Validation and comparison of pharmacogenetics-based warfarin dosing algorithms for application of pharmacogenetic testing

Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients

Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses. In this study, percentage deviations of doses predicted by 15 Chinese dosing algorithms from that by IWPC and Gage algorithms were systematically evaluated to understand the differences between Chinese and Western algorithms. In general, dose predictions by Chinese dosing algorithms tended to be lower than those predicted by IWPC or Gage algorithms for the most prevalent VKORC1 and CYP2C9 genotypes in the Chinese population. The extent of negative prediction deviation appeared to be largest in the younger age group with smaller body weight. Our findings are consistent with previous reports that Asians have a higher sensitivity to warfarin and require lower doses than Western populations.

Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study

Background

Warfarin is well known as a narrow therapeutic index that has prodigious variability in response which challenges dosing adjustment for the maintenance of therapeutic international normalized ratio. However, an appreciated population not on new oral anticoagulants may still need to be stabilized with warfarin dosing.

Objective

The current study's main objective was to validate and compare two models of warfarin clinical algorithm models namely the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) with warfarin 5 mg fixed standard dosing strategy in a sample of Sudanese subjects.

Method

We have conducted a cross-sectional study recruited from the out-patient clinic at a tertiary specialized heart center. We included subjects with unchanged warfarin dose (stabilized), and with therapeutic international normalized ratio. The predicted doses of warfarin in the two models were calculated by three different methods (accuracy, clinical practicality, and the clinical safety of the clinical algorithms).

Main outcome measure

The primary outcomes were the measurements of the clinical (accuracy, practicality, and safety) in each of the two clinical algorithms models compared to warfarin 5 mg fixed standard dose strategy.

Results

We have enrolled 71 Sudanese subjects with mean age (51.7 ± 14 years), of which (49, 69.0%) were females. There was no significant difference between the warfarin 5 mg fixed standard dose strategy and the predicted doses of the two clinical algorithm models (MAE 1.44, 1.45, and 1.49 mg/day [P =0.4]) respectively. In the clinical practicality, all of the three models had a high percent of subjects (95.0%, 51.9%, and 66.7%) in the ideal dose range in middle dose group (3-7 mg/ day) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithm models respectively. However, a small percent of subjects was exhibited in the warfarin low dose group ≤ 3 mg/day (0.0%, 15.0%, and 10.0%) and warfarin high dose group ≥ 7 mg/day (0.0%, 33.3%, and 33.3%) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithms respectively. In terms of clinical safety, the percent of subjects with severely over-prediction were 28.2%, 22.5%, and 22.5% for warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. While the percent of severely under-prediction was 12.7%, 7.0%, and 5.6% for the warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively.

Conclusion

The Gage and IWPC clinical algorithm models were accurate, more clinically practical, and clinically safe than warfarin 5 mg standard dosing in the study population. The cardiologist can use either models (Gage and IWPC) to stratify subjects for accurate, practical, and clinically safe warfarin dosing..

Ethnic Diversity and Warfarin Pharmacogenomics

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

Pharmacogenetics in developing countries and low resource environments

While significant advances have been made in pharmacogenetics (PGx), especially in countries with developed economies, this field remains at its infancy in developing countries and low resource environments. Herein, we provide insights into the gap and challenges of PGx at the research and clinical fronts, and some perspectives to bridge the gap and move forward with PGx in the developing world. We show that developing countries fall behind in PGx research, evidenced by a lower number of researchers, citations, and research output. In addition, the implementation of PGx in the clinic has been progressing at a much slower pace than research, and more so in developing countries. To bridge this gap, we recommend fostering regional and multinational collaborations to secure funds for high-throughput genotyping and local capacity building while preserving individual countries' identity, implementing next-generation sequencing, and organizing specialized training and exchange programs to move PGx research and clinical applications forward in developing countries.

Clinical verification of Lou type warfarin pharmacokinetic dosing algorithms equation

Warfarin is the most commonly used oral anti-coagulant in clinic practice. However, it is difficult to recommend the correct dosage due to its narrow therapeutic window. The aim of the present study was to verify the clinical value of the Lou type equation, using pharmacogenetics‑based warfarin dosing algorithms to appropriately predict the actual maintenance dose. A total of 87 Chinese Han patients who required treatment with warfarin were enrolled and randomly divided into the experimental and control groups. In the experimental group, the first 3 doses of warfarin were calculated according to the Lou type equation. While in the control group, these 3 treatments were performed following the doctors' recommendations. Then the dose of warfarin was gradually adjusted to the stable dose according to the changes in the international standardized ratio. At the end of the 50 day experimental period, there were a greater number of patients in the experimental group who exhibited a stable blood concentration of warfarin than those in the control group (83.35 and 64.4%, respectively). In addition, the mean and median times for patients to obtain a stable dose in the experimental group were significantly shorter than those in the control group (mean, 18.2±1.7 and 27.3±2.0 days; and median, 11.7±1.1 and 20.5±1.8 days, respectively). The adverse reaction rate of the experimental group (9.5%) was markedly lower than that of the control group (26.7%). The occurrence of adverse reactions in the experimental group was also significantly later when compared with the control group (43.9±1.6 and 38.6±1.5 days, respectively). Furthermore, there was no significant difference between the average predicted dose (3.4±1.1 mg/day) and the average actual dose (3.5±1.4 mg/day; P=0.313). In conclusion, using the Lou type warfarin pharmacokinetic dosing algorithm equation to administer warfarin markedly shortened the adjustment time of warfarin to reach a stable dose and reduced the adverse reactions rate, thus supporting clinical feasibility.

