Comparative performance of gene-based warfarin dosing algorithms in a multiethnic population

Abstract

Summary Background Gene-based warfarin dosing algorithms have largely been developed in homogeneous populations, and their generalizability has not been established. Objectives We sought to assess the performance of published algorithms in a racially diverse and multiethnic sample, and determine if additional clinical variables or genetic variants associated with dose could enhance algorithm performance. Patients and methods In 145 compliant patients on warfarin with a goal international normalized ratio (INR) of 2–3, stable, therapeutic doses were compared with predicted doses using 12 reported algorithms that incorporated CYP2C9 and VKORC1 variants. Additional covariates tested with each model included race, concurrent medications, medications known to interact with warfarin and previously described CYP4F2, CALU and GGCX variants. Results The mean patient age was 67 ± 14 years; 90 (62%) were male. Eighty-two (57%) were Caucasian, 28 (19%) African-American, 20 (14%) Hispanic and 15 (10%) Asian. The median warfarin dose was 35 mg per week (interquartile range 23–53 mg per week). Gene-based dosing algorithms explained 37–55% of the variation in warfarin dose requirements. Neither the addition of race, number of concurrent medications nor the number of concurrent medications interacting with warfarin enhanced algorithm performance. Similarly, consideration of CYP4F2, CALU or GGCX variant genotypes did not improve algorithms. Conclusions Existing gene-based dosing algorithms explained between approximately one-third and one-half of the variability in warfarin dose requirements in this racially and ethnically diverse cohort. Additional clinical and recently described genetic variants associated with warfarin dose did not enhance prediction in our patient population.

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

“…In agreement with a large body of similar studies [15,16], we found the rs9923231 or rs9934438 polymorphism in VKORC1, age and the *2 and *3 CYP2C9 genotypes to be the most important predictors of VKA dose in the linear regression model. Possession of variant SNP alleles was negatively associated with VKA dose, so was higher age.…”

“…Multiple dosing algorithms have been developed based on genetic and clinical information [15,16]. These algorithms are able to explain between a third and half of the variation in dose requirements [16], much more than algorithms based solely on clinical data [15,17].In contrast to the abundant evidence for genetic and clinical influences [15], little is known about the impact of individual behavioural factors on VKA dose. For example, solid evidence regarding the impact of diet [17][18][19] and exercise [20,21] is sparse.…”

“…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 based on genetic and clinical information [15,16]. These algorithms are able to explain between a third and half of the variation in dose requirements [16], much more than algorithms based solely on clinical data [15,17].…”

Accuracy assessment of pharmacogenetic algorithms for warfarin dose prediction in Chinese patients

“…We conclude that, while heterogeneity in algorithm performance exists, published algorithms explain a large proportion of variance in warfarin dose requirements. Three algorithms, Gage et [22,23], in contrast, Lubitz et al demonstrated that the two genetic polymorphisms did not enhance the performance of established algorithms [24,25]. Some potentially important non-genetic variables such as smoking, vitamin K, or alcohol were unanimously considered to affect warfarin dose requirements, which should be considered in warfarin therapeutic dose prediction using a pharmacogenetic algorithm.…”

Warfarin pharmacogenetics: A controlled dose–response study in healthy subjects

“…Warfarin dosing algorithms that include both genetic and clinical variables have been developed to estimate warfarin dose requirements, [9][10][11][12] and these are more effective than dosing either empirically or according to the information packaged with warfarin tablets. 11,13 Variant CYP2C9 alleles with reduced activity result in delayed warfarin elimination, lower therapeutic dose and greater risk of bleeding 7,14 The VKORC1 enzyme is the direct target of warfarin, and common haplotypes resulting in reduced gene expression have been associated with increased warfarin sensitivity and lower therapeutic doses.…”