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Mycophenolate Mofetil Dose Adjustment in Pediatric Kidney Transplant Recipients.

Therapeutic Drug Monitoring 2023 Februrary 23
BACKGROUND: The Immunosuppressant Bayesian Dose Adjustment web site aids clinicians and pharmacologists involved in the care of transplant recipients; it proposes dose adjustments based on the estimated area under the concentration-time curve (AUCs). Three concentrations (T20 min, T1 h, and T3 h) are sufficient to estimate mycophenolic acid (MPA) AUC0-12 h in pediatric kidney transplant recipients. This study investigates mycophenolate mofetil (MMF) doses and MPA AUC values in pediatric kidney transplant recipients, and target exposure attainment when the proposed doses were followed, through a large-scale analysis of the data set collated since the inception of the Immunosuppressant Bayesian Dose Adjustment web site.

METHODS: In this study, 4051 MMF dose adjustment requests, corresponding to 1051 patients aged 0-18 years, were retrospectively analyzed. AUC calculations were performed in the back office of the Immunosuppressant Bayesian Dose Adjustment using published Bayesian and population pharmacokinetic models.

RESULTS: The first AUC request was posted >12 months posttransplantation for 41% of patients. Overall, only 50% had the first MPA AUC0-12 h within the recommended 30-60 mg h/L range. When the proposed dose was not followed, the proportion of patients with an AUC in the therapeutic range for MMF with cyclosporine or tacrolimus at the subsequent request was lower (40% and 45%, respectively) than when it was followed (58% and 60%, respectively): P = 0.08 and 0.006, respectively. Furthermore, 3 months posttransplantation, the dispersion of AUC values was often lower at the second visit when the proposed doses were followed, namely, P = 0.03, 0.003, and 0.07 in the 4 months-1 year, and beyond 1 year with <6-month or >6-month periods between both visits, respectively.

CONCLUSIONS: Owing to extreme interindividual variability in MPA exposure, MMF dose adjustment is necessary; it is efficient at reducing such variability when based on MPA AUC.

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