Warfarin Dose Prediction Research Articles

Comparative performance of warfarin pharmacogenetic algorithms in Chinese patients

IntroductionMultiple warfarin pharmacogenetic algorithms have been confirmed to predict warfarin dose more accurately than clinical algorithm or the fixed-dose approach. However, their performance has never been objectively evaluated in patients under low intensity warfarin anticoagulation, which is optimal for prevention of thromboembolism in Asian patients. Material and methodsWe sought to compare the performances of 8 eligible pharmacogenetic algorithms in a cohort of Chinese patients (n=282) under low intensity warfarin anticoagulation with target international normalized ratio (INR) ranged from 1.6 to 2.5. The performance of each algorithm was evaluated by calculating the percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) between each predicted dose and actual stable dose. ResultsIn the entire cohort, the pharmacogenetic algorithms could predict warfarin dose with the average MAE of 0.87±0.17mg/day (0.73-1.17mg/day), and the average percentage within 20% of 43.8%±8.1% (29.1% - 52.1%). By pairwise comparison, warfarin dose prediction was significantly more accurate with the algorithms derived from Asian patients (48.6% – 50.0%) than those from Caucasian patients (29.1% - 39.7%; odds ratio [OR]: 1.61-3.36, p≤0.02). Algorithms with additional covariates of INR values or CYP4F2*3 performed better than those without the covariates (adding INR: OR: 1.71 (1.08-2.72), p =0.029; adding CYP4F2*3: OR: 2.67(1.41-5.05), p =0.004). When the patients were stratified according to the dose range, the algorithms from Caucasian and racially mixed populations tended to perform better in higher dose group (≥4.5mg/day), and algorithms from Asian populations performed better in intermediate dose group (1.5-4.5mg/day). None of the algorithms performed well in lower dose group (≤1.5mg/day). ConclusionsNo eligible pharmacogenetic algorithm could perform the best for all dosing range in the Chinese patients under low intensity warfarin anticoagulation. Construction of a refinement pharmacogenetic algorithm integrating 3 genotypes (CYP2C9, VKORC1 and CYP4F2) and INR data should be warranted to improve the warfarin dose prediction in such patients.

Clinical Application of Pharmacogenetic-Based Warfarin-Dosing Algorithm in Patients of Han Nationality after Rheumatic Valve Replacement: A Randomized and Controlled Trial

Background The polymorphisms of VKORC1 and CYP2C9 play increasingly important roles in the inter-individual variability in warfarin dose. This study aimed to evaluate the feasibility of clinical application of pharmacogenetic-based warfarin-dosing algorithm in patients of Han nationality with rheumatic heart disease after valve replacement in a randomized and controlled trial. Methods One hundred and one consecutive patients of Han nationality with rheumatic heart disease undergoing valve surgery were enrolled and randomly assigned to an experimental group (n=50, based on CYP2C9 and VKORC1 genotypes, pharmacogenetic-based “predicted warfarin dose” for 3 days and then was adjusted to INR until stable warfarin maintenance dose) or a control group (n=51, 2.5mg/d for 3 days and then was adjusted to INR until stable warfarin maintenance dose). All included patients were followed for 50 days after initiation of warfarin therapy. The primary end-point was the time to reach a stable warfarin maintenance dose. Results During the follow-up, 84.0% patients in the experimental group and 58.8% patients in the control group received warfarin maintenance dose. Compared with control group, patients in the experimental group had shorter mean time elapse from initiation of warfarin therapy until warfarin maintenance dose (27.5±1.8 d versus 34.7±1.8 d, p<0.001). Cox regression revealed that group (HR for experimental versus control group: 1.568, 95%CI 1.103-3.284) and age were two significant variables related to the time elapse from initiation of warfarin therapy until warfarin maintenance dose. The predicted warfarin maintenance dose was prominently correlated with the actual warfarin maintenance dose (r=0.684, p<0.001). Conclusion: Based on CYP2C9 and VKORC1 genotypes, the pharmacogenetic-based warfarin-dosing algorithm may shorten the time elapse from initiation of warfarin therapy until warfarin maintenance dose. It is feasible for the clinical application of the pharmacogenetic-based warfarin-dosing algorithm in patients of Han nationality with rheumatic heart disease after valve replacement.

