimus formulation, whereas its association with P2 latency was observed only in the Prograf group. Both the type of tacrolimus formulation and drug exposure influenced the VEP parameters in stable KTRs.

High intrapatient variability (IPV) of tacrolimus trough levels is associated with poor long-term outcome after transplantation. Polypharmacy, related to the high co-morbidity, may affect the pharmacokinetics of tacrolimus in a substantial proportion of kidney transplant recipients (KTRs). We aimed to evaluate whether the number of regularly prescribed medications is associated with the tacrolimus IPV. We studied 152 tacrolimus-treated KTRs with mean post-transplant time 6.0±3.1 years, without dosing changes over the consecutive 2 years. The coefficient of variation (CV) as a measure IPV was calculated in each patient. Data concerning the type (generic name) and number of currently prescribed medications were collected. The participants were divided into 4 groups, based on the number of regularly prescribed drugs (≤3; 4-6; 7-9; ≥10). The median daily pill burden was 6.2±2.5 (ranged 2 to 15). There was an increasing trend for median CV, proportional to the increasing number of medications [group 1: 0.11 (IQR 0.08-0.14); group 2: 0.14 (0.01-0.17); group 3: 0.17 (0.14-0.23); group 4: 0.17 (0.15-0.30); p value for trend = 0.001]. Stepwise backward multivariate regression analysis revealed that the number of medications [partial correlation coefficient (r_partial) = 0.503; p<0.001], age [r_partial = -0.150; p=0.07] and eGFR [r_partial = -0.140; p=0.09] independently influenced the tacrolimus IPV (R²=0.30). Concomitant steroids or diuretics use increased IPV only in Advagraf-treated KTRs, whereas PPIs or statin use increased IPV in Prograf, but not Advagraf group. The number of medications is positively associated with tacrolimus IPV in stable KTRs. There were also tacrolimus formulation-dependent differences in the assumed influence of several concomitantly received classes of medications, including steroids, diuretics, PPIs and statins, on the tacrolimus IPV.