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The impact of diuretic use and ABCG2 genotype on the predictive performance of a published allopurinol dosing tool
Author(s) -
Wright Daniel F. B.,
Dalbeth Nicola,
PhippsGreen Amanda J.,
Merriman Tony R.,
Barclay Murray L.,
Drake Jill,
Tan Paul,
Horne Anne,
Stamp Lisa K.
Publication year - 2018
Publication title -
british journal of clinical pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.216
H-Index - 146
eISSN - 1365-2125
pISSN - 0306-5251
DOI - 10.1111/bcp.13516
Subject(s) - dosing , allopurinol , diuretic , medicine , gout , pharmacology
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 ( R 2 = 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.