A new algorithm to predict warfarin dose from polymorphisms of CYP4F2, CYP2C9 and VKORC1 and clinical variables: Derivation in Han Chinese patients with non valvular atrial fibrillation

Few pharmacogenomic dosing regimens of warfarin have been developed for Chinese patients with non valvular atrial fibrillation (NVAF). The objective of this study was to develop a new algorithm by polymorphisms of CYP2C9, VKORC1 and CYP4F2 to predict the daily stable dose of warfarin in Chinese patients with NVAF. A total of 325 Chinese NVAF patients on stable dose of warfarin with a target international normalised ratio of 1.5 to 3.0 were recruited and divided randomly into two cohorts. CYP2C9*3, VKORC1-1639, VKORC1 1173 and CYP4F2 were detected by ligase detection reaction method. The new algorithm was developed with multivariate linear regression in cohort 1 (260 patients) and assessed with Pearson Correlation Analysis (PCA) in cohort 2 (65 patients). From 260 enrolled patients, the model (R2 = 51.7%) was developed as: Dose = 3.47 - 0.022 (AGE) + 0.017 (WT) + 0.189 (PTE) - 0.283 (β-blocker) - 0.471 (AMIO) - 0.586 (CYP2C9 *1/*3) - 0.296 (VKORC1 CT) - 0.648 (VKORC1 TT) + 0.219 (CYP4F2 TT). PCA displayed that the algorithm was good (r = 0.658). The residual plots revealed that the predicted doses by the algorithm tend to be overestimated when lower doses were administered to patients and to be underestimated in higher doses. The algorithm developed by us might predict warfarin dose used by Chinese NVAF patients.

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.

Influence of CYP4F2 genotype on warfarin dose requirement–a systematic review and meta-analysis

IntroductionWarfarin is a commonly used oral anticoagulant and the dosage is individually adjusted on the basis of the international normalized ratio (INR) monitoring. It is well known that gene polymorphisms of CytochromeP450 (CYP) 2C9 gene and the vitamin K epoxide reductase complex 1 (VKORC1) were significantly associated with warfarin dose. However, the association between Cytochrome P450 4F2 (CYP4F2) polymorphism and warfarin dose requirement is still controversial. This study was to investigate the influence of the CYP4F2 polymorphism, V433M (rs2108622) on warfarin dose for patients by meta-analysis. MethodsStrict inclusion and exclusion criteria were set, and the studies prior to December 19, 2010 were searched in PubMed, EMBASE and CNKI. References were examined and experts of primary studies were consulted for additional information. Revman 5.0.2 software was used to analyze the relationship between warfarin maintenance dose and CYP4F2 polymorphism ResultsThirteen studies were included in the meta-analysis which consisted of Caucasian, Asian and African populations. Compared to individuals with the homozygous CYP4F2 genotype (CC), carriers of CT, TT genotypes required 10.0% (95% confidence interval(CI) 4.0-15.0) and 21.0% (95% CI 9.0-33.0) higher warfarin doses respectively (P value <0.05). In addition, T carriers required 11.0% (95% CI 6.0-17.0) higher warfarin dose than CC genotype. ConclusionsOur study showed that polymorphism of CYP4F2 had a moderate but statistically significant association with the variation of interindividual warfarin dose. However, whether CYP4F2 can improve the prediction of warfarin dose warrants need further investigation when combined with environmental factors.

Establishment of pharmacogenomic algorithm for predicting stable warfarin dose in Chinese patients

BackgroundGenetic variants of cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1) are known to influence warfarin dose, but the effect of other genes has not been fully elucidated....

