Warfarin Dose Prediction Research Articles

Development and Comparison of Warfarin Dosing Algorithms in Stroke Patients.

PurposeThe genes for cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) have been identified as important genetic determinants of warfarin dosing and have been studied. We developed warfarin algorithm for Korean patients with stroke and compared the accuracy of warfarin dose prediction algorithms based on the pharmacogenetics.Materials and MethodsA total of 101 patients on stable maintenance dose of warfarin were enrolled. Warfarin dosing algorithm was developed using multiple linear regression analysis. The performance of all the algorithms was characterized with coefficient of determination, determined by linear regression, and the mean of percent deviation was used to predict doses from the actual dose. In addition, we compared the performance of the algorithms using percentage of predicted dose falling within ±20% of clinically observed doses and dividing the patients into a low-dose group (≤3 mg/day), an intermediate-dose group (3–7 mg/day), and high-dose group (≥7 mg/day).ResultsA new developed algorithms including the variables of age, body weight, and CYP2C9 and VKORC1 genotype. Our algorithm accounted for 51% of variation in the warfarin stable dose, and performed best in predicting dose within 20% of actual dose and intermediate-dose group.ConclusionOur warfarin dosing algorithm may be useful for Korean patients with stroke. Further studies to elucidate clinical utility of genotype-guided dosing and find the additional genetic association are necessary.

Artificial neural network-based pharmacogenomic algorithm for warfarin dose optimization.

To develop more precise pharmacogenomic algorithm for prediction of safe and effective dose of warfarin. An artificial neural network (ANN) algorithm was developed by using age, gender, BMI, plasma vitamin K levels, thyroid status and ten genetic variables as the inputs and therapeutic warfarin dose as the output. Hyperbolic tangent function was used to build an ANN architecture. This model explained 93.5% variability in warfarin dosing and predicted warfarin dose accurately in 74.5% patients whose international normalized ratio (INR) was less than 2.0 and in 83.3% patients whose INR was more than 3.5. This algorithm reduced the out-of-range INRs (odds ratio [OR]: 0.49; 95% CI: 0.30-0.79; p = 0.003), the rate of adverse drug reactions (OR: 0.00; 95% CI: 0.00-1.21; p = 0.06) and time to reach first therapeutic INR (OR: 6.73; 95% CI: 2.17-22.31; p < 0.0001). This algorithm was found to be applicable in both euthyroid and hypothyroid status. S-warfarin/7-hydroxywarfarin ratio was found to increase in subjects with CYP2C9*2 and CYP2C9*3 justifying the warfarin sensitivity attributed to these variants. An application of ANN for warfarin dosing improves predictability and provides safe and effective dosing.

Validation of warfarin pharmacogenetic algorithms in 586 Han Chinese patients.

To compare the accuracy of the nine selected algorithms for predicting warfarin dose with 586 Han Chinese patients. Genotyping of VKORC1 1639G>A, CYP2C9*2 and CYP2C9*3 variants was performed. Both the mean absolute error and ideal estimation value were used for comparison. The top three performers were from East Asians. The algorithms from Caucasians generally performed better in the medium-dose subgroup (>3 and <7 mg/day), while the algorithms from East Asians generally performed better in the low-dose subgroup (≤ 3 mg/day). None of the algorithms performed well in the high-dose subgroup (≥ 7 mg/day). Algorithms built for specific ethnic groups and preassigned-dose groups are suggested for better prediction.

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

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. 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. 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. 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.

VKORC1 and CYP2C9 genotypic data-based dose prediction alone does not accurately predict warfarin dose requirements in some Malaysian patients.

