The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool

Aim This research aims to evaluate the predictive performance of a published allopurinol dosing tool. Methods Allopurinol dose predictions were compared to the actual dose required to achieve serum urate (SU) <0.36 mmol l−1 using mean prediction error. The influence of patient factors on dose predictions was explored using multilinear regression. Results Allopurinol doses were overpredicted by the dosing tool; however, this was minimal in patients without diuretic therapy (MPE 63 mg day−1, 95% CI 40–87) compared to those receiving diuretics (MPE 295 mg day−1, 95% CI 260–330, P < 0.0001). ABCG2 genotype (rs2231142, G>T) had an important impact on the dose predictions (MPE 201, 107, 15 mg day−1 for GG, GT and TT, respectively, P < 0.0001). Diuretic use and ABCG2 genotype explained 53% of the variability in prediction error (R2 = 0.53, P = 0.0004). Conclusions The dosing tool produced acceptable maintenance dose predictions for patients not taking diuretics. Inclusion of ABCG2 genotype and a revised adjustment for diuretics would further improve the performance of the dosing tool.