Influence of genetic, biological and pharmacological factors on warfarin dose in a Southern Brazilian population of European ancestry

To investigate the influence of polymorphisms in CYP2C9, VKORC1, CYP4F2 and F2 genes on warfarin dose-response and develop a model including genetic and non-genetic factors for warfarin dose prediction needed for each patient. A total of 279 patients of European ancestry on warfarin medication were investigated. Genotypes for -1639G>A, 1173C>T, and 3730G>A SNPs in the VKORC1 gene, CYP2C9*2 and CYP2C9*3, 1347C>T in the CYP4F2 gene and 494C>T in the F2 gene were determined by allelic discrimination with Taqman 5'-nuclease assays. The CYP2C9*2 and CYP2C9*3 polymorphisms in the CYP2C9 gene, -1639G>A and 1173C>T in the VKORC1 gene and 494C>T in the F2 gene are responsible for lower anticoagulant doses. In contrast, 1347C>T in the CYP4F2 gene and 3730G>A in the VKORC1 gene are responsible for higher doses of warfarin. An algorithm including genetic, biological and pharmacological factors that explains 63.3% of warfarin dose variation was developed. The model suggested has one of the highest coefficients of determination among those described in the literature.

A randomized controlled trial of genotype-based Coumadin initiation

PurposeA randomized controlled trial was conducted in patients initiating warfarin to determine whether algorithms that incorporate genotypes affecting warfarin metabolism and function, and Vitamin K metabolism improve prediction of therapeutic warfarin dose and anticoagulation management. MethodsA total of 230 patients were randomized to either a clinical arm where dosing algorithms considered only clinical information or an interventional arm where dosing algorithms used clinical and genotypic variables (CYP2C9, CYP4F2, and VKORC1). Subjects in the interventional arm were genotyped within 5 hours, and the initial dose was informed by genotype. Primary endpoints were absolute prediction error relative to therapeutic dose, and time in therapeutic target range during the first 14 days. Secondary endpoints included time to stable dose in therapeutic range, time to first international normalization ratio >4, and warfarin-related adverse events. ResultsThe model including genetics more accurately identified therapeutic dose twice as often as the clinical model (65.3% vs. 34.7%) (P < 0.0001). Patients in the interventional arm did not achieve greater time in therapeutic range. Study arms were similar regarding time to international normalization ratio >4 and adverse events. ConclusionGenotype-informed dosing clearly improved prediction of therapeutic dose beyond that available with clinical parameters. Genetic information did not affect time in therapeutic target range during the first 14 days of therapy. Current management practices with the vagaries in dose adjustment after warfarin initiation exert a strong influence on traditional clinical outcomes.

High-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African Americans

With complex traits and diseases having potential genetic contributions of thousands of genetic factors, and with current genotyping arrays consisting of millions of single nucleotide polymorphisms (SNPs), powerful high-dimensional statistical techniques are needed to comprehensively model the genetic variance. Machine learning techniques have many advantages including lack of parametric assumptions, and high power and flexibility. We have applied three machine learning approaches: Random Forest Regression (RFR), Boosted Regression Tree (BRT) and Support Vector Regression (SVR) to the prediction of warfarin maintenance dose in a cohort of African Americans. We have developed a multi-step approach that selects SNPs, builds prediction models with different subsets of selected SNPs along with known associated genetic and environmental variables and tests the discovered models in a cross-validation framework. Preliminary results indicate that our modeling approach gives much higher accuracy than previous models for warfarin dose prediction. A model size of 200 SNPs (in addition to the known genetic and environmental variables) gives the best accuracy. The R(2) between the predicted and actual square root of warfarin dose in this model was on average 66.4% for RFR, 57.8% for SVR and 56.9% for BRT. Thus RFR had the best accuracy, but all three techniques achieved better performance than the current published R(2) of 43% in a sample of mixed ethnicity, and 27% in an African American sample. In summary, machine learning approaches for high-dimensional pharmacogenetic prediction, and for prediction of clinical continuous traits of interest, hold great promise and warrant further research.