Evaluation of CYP2C9- and VKORC1-based pharmacogenetic algorithm for warfarin dose in Gaza-Palestine

Aim

To evaluate applicability of CYP2C9*2, *3 and VKORC1-1639G > A based algorithm to predict warfarin stable dose (WSD) in a group of Palestinian patients.

Patients & methods

Warfarin doses were retrospectively calculated for 101 Palestinian patients under warfarin therapy using three models. Performance of the three models was assessed in 47 patients found to take WSD.

Results

Frequency of CYP2C9*2, *3 and VKORC1-1639G > A alleles is 13.6, 0.0 and 46.5% respectively. The international warfarin pharmacogenetics consortium algorithm was more reliable (MAE = 8.9 ± 1.4; R² = 0.350) than both the clinical algorithm (MAE = 10.4 ± 1.4; R² = 0.128;) and the fixed-dose algorithm (MAE = 11.1 ± 1.7).

Conclusion

The international warfarin pharmacogenetics consortium algorithm can be reliably applied for predicting the WSD in Palestinian population.

Estimation of the warfarin dose with a pharmacogenetic refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation

Pharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic dose more accurately;however, most of them are based on standard intensity of warfarin anticoagulation, and their utility outside this range is limited. This study was designed to develop and validate a PG refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under stable warfarin treatment were randomly divided into a derivation (n=207) and a validation cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation, respectively. In the derivation cohort, a PG algorithm was constructed on the basis of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of international normalised ratio (INR) values (INR on day 4 of therapy and target INR) and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and explained 54% of warfarin dose variability. In the validation cohort, warfarin dose prediction was more accurate (p <0.01) with the PG refinement algorithm than with the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the PG refinement algorithm could accurately identify larger proportions of patients with lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction in Chinese patients mainly under low-intensity anticoagulation.

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

Background

Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects.

Methods

Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions.

Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals.

Results

We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations.

Conclusions

Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions.

MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0495-0) contains supplementary material, which is available to authorized users.

Warfarin Dosing Algorithms Underpredict Dose Requirements in Patients Requiring ≥7 mg Daily: A Systematic Review and Meta-analysis

There is preliminary evidence to suggest that some published warfarin dosing algorithms produce biased maintenance dose predictions in patients who require higher than average doses. We conducted a meta-analysis of warfarin dosing algorithms to determine if there exists a systematic under- or overprediction of dose requirements for patients requiring ≥7 mg/day across published algorithms. Medline and Embase databases were searched up to September 2015. We quantified the proportion of over- and underpredicted doses in patients whose observed maintenance dose was ≥7 mg/day. The meta-analysis included 47 evaluations of 22 different warfarin dosing algorithms from 16 studies. The meta-analysis included data from 1,492 patients who required warfarin doses of ≥7 mg/day. All 22 algorithms were found to underpredict warfarin dosing requirements in patients who required ≥7 mg/day by an average of 2.3 mg/day with a pooled estimate of underpredicted doses of 92.3% (95% confidence interval 90.3-94.1, I² = 24%).

Verification of five pharmacogenomics-based warfarin administration models

Objective:

This study aims to screen and validate five individual warfarin dosing models (four Asian model algorithms, namely, Ohno, Wen, Miao, Huang, and the algorithm of International Warfarin Pharmacogenetic Consortium, namely IWPC algorithm) with the aim of evaluating their accuracy, practicality, and safety.

Materials and Methods:

Patients’ CYP2C9*3 and VKORC1–1639G >A genes were genotyped, and patient-related information and steady warfarin doses were recorded. The difference between the predicted dose and actual maintenance dose of each model was compared.

Results:

The prediction accuracies of the Huang and Wen models were the highest. In terms of clinical practicality, the Huang model rated the highest for the low-dose group, whereas the Ohno and IWPC models rated the highest for the middle-dose group. The models tended to markedly overpredict the doses in the low-dose group, especially the IWPC model. The Miao model tended to severely underpredict the doses in the middle-dose group, whereas no model exhibited severe overprediction.

Conclusions:

Since none of the models ranked high for all the three criteria considered, the impact of various factors should be thoroughly considered before selecting the most appropriate model for the region's population.

Pharmacogenetic-guided Warfarin Dosing Algorithm in African-Americans

We aim to develop warfarin dosing algorithm for African-Americans. We explored demographic, clinical, and genetic data from a previously collected cohort of 163 African-American patients with a stable warfarin dose. We explored 2 approaches to develop the algorithm: multiple linear regression and artificial neural network (ANN). The clinical significance of the 2 dosing algorithms was evaluated by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual dose. Linear regression model and ANN model predicted the ideal dose in 52% and 48% of the patients, respectively. The mean absolute error using linear regression model was estimated to be 10.8 mg compared with 10.9 mg using ANN. Linear regression and ANN models identified several predictors of warfarin dose including age, weight, CYP2C9 genotype *1/*1, VKORC1 genotype, rs12777823 genotype, rs2108622 genotype, congestive heart failure, and amiodarone use. In conclusion, we developed a warfarin dosing algorithm for African-Americans. The proposed dosing algorithm has the potential to recommend warfarin doses that are close to the appropriate doses. The use of more sophisticated ANN approach did not result in improved predictive performance of the dosing algorithm except for patients of a dose of ≥49 mg/wk.

