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The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool
Daniel F B Wright1, Nicola Dalbeth2, Amanda J Phipps-Green3
1School of Pharmacy, University of Otago, Dunedin, New Zealand.
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.
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