Novel multi-mode ultra performance liquid chromatography–tandem mass spectrometry assay for profiling enantiomeric hydroxywarfarins and warfarin in human plasma

Coumadin (R/S-warfarin) is a commonly prescribed anticoagulant for over ∼20 million Americans. Although highly efficacious, positive clinical outcomes during warfarin therapy depend on maintaining a narrow therapeutic range for the drug. This goal is challenging due to large inter-individual variability in patient response, which has been attributed to diversity in drug metabolism. Warfarin is given as a racemic mixture and evidence suggest differences of R and S-warfarin in their therapeutic activities and metabolism. Previous investigation of warfarin metabolism has been hampered by the inability to quantify the individual enantiomers. To overcome this limitation a multi-mode LC–MS/MS method is reported. This strategy combines phenyl based reverse phase chromatography with chiral phase chromatography prior to quantitation by liquid chromatography tandem mass spectrometry. This approach was made possible through advances in UPLC technology producing narrow peaks suitable for transferring to a second column. The reported method separated individual R and S enantiomers of hydroxywarfarin and warfarin. All four possible isomers of 10-hydroxywarfarin were resolved to reveal unprecedented insights into the stereo-specific metabolism of warfarin. Characterization of the method demonstrated that it is robust and sensitive with inter-day coefficients of error between <7% and a detection limit of 2 nM in sample or 10 fmol on column for each analyte. Individual metabolites may be suitable surrogate biomarkers or predictive markers that predict warfarin dose, adverse interactions, or other important clinical outcomes during anticoagulant therapy. Consequently, the metabolite profiles obtained through this dual phase UPLC–MS/MS method are expected to increase our understanding of the role warfarin metabolism plays in patient response to therapy and yield new strategies to improve patient outcomes.

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.

Genetic Warfarin Dosing: Tables Versus Algorithms

The aim of this study was to compare the accuracy of genetic tables and formal pharmacogenetic algorithms for warfarin dosing. Pharmacogenetic algorithms based on regression equations can predict warfarin dose, but they require detailed mathematical calculations. A simpler alternative, recently added to the warfarin label by the U.S. Food and Drug Administration, is to use genotype-stratified tables to estimate warfarin dose. This table may potentially increase the use of pharmacogenetic warfarin dosing in clinical practice; however, its accuracy has not been quantified. A retrospective cohort study of 1,378 patients from 3 anticoagulation centers was conducted. Inclusion criteria were stable therapeutic warfarin dose and complete genetic and clinical data. Five dose prediction methods were compared: 2 methods using only clinical information (empiric 5 mg/day dosing and a formal clinical algorithm), 2 genetic tables (the new warfarin label table and a table based on mean dose stratified by genotype), and 1 formal pharmacogenetic algorithm, using both clinical and genetic information. For each method, the proportion of patients whose predicted doses were within 20% of their actual therapeutic doses was determined. Dosing methods were compared using McNemar's chi-square test. Warfarin dose prediction was significantly more accurate (all p < 0.001) with the pharmacogenetic algorithm (52%) than with all other methods: empiric dosing (37%; odds ratio [OR]: 2.2), clinical algorithm (39%; OR: 2.2), warfarin label (43%; OR: 1.8), and genotype mean dose table (44%; OR: 1.9). Although genetic tables predicted warfarin dose better than empiric dosing, formal pharmacogenetic algorithms were the most accurate.

New genetic variant that might improve warfarin dose prediction in African Americans