A systematic analysis and comparison of warfarin initiation strategies

OBJECTIVE

Randomized trials have reported inconsistent evidence on the effectiveness of algorithms that use genotypes to initiate warfarin therapy. The Clarification of Optimal Anticoagulation through Genetics (COAG) trial initiated therapy on the basis of predicted maintenance doses, with a pharmacogenetic-guided algorithm in one study group and a clinically guided algorithm in the other. The European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) consortium initiated therapy on the basis of loading doses, with an algorithm-based prediction in one study group and a fixed-dose regimen in the other. To understand the differences between these trials, we compared the initial doses between alternative dosing algorithms (the pharmacogenetic-guided and clinically guided algorithms developed by Gage and colleagues and those developed by the International Warfarin Pharmacogenetics Consortium) and between the COAG and EU-PACT dose-initiation strategies.

METHODS

This was a secondary analysis of the COAG trial - a double-blind, randomized-controlled trial (2009-2013) - conducted at 18 clinical centers in the USA, which included 1010 adults initiating warfarin therapy, of whom 719 achieved maintenance dose.

RESULTS

Among COAG participants, the distribution of initial doses differed between algorithms, but showed similar prediction accuracy for maintenance dose. However, had the COAG trial implemented the EU-PACT strategy, the 3-day initial dose would have been 4.8 mg greater among participants randomized to pharmacogenetic-guided dosing, but only 2.5 mg greater among participants randomized to clinically guided dosing (P<0.001).

CONCLUSION

Compared with the COAG trial, the EU-PACT trial used systematically larger loading doses in the pharmacogenetic-guided group and might have inadequately adjusted for clinical variability in warfarin dose requirements in the fixed-dose group.

Pharmacogenomics and Global Precision Medicine in the Context of Adverse Drug Reactions: Top 10 Opportunities and Challenges for the Next Decade

In a move indicative of the enthusiastic support of precision medicine, the U.S. President Barack Obama announced the Precision Medicine Initiative in January 2015. The global precision medicine ecosystem is, thus, receiving generous support from the United States ($215 million), and numerous other governments have followed suit. In the context of precision medicine, drug treatment and prediction of its outcomes have been important for nearly six decades in the field of pharmacogenomics. The field offers an elegant solution for minimizing the effects and occurrence of adverse drug reactions (ADRs). The Clinical Pharmacogenetics Implementation Consortium (CPIC) plays an important role in this context, and it aims at specifically guiding the translation of clinically relevant and evidence-based pharmacogenomics research. In this forward-looking analysis, we make particular reference to several of the CPIC guidelines and their role in guiding the treatment of highly relevant diseases, namely cardiovascular disease, major depressive disorder, cancer, and human immunodeficiency virus, with a view to predicting and managing ADRs. In addition, we provide a list of the top 10 crosscutting opportunities and challenges facing the fields of precision medicine and pharmacogenomics, which have broad applicability independent of the drug class involved. Many of these opportunities and challenges pertain to infrastructure, study design, policy, and science culture in the early 21st century. Ultimately, rational pharmacogenomics study design and the acquisition of comprehensive phenotypic data that proportionately match the genomics data should be an imperative as we move forward toward global precision medicine.

Prediction of Warfarin Dose in Pediatric Patients: An Evaluation of the Predictive Performance of Several Models

OBJECTIVES

The objective of this study was to evaluate the performance of pediatric pharmacogenetic-based dose prediction models by using an independent cohort of pediatric patients from a multicenter trial.

METHODS

Clinical and genetic data (CYP2C9 [cytochrome P450 2C9] and VKORC1 [vitamin K epoxide reductase]) were collected from pediatric patients aged 3 months to 17 years who were receiving warfarin as part of standard care at 3 separate clinical sites. The accuracy of 8 previously published pediatric pharmacogenetic-based dose models was evaluated in the validation cohort by comparing predicted maintenance doses to actual stable warfarin doses. The predictive ability was assessed by using the proportion of variance (R(2)), mean prediction error (MPE), and the percentage of predictions that fell within 20% of the actual maintenance dose.

RESULTS

Thirty-two children reached a stable international normalized ratio and were included in the validation cohort. The pharmacogenetic-based warfarin dose models showed a proportion of variance ranging from 35% to 78% and an MPE ranging from -2.67 to 0.85 mg/day in the validation cohort. Overall, the model developed by Hamberg et al showed the best performance in the validation cohort (R(2) = 78%; MPE = 0.15 mg/day) with 38% of the predictions falling within 20% of observed doses.

CONCLUSIONS

Pharmacogenetic-based algorithms provide better predictions than a fixed-dose approach, although an optimal dose algorithm has not yet been developed.