VKORC1 and CYP2C9 genetic polymorphisms may not accurately predict warfarin dose requirements. We evaluated an existing warfarin dosing algorithm developed for Malaysian patients that was based only on VKORC1 and CYP2C9 genes. Five Malay patients receiving warfarin maintenance therapy were investigated for their CYP2C9*2, CYP2C9*3, and VKORC1-1639G>A genotypes and their vitamin K-dependent (VKD) clotting factor activities. The records of their daily warfarin doses and international normalized ratio (INR) 2 years prior to and after the measurement of VKD clotting factors activities were acquired. The mean warfarin doses were compared with predicted warfarin doses calculated from a genotypic-based dosing model developed for Asians. A patient with the VKORC1-1639 GA genotype, who was supposed to have higher dose requirements, had a lower mean warfarin dose similar to those having the VKORC1-1639 AA genotype. This discrepancy may be due to the coadministration of celecoxib, which has the potential to decrease warfarins metabolism. Not all patients' predicted mean warfarin doses based on a previously developed dosing algorithm for Asians were similar to the actual mean warfarin dose, with the worst predicted dose being 54.34% higher than the required warfarin dose. Multiple clinical factors can significantly change the actual required dose from the predicted dose from time to time. The additions of other dynamic variables, especially INR, VKD clotting factors, and concomitant drug use, into the dosing model are important in order to improve its accuracy.

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

ObjectiveTo 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.MethodsWe 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.ResultsA 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.ConclusionsAll 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.

VKORC1 and CYP2C9 genotypes are predictors of warfarin‐related outcomes in children

Despite substantial evidence supporting a pharmacogenetic approach to warfarin therapy in adults, evidence on the importance of genetics in warfarin therapy in children is limited, particularly for clinical outcomes. We assessed the contribution of CYP2C9/VKORC1/CYP4F2 genotypes and variation in other genes involved in vitamin K and coagulation pathways to warfarin dose and related clinical outcomes in children. Clinical and genetic data for 93 children (age ≤ 18 years) who received warfarin therapy were obtained. DNA was genotyped for 93 selected single nucleotide polymorphisms using a custom assay. With a median age of 4.8 years, our cohort included more young children than most previous studies. Overall, 76.3% of dose variability was explained by weight, indication, VKORC1-1639G/A and CYP2C9 *2/*3, with genotypes accounting for 21.1% of variability. There was a strong correlation (R(2) = 0.68; P < 0.001) between actual and predicted warfarin dose using a pediatric genotype-based dosing model. VKORC1 genotype had a significant impact on time to therapeutic international normalized ratio (INR) (P = 0.047) and time to over-anticoagulation (INR > 4; P = 0.024) during the initiation of therapy. CYP2C9*3 carriers were also at increased risk of major bleeding while receiving warfarin (adjusted OR = 11.28). An additional variant in CYP2C9 (rs7089580) was significantly associated with warfarin dose (P = 0.020) in a multivariate clinical and genetic model. This study confirms the importance of VKORC1/CYP2C9 genotypes for warfarin dosing in a young pediatric cohort and demonstrates an impact of genetic factors on clinical outcomes in children. Furthermore, we identified an additional variant in CYP2C9 of potential relevance for warfarin dosing in children.

Improvement of anticoagulant treatment using a dynamic decision support algorithm

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

A randomized controlled study of the VKORC1 and CYP2C9 genotypes in guiding warfarin therapy for pulmonary thromboembolism

To evaluate the clinical application of a dosing algorithm by genotypes in prediction of warfarin maintenance dose in Chinese patients with pulmonary thromboembolism. During October 2010 and August 2012, 220 inpatients or outpatients with pulmonary embolism in Beijing Anzhen Hospital, were enrolled by the inclusion criteria. The patients included 86 males and 134 females. The clinical data and blood samples were collected. The fluorescent PCR genotyping method was used to detect the genotypes of vitamin K epoxy compounds reductase complex subunit 1 (VKORC1) and cytochrome P450 enzyme 2C9 (CYP2C9). According to the random number table, the patients were randomly divided into a study group and a control group. In the study group, the first 3 doses of warfarin were prescribed according to the predicted warfarin dose, while in the control group the drug was prescribed according to the dose estimated empirically by clinicians. Warfarin was adjusted until it reached a stable dose according to the INR value, and the following-up lasted for 50 days. AT the end of follow-up, the percentage of patients who obtained a stable dose in the study group and the control group was 82.1% (n = 78) and 66% (n = 64), respectively. The mean time to reach a stable dose in the study group and the control group was (16.8 ± 1.5) and (25.6 ± 1.8) days, and the median time was (11.0 ± 1.0) days and (20.0 ± 2.0) days, the difference between the 2 groups being statistically significant (χ(2) = 18.175, P < 0.001). The incidence of side effects of the study group was lower than that of the control group, and the time to the occurrence of side effects in study group was longer. The average predicted dose of the 142 patients who reached a stable dose was (3.6 ± 0.9) mg/d, and the average effective dose was (3.7 ± 1.3) mg/d, the average predicted dose being lower than the actual dose (0.1 ± 1.2) mg/d, but the difference was not significant(t = -1.202, P > 0.05). The warfarin stable dose prediction algorithm, containing genetic factors and non-heritage factors, can significantly shorten the adjustment time to reach warfarin stable dose, and reduce the incidence of side effects, and is clinically applicable.