Variants in the CYP2C9 (i.e. *2 and *3) and VKORC1 (i.e. 1173C/T or -1639G/A) genes have been shown to influence warfarin dose requirements. However, these factors seem to explain less of the dose variability in African Americans who have a lower prevalence of the CYP2C9*2 and *3 and VKORC1 1173T alleles. In African Americans, the VKORC1 rs17886199 variant was statistically significantly associated with log-transformed warfarin maintenance dose, independent of the influence of VKORC1 1173C>T and CYP2C9*2 and *3. However, replication of our finding is needed to confirm the association of rs1786199 SNP in African Americans, since Limdi et al.[3] did not examine the effect of this SNP because the prevalence of the rs1786199 A-allele was too low. To raise hypotheses with regards to whether genetic variants in the VKORC1, CYP2C9, EPHX1, GGCX and ALB genes might influence warfarin dose in African Americans and Caucasians, independent of the effects of the VKORC1 1173C>T and CYP2C9*2 and *3 variants. From a prospective cohort study, we obtained additional DNA on 36 Caucasian and 22 African American warfarin users who reached maintenance dose and genotyped them for tagSNPs (r2<0.8) in VKORC1, EPHX1, GGCX and ALB genes, and one exonic CYP2C9 SNP. Linear regression models were fitted to estimate the relationship (P value) between log-transformed maintenance dose and each SNP and the amount of the warfarin dose variability accounted for by each SNP (partial R2). In African Americans, the VKORC1 rs17886199 A-allele was associated with a lower dose (GG=46.3 mg and GA=25.6 mg; P=0.002), independent of the VKORC1 1173C>T and CYP2C9*2 and *3 variants. Even after applying Bonferroni correction, the P value would still be considered statistically significant. The VKORC1 rs17886199 variant was not found in Caucasians. In Caucasians, the EPHX1 rs1051741 T-allele was associated with a lower dose (CC=41.3 mg and CT=30.0 mg; P=0.04). The latter was no longer statistically significant after applying Bonferroni correction. Our pilot study suggests that the VKORC1 rs17886199 variant could influence warfarin maintenance dose among African Americans, even after accounting for the influence of the VKORC1 1173C>T variant. Future studies with a larger sample size will be needed to confirm our findings.

A haplotype of CYP2C9 associated with warfarin sensitivity in mechanical heart valve replacement patients

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT * CYP2C9 single nucleotide polymorphisms (SNPs) are important in safe and effective oral anticoagulation with warfarin use. * Although CYP2C9*2 and *3 are important genetic factors for the warfarin dose, one of the CYP2C9 SNPs, IVS-65G>C, has been suggested to be associated with warfarin sensitivity. However, as of yet, there has been no explanation about the possible mechanism and linkage analysis. WHAT THIS PAPER ADDS * New information on CYP2C9 SNPs and their occurrences in common haplotype structures in healthy unrelated Koreans and in individuals who require low warfarin dose after mechanical heart valve replacements (MHVRs) were studied. * Additional evidence showed that an Asian dominant haplotype consisting of -1565C>T, -1188T>C, IVS3+197G>A, IVS3-334C>T, IVS3-65G>C, IVS4-115A>G and IVS5-73A>G could be associated with a low warfarin maintenance dose in mechanical heart valve replacement (MHVR) patients. AIMS The objectives of this study were to determine the distribution of CYP2C9 variants in Koreans and investigate their association with warfarin dose requirements in patients who received MHVRs. METHODS All nine exons, intron-exon junction, and promoter region of CYP2C9 were amplified and directly sequenced in 50 healthy normal Koreans. Additional direct DNA sequencing of the CYP2C9 gene was conducted in 36 of the 267 MHVR patients who required low maintenance warfarin doses without carrying CYP2C9*3 and VKORC1 1173T mutations. The effects of CYP2C9 genetics on warfarin maintenance dose were assessed in 267 MHVR patients. RESULTS Thirty-nine single nucleotide polymorphisms (SNPs) including seven previously unidentified SNPs were identified in 50 Koreans by direct DNA sequencing. One of the CYP2C9 haplotypes exhibited an association with warfarin low dose requirement. The adjusted odds ratio for the haplotype between the low dose group and the normal subjects was 2.5 (95% confidence interval 1.05, 6.16). This haplotype consisting of -1565C>T, -1188T>C, IVS3+197G>A, IVS3-334C>T, IVS3-65G>C, IVS4-115A>G, and IVS5-73A>G was found in 15% of 36 MHVR patients who required low warfarin doses, while 4% of 50 normal healthy subjects exhibited this haplotype. One of the SNPs comprising this haplotype, -1565C>T, apparently changed a protein binding pattern as observed in electrophoretic mobility shift assay. CONCLUSION The haplotype including -1565C>T, -1188T>C, IVS3+197G>A, IVS3-334C>T, IVS3-65G>C, IVS4-115A>G, and IVS5-73A>G seems to be associated with low warfarin dose requirement and this haplotype could be considered in the development of a warfarin dose prediction model for Asian populations.