Prediction of sensitivity to warfarin based on VKORC1 and CYP2C9 polymorphisms in patients from different places in Colombia

INTRODUCTION

In the search to prevent hemorrhages associated with anticoagulant therapy, a major goal is to validate predictors of sensitivity to warfarin. However, previous studies in Colombia that included polymorphisms in the VKORC1 and CYP2C9 genes as predictors reported different algorithm performances to explain dose variations, and did not evaluate the prediction of sensitivity to warfarin. 

OBJECTIVE

To determine the accuracy of the pharmacogenetic analysis, which includes the CYP2C9 *2 and *3 and VKORC1 1639G>A polymorphisms in predicting patients' sensitivity to warfarin at the Hospital Militar Central, a reference center for patients born in different parts of Colombia. 

MATERIALS AND METHODS

Demographic and clinical data were obtained from 130 patients with stable doses of warfarin for more than two months. Next, their genotypes were obtained through a melting curve analysis. After verifying the Hardy-Weinberg equilibrium of the genotypes from the polymorphisms, a statistical analysis was done, which included multivariate and predictive approaches. 

RESULTS

A pharmacogenetic model that explained 52.8% of dose variation (p<0.001) was built, which was only 4% above the performance resulting from the same data using the International Warfarin Pharmacogenetics Consortium algorithm. The model predicting the sensitivity achieved an accuracy of 77.8% and included age (p=0.003), polymorphisms *2 and *3 (p=0.002) and polymorphism 1639G>A (p<0.001) as predictors. 

CONCLUSIONS

These results in a mixed population support the prediction of sensitivity to warfarin based on polymorphisms in VKORC1 and CYP2C9 as a valid approach in Colombian patients.

Poor warfarin dose prediction with pharmacogenetic algorithms that exclude genotypes important for African Americans

OBJECTIVES

Recent clinical trial data cast doubt on the utility of genotype-guided warfarin dosing, specifically showing worse dosing with a pharmacogenetic versus clinical dosing algorithm in African Americans. However, many genotypes important in African Americans were not accounted for. We aimed to determine whether omission of the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype affects performance of dosing algorithms in African Americans.

METHODS

In a cohort of 274 warfarin-treated African Americans, we examined the association between the CYP2C9*5, CYP2C9*6, CYP2C9*8, CYP2C9*11 alleles and rs12777823 G > A genotype and warfarin dose prediction error with pharmacogenetic algorithms used in clinical trials.

RESULTS

The http://www.warfarindosing.org algorithm overestimated doses by a median (interquartile range) of 1.2 (0.02-2.6) mg/day in rs12777823 heterozygotes (P<0.001 for predicted vs. observed dose), 2.0 (0.6-2.8) mg/day in rs12777823 variant homozygotes (P = 0.004), and 2.2 (0.5-2.9) mg/day in carriers of a CYP2C9 variant (P < 0.001). The International Warfarin Pharmacogenetics Consortium (IWPC) algorithm underdosed warfarin by 0.8 (-2.3 to 0.4) mg/day for patients with the rs12777823 GG genotype (P < 0.001) and overdosed warfarin by 0.7 (-0.4 to 1.9) mg/day in carriers of a variant CYP2C9 allele (P = 0.04). Modifying the http://www.warfarindosing.org algorithm to adjust for variants important in African Americans led to better dose prediction than either the original http://www.warfarindosing.org (P < 0.01) or IWPC (P < 0.01) algorithm.

CONCLUSION

These data suggest that, when providing genotype-guided warfarin dosing, failure to account for variants important in African Americans leads to significant dosing error in this population.

Pharmacogenetics in Jewish populations

Spanning over 2000 years, the Jewish population has a long history of migration, population bottlenecks, expansions, and geographical isolation, which has resulted in a unique genetic architecture among the Jewish people. As such, many Mendelian disease genes and founder mutations for autosomal recessive diseases have been discovered in several Jewish groups, which have prompted recent genomic studies in the Jewish population on common disease susceptibility and other complex traits. Although few studies on the genetic determinants of drug response variability have been reported in the Jewish population, a number of unique pharmacogenetic variants have been discovered that are more common in Jewish populations than in other major racial groups. Notable examples identified in the Ashkenazi Jewish (AJ) population include the vitamin K epoxide reductase complex subunit 1 (VKORC1) c.106G>T (p.D36Y) variant associated with high warfarin dosing requirements and the recently reported cytochrome P450 2C19 (CYP2C19) allele, CYP2C19*4B, that harbors both loss-of-function [*4 (c.1A>G)] and increased-function [*17 (c.-806C>T)] variants on the same haplotype. These data are encouraging in that like other ethnicities and subpopulations, the Jewish population likely harbors numerous pharmacogenetic variants that are uncommon or absent in other larger racial groups and ethnicities. In addition to unique variants, common multi-ethnic variants in key drug metabolism genes (e.g., ABCB1, CYP2C8, CYP2C9, CYP2C19, CYP2D6, NAT2) have also been detected in the AJ and other Jewish groups. This review aims to summarize the currently available pharmacogenetics literature and discuss future directions for related research with this unique population.

Extrapolation of acenocoumarol pharmacogenetic algorithms

INTRODUCTION

Acenocoumarol (ACN) has a narrow therapeutic range that is especially difficult to control at the start of its administration. Various dosing pharmacogenetic-guided dosing algorithms have been developed, but further work on their external validation is required. The aim of this study was to evaluate the extrapolation of pharmacogenetic algorithms for ACN as an alternative to the development of a specific algorithm for a given population.

