AIM: The goal of this study was to evaluate the performance of four warfarin pharmacogenetic algorithms in a real clinical setting, namely the algorithms of Gage et al., Michaud et al., Wadelius et al. and the International Warfarin Pharmacogenetics Consortium algorithm. PATIENTS & METHODS: Data was obtained retrospectively for 605 patients who had initiated warfarin therapy at the Montreal Heart Institute. Warfarin dosing and International Normalized Ratio history were obtained from hospital charts and CYP2C9 and VKORC1 polymorphisms were genotyped. RESULTS: The four algorithms produced similar accuracy with mean absolute error ranging from 1.36-1.52 mg/day and adjusted R(2) from 40-44%. Gage's algorithm and Wadelius' algorithm predicted the largest proportion of patients within ± 20% of their observed stable warfarin dose. For patients requiring low doses, Gage's algorithm provided the highest proportion of patients within ideal dose range (36.3%), while Wadelius' algorithm performed the best for patients requiring high doses (37.3% of patients within ideal dose range). CONCLUSION: Our study demonstrates the value of published pharmacogenetic dosing algorithms for the prediction of warfarin doses, in particular for patients with low or high therapeutic dose requirements.
AIM: The goal of this study was to evaluate the performance of four warfarin pharmacogenetic algorithms in a real clinical setting, namely the algorithms of Gage et al., Michaud et al., Wadelius et al. and the International Warfarin Pharmacogenetics Consortium algorithm. PATIENTS & METHODS: Data was obtained retrospectively for 605 patients who had initiated warfarin therapy at the Montreal Heart Institute. Warfarin dosing and International Normalized Ratio history were obtained from hospital charts and CYP2C9 and VKORC1 polymorphisms were genotyped. RESULTS: The four algorithms produced similar accuracy with mean absolute error ranging from 1.36-1.52 mg/day and adjusted R(2) from 40-44%. Gage's algorithm and Wadelius' algorithm predicted the largest proportion of patients within ± 20% of their observed stable warfarin dose. For patients requiring low doses, Gage's algorithm provided the highest proportion of patients within ideal dose range (36.3%), while Wadelius' algorithm performed the best for patients requiring high doses (37.3% of patients within ideal dose range). CONCLUSION: Our study demonstrates the value of published pharmacogenetic dosing algorithms for the prediction of warfarin doses, in particular for patients with low or high therapeutic dose requirements.
Authors: Chaitali Passey; Angela K Birnbaum; Richard C Brundage; David P Schladt; William S Oetting; Robert E Leduc; Ajay K Israni; Weihua Guan; Arthur J Matas; Pamala A Jacobson Journal: Pharmacogenomics Date: 2012-07 Impact factor: 2.533
Authors: Erik Fung; Nikolaos A Patsopoulos; Steven M Belknap; Daniel J O'Rourke; John F Robb; Jeffrey L Anderson; Nicholas W Shworak; Jason H Moore Journal: Semin Thromb Hemost Date: 2012-10-06 Impact factor: 4.180