Aim: Febuxostat is an active xanthine oxidase (XO) inhibitor which is widely used in the treatment of hyperuricaemia. We aimed to evaluate the predictive performance of a pharmacokinetic-pharmacodynamic (PK-PD) model of the hypouricaemic effects of febuxostat.
Methods: Previously, we formulated a PK-PD model for predicting the hypouricaemic effects of febuxostat as a function of baseline serum urate levels, body weight, renal function and drug dose, using datasets reported in preapproval studies. Using an updated model with a sensitivity analysis, we examined the predictive performance of the PK-PD model, using datasets obtained from the medical records of patients who received febuxostat from March 2011 to December 2015 at Tokyo Women's Medical University Hospital. Multivariate regression analysis was performed to explore clinical variables to improve the predictive performance of the model.
Results: A total of 1199 serum urate values were retrieved from 168 patients (age: 60.5 ± 17.7 years; 71.4% male) who were receiving febuxostat as a treatment for hyperuricaemia. There was a significant correlation (r = 0.68; P < 0.01) between the serum urate levels observed and those predicted by the modified PK-PD model. A multivariate regression analysis revealed that the predictive performance of the model could be improved further by considering comorbidities (such as diabetes mellitus), estimated glomerular filtration rate (eGFR) and the coadministration of loop diuretics (r = 0.77, P < 0.01).
Conclusions: The PK-PD model may be useful for predicting individualized maintenance doses of febuxostat in real-world patients.
Keywords: chronic kidney disease; febuxostat; hyperuricaemia; pharmacometrics.
© 2018 The British Pharmacological Society.