MATERIAL AND METHODS

The predictive performance, deviation, accuracy, and clinical significance of five pharmacogenetic algorithms (EU-PACT, Borobia, Rathore, Markatos, Krishna Kumar) were compared in 189 stable ACN patients representing all indications for anticoagulant treatment.

RESULTS

The correlation between the dose predictions of the five pharmacogenetic models ranged from 7.7 to 70.6% and the percentage of patients with a correct prediction (deviation ≤20% from actual ACN dose) ranged from 5.9 to 40.7%. EU-PACT and Borobia pharmacogenetic dosing algorithms were the most accurate in our setting and evidenced the best clinical performance.

CONCLUSIONS

Among the five models studied, the EU-PACT and Borobia pharmacogenetic dosing algorithms demonstrated the best potential for extrapolation.

Oral anticoagulation: a critique of recent advances and controversies

There have recently been significant advances in the field of oral anticoagulation, but these have also led to many controversies. Warfarin is still the commonest drug used for clotting disorders but its use is complicated owing to wide inter-individual variability in dose requirement and its narrow therapeutic index. Warfarin dose requirement can be influenced by both genetic and environmental factors. Two recent randomized controlled trials (RCTs) came to different conclusion regarding the utility of genotype-guided dosing; we critically explore the reasons for the differences. The new generation of oral anticoagulants have been demonstrated to be as efficacious as warfarin, but further work is needed to evaluate their safety in real clinical settings.

A review of a priori regression models for warfarin maintenance dose prediction

A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.

Verification of pharmacogenetics-based warfarin dosing algorithms in Han-Chinese patients undertaking mechanic heart valve replacement

OBJECTIVE

To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement.

METHODS

We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms.

RESULTS

A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges.

CONCLUSIONS

All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.

Improvement of anticoagulant treatment using a dynamic decision support algorithm: a Danish Cohort study

INTRODUCTION

Warfarin is the most widely prescribed vitamin K antagonist and in the United States and Europe more than 10 million people are currently in long-term oral anticoagulant treatment. This study aims to retrospectively validate a dynamic statistical model providing dosage suggestions to patients in warfarin treatment.

MATERIALS AND METHODS

The model was validated on a cohort of 553 patients with a mean TTR of 83%. Patients in the cohort were self-monitoring and managed by a highly specialised anticoagulation clinic. The predictive model essentially consists of three parts handling INR history, warfarin dosage and biological noise, which allows for prediction of future INR values and optimal warfarin dose to stay on INR target. Further, the model is based on parameters initially being set to population values and gradually individualised during monitoring of patients.

PRIMARY OUTCOME

Time in therapeutic range was used as surrogate quality measure of the treatment, and model-suggested dosage of warfarin was used to assess the accuracy of the model performance.

RESULTS

The accuracy of the model predictions measured as median absolute error was 0.53 mg/day (interquartile range from 0.25 to 1.0). The model performance was evaluated by the difference between observed and predicted warfarin intake in the preceding week of an INR measurement. In more than 70% of the cases where INR measurements were outside the therapeutic range, the model suggested a more reasonable dose than the observed intake.

CONCLUSION

Applying the proposed dosing algorithm can potentially further increase the time in INR target range beyond 83%.

Pathway analysis of genome-wide data improves warfarin dose prediction

BACKGROUND

Many genome-wide association studies focus on associating single loci with target phenotypes. However, in the setting of rare variation, accumulating sufficient samples to assess these associations can be difficult. Moreover, multiple variations in a gene or a set of genes within a pathway may all contribute to the phenotype, suggesting that the aggregation of variations found over the gene or pathway may be useful for improving the power to detect associations.

RESULTS

Here, we present a method for aggregating single nucleotide polymorphisms (SNPs) along biologically relevant pathways in order to seek genetic associations with phenotypes. Our method uses all available genetic variants and does not remove those in linkage disequilibrium (LD). Instead, it uses a novel SNP weighting scheme to down-weight the contributions of correlated SNPs. We apply our method to three cohorts of patients taking warfarin: two European descent cohorts and an African American cohort. Although the clinical covariates and key pharmacogenetic loci for warfarin have been characterized, our association metric identifies a significant association with mutations distributed throughout the pathway of warfarin metabolism. We improve dose prediction after using all known clinical covariates and pharmacogenetic variants in VKORC1 and CYP2C9. In particular, we find that at least 1% of the missing heritability in warfarin dose may be due to the aggregated effects of variations in the warfarin metabolic pathway, even though the SNPs do not individually show a significant association.

CONCLUSIONS

Our method allows researchers to study aggregative SNP effects in an unbiased manner by not preselecting SNPs. It retains all the available information by accounting for LD-structure through weighting, which eliminates the need for LD pruning.

The population attributable fraction as a measure of the impact of warfarin pharmacogenetic testing

AIM

We aimed to estimate the population impact of warfarin pharmacogenetic testing (WPGT) across multiple populations.

MATERIALS & METHODS

We used the expanded International Warfarin Pharmacogenetics Consortium data set and genotype frequencies from HapMap to simulate dose distributions for each CYP2C9/VKORC1 genotype combination in the different races, and calculated the population attributable fraction as a measure of population impact of WPGT. WPGT was compared to both clinical and fixed-dose algorithms to estimate the benefits of WPGT.