A regression model to predict warfarin dose from clinical variables and polymorphisms in CYP2C9, CYP4F2, and VKORC1: Derivation in a sample with predominantly a history of venous thromboembolism

Background Pharmacogenomic warfarin dosing has been suggested to produce more accurate dosing and an improved patient safety profile; however, very few models have been derived in patients with venous thromboembolism. We sought to develop a new algorithm to predict maintenance dose in a cohort of patients, using clinical variables and genetic polymorphism in CYP2C9, VKORC1, and CYP4F2. Methods Patients on a stable maintenance dose of warfarin, with observed dose ranging from 0.6 to 12 mg were recruited from a specialized anticoagulation clinic (Ottawa Hospital Thrombosis Clinic) with genotyping and standardized patient interviews being conducted to collect clinical and genomic variables known to impact warfarin dose. Multivariate linear regression was used to develop the model using a stepwise backwards elimination approach. Results From 249 enrolled patients with a mean clinical maintenance dose of 5.58 mg/day, a model with an R 2 of 58% was developed as: Dose = 1.85-0.048(Age) + 0.041(BMI) + 0.05(Height in cm) - 0.73(Less Exercise) - 1.13(2C9*2 Hetero) - 2.09(2C9*2 Homo) - 1.51(2C9*3 Hetero) -1.43(VKORC1 GA) - 2.86(VKORC1 AA) - 1.33(4F2 CC) -1.24(4F2 CT) - 1.46(Angiotensin II Receptor Antagonist) - 0.84(β-Blockers). Analysis of residual plots revealed that prediction errors were a function of observed maintenance dose with the model tending to predict higher doses than observed in those with low dose requirements and lower doses than observed in those with higher dose requirement. Conclusion Our study confirms the importance of the CYP4F2 polymorphism. Our model may prove useful in clinical practice but further validation studies are required before implementation into clinical practice.

The utility of general purpose versus specialty clinical databases for research: Warfarin dose estimation from extracted clinical variables

There is debate about the utility of clinical data warehouses for research. Using a clinical warfarin dosing algorithm derived from research-quality data, we evaluated the data quality of both a general-purpose database and a coagulation-specific database. We evaluated the functional utility of these repositories by using data extracted from them to predict warfarin dose. We reasoned that high-quality clinical data would predict doses nearly as accurately as research data, while poor-quality clinical data would predict doses less accurately. We evaluated the Mean Absolute Error (MAE) in predicted weekly dose as a metric of data quality. The MAE was comparable between the clinical gold standard (10.1 mg/wk) and the specialty database (10.4 mg/wk), but the MAE for the clinical warehouse was 40% greater (14.1 mg/wk). Our results indicate that the research utility of clinical data collected in focused clinical settings is greater than that of data collected during general-purpose clinical care.

Predicting warfarin maintenance dose in patients with venous thromboembolism based on the response to a standardized warfarin initiation nomogram.

Polymorphisms in the VKORC1 and CYP2C9 genes influence warfarin requirements. It has been suggested that dosing algorithms incorporating them might outperform usual care. Standardized warfarin initiation nomograms are safe and effective and patients' responses to them could be used to predict warfarin requirements without the need for genetic testing. To develop a model to predict warfarin dose requirements based on the response to a standard nomogram without using genetic testing. We included 363 outpatients with acute venous thromboembolism who were started on treatment using a standardized warfarin nomogram and achieved a stable maintenance warfarin dose defined as a dose prescribed twice consecutively after two consecutive INR measurements between 2.0 and 3.0. Linear regression was used to derive equations predicting the maintenance dose and models were validated using non-parametric bootstrapping and tested in an independent cohort. Three models were constructed for patients completing the nomogram until day 3 (warfarin dose (mg week(-1)) = Exp [2.737 + 1.896(INR(3)(-1))-0.008(Age)]; R2adj = 0.462), day 5 (warfarin dose (mg week(-1)) = Exp[2.261 + 2.412(INR(3)(-1)) -0.285(DeltaINR(5-3))]; R2adj = 0.603) and day 8 (warfarin dose (mg week(-1)) = Exp[1.574 + 1.788(INR(8)(-1)) + 0.024(cumulated warfarin dose until nomogram day 7)]; R2adj = 0.643), where Exp is the exponential function; INR3 and INR8 are the INR on days 3 or 8 of the nomogram, and DeltaINR(5-3) is the difference in the INR on days 5 and 3. All models were internally and externally validated and were accurate to within 25% of the actual dose in >60% of patients. Maintenance warfarin dose can be accurately predicted using individual response to a standard warfarin initiation nomogram without the need for costly genetic testing.

