PURPOSE: Warfarin dosing is affected by clinical and genetic variants, but the contribution of the genotype associated with warfarin resistance in pharmacogenetic algorithms has not been well assessed yet. We developed a new dosing algorithm including polymorphisms associated both with warfarin sensitivity and resistance in the Italian population, and its performance was compared with those of eight previously published algorithms. METHODS: Clinical and genetic data (CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, and VKORC1 3730 G > A) were used to elaborate the new algorithm. Derivation and validation groups comprised 55 (58.2% men, mean age 69 years) and 40 (57.5% men, mean age 70 years) patients, respectively, who were on stable anticoagulation therapy for at least 3 months with different oral anticoagulation therapy (OAT) indications. RESULTS: Performance of the new algorithm, evaluated with mean absolute error (MAE) defined as the absolute value of the difference between observed daily maintenance dose and predicted daily dose, correlation with the observed dose and R(2) value, was comparable with or slightly lower than that obtained using the other algorithms. The new algorithm could correctly assign 53.3%, 50.0%, and 57.1% of patients to the low (≤25 mg/week), intermediate (26-44 mg/week) and high (≥ 45 mg/week) dosing range, respectively. Our data showed a significant increase in predictive accuracy among patients requiring high warfarin dose compared with the other algorithms (ranging from 0% to 28.6%). CONCLUSIONS: The algorithm including VKORC1 3730 G > A, associated with warfarin resistance, allowed a more accurate identification of resistant patients who require higher warfarin dosage.
PURPOSE:Warfarin dosing is affected by clinical and genetic variants, but the contribution of the genotype associated with warfarin resistance in pharmacogenetic algorithms has not been well assessed yet. We developed a new dosing algorithm including polymorphisms associated both with warfarin sensitivity and resistance in the Italian population, and its performance was compared with those of eight previously published algorithms. METHODS: Clinical and genetic data (CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, and VKORC1 3730 G > A) were used to elaborate the new algorithm. Derivation and validation groups comprised 55 (58.2% men, mean age 69 years) and 40 (57.5% men, mean age 70 years) patients, respectively, who were on stable anticoagulation therapy for at least 3 months with different oral anticoagulation therapy (OAT) indications. RESULTS: Performance of the new algorithm, evaluated with mean absolute error (MAE) defined as the absolute value of the difference between observed daily maintenance dose and predicted daily dose, correlation with the observed dose and R(2) value, was comparable with or slightly lower than that obtained using the other algorithms. The new algorithm could correctly assign 53.3%, 50.0%, and 57.1% of patients to the low (≤25 mg/week), intermediate (26-44 mg/week) and high (≥ 45 mg/week) dosing range, respectively. Our data showed a significant increase in predictive accuracy among patients requiring high warfarin dose compared with the other algorithms (ranging from 0% to 28.6%). CONCLUSIONS: The algorithm including VKORC1 3730 G > A, associated with warfarin resistance, allowed a more accurate identification of resistant patients who require higher warfarin dosage.
Authors: P Lenzini; M Wadelius; S Kimmel; J L Anderson; A L Jorgensen; M Pirmohamed; M D Caldwell; N Limdi; J K Burmester; M B Dowd; P Angchaisuksiri; A R Bass; J Chen; N Eriksson; A Rane; J D Lindh; J F Carlquist; B D Horne; G Grice; P E Milligan; C Eby; J Shin; H Kim; D Kurnik; C M Stein; G McMillin; R C Pendleton; R L Berg; P Deloukas; B F Gage Journal: Clin Pharmacol Ther Date: 2010-04-07 Impact factor: 6.875
Authors: Christof Geisen; Matthias Watzka; Katja Sittinger; Michael Steffens; Laurynas Daugela; Erhard Seifried; Clemens R Müller; Thomas F Wienker; Johannes Oldenburg Journal: Thromb Haemost Date: 2005-10 Impact factor: 5.249
Authors: A Pavani; S M Naushad; Y Rupasree; T R Kumar; A R Malempati; R K Pinjala; R C Mishra; V K Kutala Journal: Pharmacogenomics J Date: 2011-03-01 Impact factor: 3.550
Authors: Mia Wadelius; Leslie Y Chen; Jonatan D Lindh; Niclas Eriksson; Mohammed J R Ghori; Suzannah Bumpstead; Lennart Holm; Ralph McGinnis; Anders Rane; Panos Deloukas Journal: Blood Date: 2008-06-23 Impact factor: 22.113
Authors: H Schelleman; J Chen; Z Chen; J Christie; C W Newcomb; C M Brensinger; M Price; A S Whitehead; C Kealey; C F Thorn; F F Samaha; S E Kimmel Journal: Clin Pharmacol Ther Date: 2008-07-02 Impact factor: 6.875
Authors: T E Klein; R B Altman; N Eriksson; B F Gage; S E Kimmel; M-T M Lee; N A Limdi; D Page; D M Roden; M J Wagner; M D Caldwell; J A Johnson Journal: N Engl J Med Date: 2009-02-19 Impact factor: 91.245
Authors: Sherif M M Ekladious; Marianne Samir M Issac; Sahar Abd El-Atty Sharaf; Hazem S Abou-Youssef Journal: Mol Diagn Ther Date: 2013-12 Impact factor: 4.074
Authors: Priccila Zuchinali; Gabriela C Souza; Graziella Aliti; Mariana R Botton; Lívia Goldraich; Katia G Santos; Mara H Hutz; Eliane Bandinelli; Luis E Rohde Journal: J Thromb Thrombolysis Date: 2014-04 Impact factor: 2.300
Authors: Talitha I Verhoef; William K Redekop; Ann K Daly; Rianne M F van Schie; Anthonius de Boer; Anke-Hilse Maitland-van der Zee Journal: Br J Clin Pharmacol Date: 2014-04 Impact factor: 4.335