RESULTS

Our dose simulation revealed different dose requirements in difference races and considerable overlap in dose distributions of different genotype combinations. Population attributable fraction calculations suggest that complete implementation of WPGT can reduce inaccurate dosing by 18-24% in white individuals. However black, Japanese and Chinese patients do not benefit from WPGT, especially when compared against a race-specific fixed dose.

CONCLUSION

Our findings support WPGT in white individuals but not in black, Japanese and Chinese individuals.

Effect of genetic variants, especially CYP2C9 and VKORC1, on the pharmacology of warfarin

The genes encoding the cytochrome P450 2C9 enzyme (CYP2C9) and vitamin K-epoxide reductase complex unit 1 (VKORC1) are major determinants of anticoagulant response to warfarin. Together with patient demographics and clinical information, they account for approximately one-half of the warfarin dose variance in individuals of European descent. Recent prospective and randomized controlled trial data support pharmacogenetic guidance with their use in warfarin dose initiation and titration. Benefits from pharmacogenetics-guided warfarin dosing have been reported to extend beyond the period of initial dosing, with supportive data indicating benefits to at least 3 months. The genetic effects of VKORC1 and CYP2C9 in African and Asian populations are concordant with those in individuals of European ancestry; however, frequency distribution of allelic variants can vary considerably between major populations. Future randomized controlled trials in multiethnic settings using population-specific dosing algorithms will allow us to further ascertain the generalizability and cost-effectiveness of pharmacogenetics-guided warfarin therapy. Additional genome-wide association studies may help us to improve and refine dosing algorithms and potentially identify novel biological pathways.

Validation of pharmacogenetic algorithms and warfarin dosing table in Egyptian patients

BACKGROUND

Warfarin remains a difficult drug to use due to the large variability in dose response. Clear understanding of the accuracy of warfarin pharmacogenetic dosing methods might lead to appropriate control of anticoagulation.

OBJECTIVE

This study aims to evaluate the accuracy of warfarin dosing table and two pharmacogenetic algorithms, namely the algorithms of Gage et al. (Clin Pharmacol Ther 84:326-331, 2008), and the International Warfarin Pharmacogenetics Consortium algorithm (IWPC) in a real Egyptian clinical setting. Additionally, three non-pharmacogenetic dosing methods (the Gage, IWPC clinical algorithms and the empiric 5 mg/day dosing) were evaluated.

SETTING

Sixty-three Egyptian patients on a stable therapeutic warfarin dose were included. Patients were recruited from the outpatient clinic of the critical care medicine department.

METHODS

CYP2C9 and VKORC1 polymorphisms were genotyped by real time PCR system. Predicted doses by all dosing methods were calculated and compared with the actual therapeutic warfarin doses.

RESULTS

The Gage algorithm (adjusted R(2) = 0.421, and mean absolute error (MAE) = 3.3), and IWPC algorithm (adjusted R(2) = 0.419, MAE = 3.2) produced better accuracy than did the warfarin dosing table (adjusted R(2) = 0.246, MAE = 3.5), the two clinical algorithms (R(2) = 0.24, MAE = 3.7) and the fixed dose approach (MAE = 3.9). However, all dosing models produced comparable clinical accuracy with respect to proportion of patients within 1 mg/day of actual dose (ideal dose). Non-pharmacogenetic methods severely over-predicted dose (defined as ≥2 mg/day more than actual dose) compared to the three pharmacogenetic models. In comparison to non-pharmacogenetic methods, the three pharmacogenetic models performed better regarding the low dose group in terms of percentage of patients within ideal dose. In the high dose group, none of the dosing models predicted warfarin doses within ideal dose.

CONCLUSION

Our study showed that genotype-based dosing improved prediction of warfarin therapeutic dose beyond that available with the fixed-dose approach or the clinical algorithms, especially in the low-dose group. However, the two pharmacogenetic algorithms were the most accurate.

Validation of warfarin pharmacogenetic algorithms in clinical practice

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.

Bioinformatics and variability in drug response: a protein structural perspective

Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk-benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein-drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein-drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants.

Role of pharmacogenomics in the management of traditional and novel oral anticoagulants

Warfarin is the most commonly prescribed oral anticoagulant. However, it remains a difficult drug to manage mostly because of its narrow therapeutic index and wide interpatient variability in anticoagulant effects. Over the past decade, there has been substantial progress in our understanding of genetic contributions to variable warfarin response, particularly with regard to warfarin dose requirements. The genes encoding for cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) are the major genetic determinants of warfarin pharmacokinetics and pharmacodynamics, respectively. Numerous studies have demonstrated significant contributions of these genes to warfarin dose requirements. The CYP2C9 gene has also been associated with bleeding risk with warfarin. The CYP4F2 gene influences vitamin K availability and makes minor contributions to warfarin dose requirements. Less is known about genes influencing warfarin response in African-American patients compared with other racial groups, but this is the focus of ongoing research. Several warfarin pharmacogenetic dosing algorithms and United States Food and Drug Administration-cleared genotyping tests are available for clinical use. Clinical trials are ongoing to determine the clinical utility and cost-effectiveness of genotypeguided warfarin dosing. Results from these trials will likely influence clinical uptake and third party payer reimbursement for genotype-guided warfarin therapy. There is still a lack of pharmacogenetic data for the newly approved oral anticoagulants, dabigatran and rivaroxaban, and with other oral anticoagulants in the research and development pipeline. These data, once known, could be of great importance as routine monitoring parameters for these agents are not available.