Validation of Clinical Testing for Warfarin Sensitivity: Comparison of CYP2C9-VKORC1 Genotyping Assays and Warfarin-Dosing Algorithms

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 -1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses.

SYBR Green-based real-time PCR assay for detection of VKORC1 and CYP2C9 polymorphisms that modulate warfarin dose requirement

Polymorphisms in VKORC1 (vitamin K epoxide reductase complex subunit 1) and CYP2C9 (cytochrome P450 2C9) genes are considered the major genetic factors modulating warfarin dose requirement. As a result, a rapid and economic method for genotyping patients for predicting warfarin dose could be useful in clinical applications. In this study, we developed and validated a melting temperature (T(m))-shift genotyping assay for detection of VKORC1 C1173T and CYP2C9 A1075C polymorphisms by using SYBR Green-based multiplex allele-specific PCR and consequent melting curve analysis. In this T(m)-shift genotyping assay, a GC-tail was incorporated into one of the two allele-specific primers to increase the melting temperature of PCR product, such that both alleles can be differentially detected simultaneously at their respective melting curve patterns. In total, 100 randomly selected samples of both VKORC1 and CYP2C9 genes from each genotype group determined by melting curve were validated by direct DNA sequencing and denaturing high-performance liquid chromatography (DHPLC) analysis. There was 100% concordance between the results of DNA sequencing and T(m)-shift genotyping, and 99% concordance between the results of DHPLC assay and T(m)-shift genotyping. This allele-specific PCR assay is convenient, inexpensive and will be useful for VKORC1 and CYP2C9 genotyping in a clinic laboratory.

VKORC1 Polymorphisms, Haplotypes and Haplotype Groups on Warfarin Dose Among African–Americans and European–Americans

Although the influence of VKORC1 and CYP2C9 polymorphisms on warfarin response has been studied, variability in dose explained by CYP2C9 and VKORC1 is lower among African-Americans compared with European-Americans. This has lead investigators to hypothesize that assessment of VKORC1 haplotypes may help capture a greater proportion of the variability in dose for this under-represented group. However, the inadequate representation of African-Americans and the assessment of a few VKORC1 polymorphisms have hindered this effort. To determine if VKORC1 haplotypes or haplotype groups explain a higher variability in warfarin dose, we comprehensively assessed VKORC1 polymorphisms in 273 African-Americans and 302 European-Americans. The influence of VKORC1 polymorphisms, race-specific haplotypes and haplotype groups on warfarin dose was evaluated in race-stratified multivariable analyses after accounting for CYP2C9 (*2, *3, *5, *6 and *11) and clinical covariates. VKORC1 explained 18% (30% with CYP2C9) variability in warfarin dose among European-Americans and 5% (8% with CYP2C9) among African-Americans. Four common haplotypes in European-Americans and twelve in African-Americans were identified. In each race VKORC1 haplotypes emerged into two groups: low-dose (Group A) and high-dose (Group B). African-Americans had a lower frequency of Group A haplotype (10.6%) compared with European-Americans (35%, p < 0.0001).The variability in dose explained by VKORC1 haplotype or haplotype groups was similar to that of a single informative polymorphism. Our findings support the use of CYP2C9, VKORC1 polymorphisms (rs9934438 or rs9923231) and clinical covariates to predict warfarin dose in both African- and European-Americans. A uniform set of common polymorphisms in CYP2C9 and VKORC1, and limited clinical covariates can be used to improve warfarin dose prediction for a racially diverse population.