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

This research aims to evaluate the predictive performance of a published allopurinol dosing tool. 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. Allopurinol doses were over-predicted by the dosing tool, however, this was minimal in patients without diuretic therapy (MPE 63mg day-1 , 95%CI 40-87) compared to those receiving diuretics (MPE 295mg 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, 15mg day-1 for GG, GT and TT, respectively, p<0.0001). Diuretic use and ABCG2 genotype explained 53% if the variability in prediction error (R2 =0.53, p=0.0004). 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.