Prediction of warfarin dose: why, when and how?

Prediction models are the key to individualized drug therapy. Warfarin is a typical example of where pharmacogenetics could help the individual patient by modeling the dose, based on clinical factors and genetic variation in CYP2C9 and VKORC1. Clinical studies aiming to show whether pharmacogenetic warfarin dose predictions are superior to conventional initiation of warfarin are now underway. This review provides a broad view over the field of warfarin pharmacogenetics from basic knowledge about the drug, how it is monitored, factors affecting dose requirement, prediction models in general and different types of prediction models for warfarin dosing.

Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record

AIM

Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European-Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose.

PATIENTS & METHODS

We used BioVU, the Vanderbilt EHR-linked DNA repository, to identify European-Americans (n = 1022) and African-Americans (n = 145) on stable warfarin therapy and evaluated the effect of 15 pharmacogenetic variants on stable warfarin dose.

RESULTS

Associations between variants in VKORC1, CYP2C9 and CYP4F2 with weekly dose were observed in European-Americans as well as additional variants in CYP2C9 and CALU in African-Americans. Compared with traditional 5 mg/day dosing, implementing the US FDA recommendations or the International Warfarin Pharmacogenomics Consortium (IWPC) algorithm reduced error in weekly dose in European-Americans (13.5-12.4 and 9.5 mg/week, respectively) but less so in African-Americans (15.2-15.0 and 13.8 mg/week, respectively). By further incorporating associated variants specific for European-Americans and African-Americans in an expanded algorithm, dose-prediction error reduced to 9.1 mg/week (95% CI: 8.4-9.6) in European-Americans and 12.4 mg/week (95% CI: 10.0-13.2) in African-Americans. The expanded algorithm explained 41 and 53% of dose variation in African-Americans and European-Americans, respectively, compared with 29 and 50%, respectively, for the IWPC algorithm. Implementing these predictions via dispensable pill regimens similarly reduced dosing error.

CONCLUSION

These results validate EHR-linked DNA biorepositories as real-world resources for pharmacogenomic validation and discovery.

Copy number variation and warfarin dosing: evaluation of CYP2C9, VKORC1, CYP4F2, GGCX and CALU

AIM

To determine if copy number variants contribute to warfarin dose requirements, we investigated CYP2C9, VKORC1, CYP4F2, GGCX and CALU for deletions and duplications in a multiethnic patient population treated with therapeutic doses of warfarin.

PATIENTS & METHODS

DNA samples from 178 patients were subjected to copy number analyses by multiplex ligation-dependent probe amplification or quantitative PCR assays. Additionally, the CYP2C9 exon 8 insertion/deletion polymorphism (rs71668942) was examined among the patient cohort and 1750 additional multiethnic healthy individuals.

RESULTS

All patients carried two copies of CYP2C9 by multiplex ligation-dependent probe amplification and no exon 8 deletion carriers were detected. Similarly, quantitative PCR assays for VKORC1, CYP4F2, GGCX and CALU identified two copies in all populations.

CONCLUSION

These data indicate that copy number variants in the principal genes involved in warfarin dose variability (CYP2C9, VKORC1), including genes with lesser effect (CYP4F2, GGCX), and those that may be more relevant among certain racial groups (CALU), are rare in multiethnic populations, including African-Americans.

Cardiovascular pharmacogenomics

Patients vary in their responses to drug therapy, and some of that variability is genetically determined. This review outlines general approaches used to identify genetic variation that influences drug response. Examples from specific therapeutic areas are presented, such as cholesterol management, arrhythmias, heart failure, hypertension, warfarin anticoagulation, and antiplatelet agents. A brief view of potential pathways to implementation is presented.

A cost effectiveness analysis of thiopurine methyltransferase testing for guiding 6-mercaptopurine dosing in children with acute lymphoblastic leukemia

BACKGROUND

An increased understanding of the genetic basis of disease creates a demand for personalized medicine and more genetic testing for diagnosis and treatment. The objective was to assess the incremental cost-effectiveness per life-month gained of thiopurine methyltransferase (TPMT) genotyping to guide doses of 6-mercaptopurine (6-MP) in children with acute lymphoblastic leukemia (ALL) compared to enzymatic testing and standard weight-based dosing.

PROCEDURE

A cost-effectiveness analysis was conducted from a health care system perspective comparing costs and consequences over 3 months. Decision analysis was used to evaluate the impact of TPMT tests on preventing myelosuppression and improving survival in ALL patients receiving 6-MP. Direct medical costs included laboratory tests, medications, physician services, pharmacy and inpatient care. Probabilities were derived from published evidence. Survival was measured in life-months. The robustness of the results to variable uncertainty was tested in one-way sensitivity analyses. Probabilistic sensitivity analysis examined the impact of parameter uncertainty and generated confidence intervals around point estimates.

