Genetic, Clinical and Behavioural Determinants of Vitamin K‐Antagonist Dose – Explored Through Multivariable Modelling and Visualization

Abstract

Vitamin K antagonists (VKA) are highly effective anticoagulants but their use is hampered by multiple interactions with food and medicine and a narrow therapeutic range. The large variation in dose requirements has led to the development of several dosing algorithms based on pharmacogenetic and clinical variables. In contrast, evidence about the influence of behavioural (i.e. diet and exercise) and socio-psychological factors is sparse. To investigate the impact of pharmacogenetic, clinical, behavioural and socio-psychological factors on maintenance dose of VKA. In a cross-sectional study, we interviewed 250 consecutive patients from an anticoagulant clinic and subsequently measured pharmacogenetic and anthropometric variables. Statistical analyses were carried out using linear regression and multivariable models with visualization features. In both types of analyses, the strongest determinants of VKA dose were polymorphisms in the VKORC1 and CYP2C9 genes and age. Half of the variation in VKA dose could be explained by a linear regression model including four variables, while a multivariable model with 20 pharmacogenetic and clinical variables explained 60%. A multivariable model including 94 predictor variables was not notably better regarding predictive performance, but visualization of this model offered information about the correlation structure between predictor variables. The strongest determinants of VKA dose are well-known pharmacogenetic variables and age. The variables describing health-related behaviour and socio-psychological factors are strongly inter-correlated and not useful in dosing algorithms.Vitamin K antagonists (VKA) are effective and widely used oral anticoagulants [1]. In Denmark, warfarin and less commonly phenprocoumon are prescribed for the prevention of thromboembolic complications in patients with mechanical heart valves or atrial fibrillation (AF) combined with co-morbid conditions [2,3] or for preventing the recurrence of venous thromboembolic disorders. VKA treatment has to be monitored frequently and carefully [4], because fluctuations of the international normalized ratio (INR) [5] outside the designated range are strongly correlated with haemorrhagic or thromboembolic events [6][7][8]. On the population level, INR control [9,10] can be improved and the number of bleedings or thromboses reduced [11] by computer-assisted dosage of VKA in the setting of specialized anticoagulant clinics [12].One of the serious challenges associated with the management of VKA treatment is a large inter-individual variation in maintenance dose. Much of the variability can be ascribed to genetic polymorphisms, importantly those in the VKORC1 gene [13], coding for the enzyme inhibited by VKA, and the CYP2C9 gene [14] coding for the cytochrome P450 enzyme mainly responsible for warfarin clearance. Furthermore, clinical factors such as age, weight and use of certain co-medications influence maintenance dose in a robust and predictable manner. Multiple dosing algorithms have been developed base...

Effect of Genetic Variants, Especially CYP2C9 and VKORC1, on the Pharmacology of Warfarin

“…1,36 Despite these advances, a considerable degree of uncharacterized variability still existed, and studies aimed at delineating these variables ensued. 13,37 Of variables that affect warfarin dose variance, age accounts for 7% and its effects have been found consistent in different studies and validated across ethnic groups. 13,[38][39][40][41] Flexible dosing protocols have been developed that adjust for age.…”

“…13,37 Of variables that affect warfarin dose variance, age accounts for 7% and its effects have been found consistent in different studies and validated across ethnic groups. 13,[38][39][40][41] Flexible dosing protocols have been developed that adjust for age. 34 Nongenetic, complex environmental variables including drug and food interactions, serum vitamin K levels, and clinical factors (e.g., renal and hepatic function, presence of malignancy), among others, have been correlated in some studies.…”

“…6,7 Due to the wide interindividual variability and narrow therapeutic index of warfarin, [8][9][10] there has been considerable interest in identifying genetic and nongenetic variables that affect warfarin dose requirements. [11][12][13][14] Initially developed to accelerate the rate with which therapeutic levels of anticoagulation were achieved, fixeddose algorithms have successively been superseded by more sophisticated clinical algorithms based on patient demographics and other clinical variables 15 ; however, the success in ameliorating variability has been modest. Recently, pharmacogenetic testing of candidate genes important in warfarin pharmacodynamics (e.g., vitamin K-epoxide reductase complex unit 1 [VKORC1]) and pharmacokinetics (e.g., the cytochrome P450 2C9 enzyme [CYP2C9]) have yielded encouraging results in dose initiation and titration, [16][17][18] with potential for cost savings and reduction of length of hospitalization.…”

The influence of VKORC1 3730 G > A polymorphism on warfarin dose: reply

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Dear Sirs, Skov et al object that the effect of the variant allele rs7294 which is associated with higher warfarin requirements is not relevant in our dosing algorithm, its effect being significant at the univariate but not at the multivariate analysis.Skov et al also show that there is not a complete linkage disequilibrium but a significant correlation between rs 7294 and the variant allele rs 9934438 which is associated with warfarin sensitivity, based on the data of their study [1]. The frequency of the variant allele rs 7294 was 9.6% in their study vs 7.3% in our derivation group and 10% in the validation group.

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“…Skov et al also show that there is not a complete linkage disequilibrium but a significant correlation between rs 7294 and the variant allele rs 9934438 which is associated with warfarin sensitivity, based on the data of their study [1]. The frequency of the variant allele rs 7294 was 9.6% in their study vs 7.3% in our derivation group and 10% in the validation group.…”