RESULTS

Neither of the testing interventions showed a benefit in survival compared to weight-based dosing. Both test strategies were more costly compared to weight-based dosing. Incremental costs per child (95% confidence interval) were $277 ($112, $442) and $298 ($392, $421) for the genotyping and phenotyping strategies, respectively, compared to weight-based dosing.

CONCLUSIONS

The present analysis suggests that screening for TPMT mutations using either genotype or enzymatic laboratory tests prior to the administration of 6-MP in pediatric ALL patients is not cost-effective.

Comparison of warfarin pharmacogenetic dosing algorithms in a racially diverse large cohort

AIMS

Multiple warfarin pharmacogenetic dosing algorithms have been reported to date. However, there is only limited information available on the performance of the algorithms that can be used with the results of a US FDA-cleared warfarin pharmacogenetic test. We compared the performance of warfarin pharmacogenetic dosing algorithms in a large racially diverse cohort.

MATERIALS & METHODS

Warfarin pharmacogenetic dosing algorithms were identified using the PubMed database. Patient information from the International Warfarin Pharmacogenetics Consortium database was used to predict therapeutic warfarin doses according to each algorithm. By using bootstrapping analysis, the performance of algorithms was tested by comparing the mean absolute error and mean percentage of patients whose predicted dose fell within 20% of actual dose (percentage within 20%) in the entire cohort, and by race and therapeutic dose range.

RESULTS

A total of 13 algorithms and 1940 patients were included in the study. Overall, all the algorithms had similar performances (mean absolute error: 10.3 mg/week and mean percentage within 20%-41.4%). However, algorithms derived from racially mixed populations tended to perform better than those derived from single race populations. Mixed population algorithms had the lowest mean absolute error and the highest percentage within 20% across the racial groups. Most algorithms performed better in the intermediate-dose range (between 21 and 49 mg/week) than in the low (≤21 mg/week) or high-(≥49 mg/week) range.

CONCLUSION

Published warfarin pharmacogenetic algorithms performed similarly, although mixed population algorithms tended to perform better than race-specific algorithms.

Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia

Genetic markers displaying highly significant statistical associations with complex phenotypes may not necessarily possess sufficient clinical validity to be useful. Understanding the contribution of these markers beyond readily available clinical biomarkers is particularly important in pharmacogenetics. We demonstrate the utility of genetic testing using the example of warfarin in a multi-ethnic setting comprising of three Asian populations that are broadly representative of the genetic diversity for half of the population in the world, especially as distinct interethnic differences in warfarin dose requirements have been previously established. We confirmed the roles of three well-established loci (CYP2C9, VKORC1 and CYP4F2) in explaining warfarin dosage variation in the three Asian populations. In addition, we assessed the relationship between ethnicity and the genotypes of these loci, observing strong correlations at VKORC1 and CYP4F2. Subsequently, we established the additional utility of these genetic factors in predicting warfarin dose beyond ethnicity and clinical biomarkers through performing a series of systematic cross-validation analyses of the relative predictive accuracies of various fixed-dose regimen, clinical and genetic models. Through a pharmacogenetics model for warfarin, we show the importance of genetic testing beyond readily available clinical biomarkers in predicting dose requirements, confirming the role of genetic profiling in personalized medicine.

Proposal of pharmacogenetics-based warfarin dosing algorithm in Korean patients

Warfarin is a commonly prescribed anticoagulant drug for the prevention of thromboembolic disorders. We investigated the contribution of genetic variations of four genes and clinical factors to warfarin dose requirement and provided a warfarin-dosing algorithm based on genetic and clinical variables in Korean patients. We recruited 564 Korean patients on stable anticoagulation. Single nucleotide polymorphisms (SNPs) for the VKORC1, CYP2C9, CYP4F2 and GGCX were analyzed. Using multiple regression analysis, we developed a model to predict the warfarin requirement. The SNPs of VKORC1, CYP2C9, CYP4F2 and GGCX showed significant correlation with warfarin dose. Patients with the 3730AA genotype received significantly higher doses of warfarin than those with the 3730GG (P=0.0001). For CYP2C9, the highest maintenance dose was observed in the patients with wild-type genotype compared with the variant allele carriers (P<0.0001). The multiple regression model including age, gender, body surface area (BSA), international normalized ratio (INR) and four genetic polymorphisms accounted for 35% of total variations in warfarin dose (R(2)=0.3499; P<0.0001). This study shows that age, gender, BSA, INR and VKORC1, CYP2C9 and CYP4F2 polymorphism affect warfarin dose requirements in Koreans. Translation of this knowledge into clinical guidelines for warfarin prescription may contribute to improve the efficacy and safety of warfarin treatment for Korean patients.

Testing of VKORC1 and CYP2C9 alleles to guide warfarin dosing. Test category: pharmacogenomic (treatment)

Warfarin is an oral anticoagulant that is widely prescribed to prevent thromboembolic events in persons at increased risk. The optimal dose is difficult to establish because it can vary 10-fold among individuals due to clinical and demographic factors. Testing for variants of the vitamin K epoxide reductase complex 1 (VKORC1) and cytochrome P450 2C9 (CYP2C9) genes has been proposed for use in guiding the initial dose of warfarin, thus achieving optimal dosing more quickly and with lower risk of bleeding.