Erratum to: Warfarin dose prediction in children using pharmacometric bridging – comparison with published pharmacogenetic dosing algorithms

Erratum to: Warfarin dose prediction in children using pharmacometric bridging – comparison with published pharmacogenetic dosing algorithms

Validation of a Proposed Warfarin Dosing Algorithm Based on the Genetic Make-Up of Egyptian Patients

Warfarin is the most frequently prescribed oral anticoagulant worldwide. Due to its narrow therapeutic index and inter-patient variability in dose requirement, this drug has been considered an ideal target for personalised medicine. Several warfarin dosing algorithms have been proposed to tailor the warfarin dosage in the European, Asian and African-American populations. However, minimal interest was directed towards Middle East countries. The factors affecting warfarin dose requirement could be different in patients from different geographical and ethnic groups, limiting the value of published dosing algorithms. The first objective of this study was to examine the contribution of genetic and nongenetic factors on the variability of warfarin dose requirements in the Egyptian population using an easy, cost-effective and rapid analysis of vitamin K epoxide reductase complex subunit 1 (VKORC1) and cytochrome P450 (CYP) 2C9 single nucleotide polymorphism (SNP) genotyping of patients. A second objective was to develop and validate an algorithm for warfarin dose prediction that is tailored to Egyptian patients. Eighty-four patients, 41 males and 43 females, with a median (25th-75th percentiles) age of 39 (31-48) years were recruited in this study. Fifty patients whose international normalised ratio (INR) was in the range of 2-3 were allocated to a study cohort. SYBR Green-based multiplex allele-specific real-time PCR was used for genotyping of CYP2C9 (1075A>C) and VKORC1 (1173C>T) polymorphisms. Linear regression analysis, including the variables age, gender, CYP2C9 and VKORC1 SNP genotypes, was run to derive the best model for estimating the warfarin dose that achieves an INR of 2-3. The new warfarin dosing algorithm was examined in a second cohort of patients (n=34) to check its validity. The predicted dose requirements for a subgroup of our patients were calculated according to Gage and International Warfarin Pharmacogenetics Consortium (IWPC) algorithms available at http://www.warfarindosing.org. In the study cohort, warfarin dose/week in VKORC1 TT subjects was statistically significantly lower than in VKORC1 CC/CT subjects (p=0.032), while there was no statistically significant difference in warfarin dose/week between CYP2C9*1*1 and *1*3 (p=0.925). A multivariate stepwise linear regression analysis revealed that age and VKORC1 had independent and significant contributions to the overall variability in warfarin dose with a p-value=0.013 and 0.042, respectively. Maintenance dose (mg/week)=65.226-0.422×(age) - 9.474×(VKORC1). The estimated regression equation was able to account for 20.5% of the overall variability in warfarin maintenance dose. A significant positive correlation, with sufficient strength, was observed between the predicted warfarin dose and the actual prescribed dose (r=0.453, p=0.001). In the validation cohort, after application of the dosing algorithm, correlation between predicted and actual dose was statistically significant (p=0.023). The equation was particularly successful among patients with a dose≥35 mg/week. The correlation coefficient between the actual and predicted doses for IWPC and Gage were 0.304 and 0.276, respectively. When compared with our algorithm (r=0.279), the difference was non-significant: p=0.903 and 0.990, respectively. VKORC1 (1173C>T) contributes to the warfarin dose variability. Patients' age and genetic variants of VKORC1 account for nearly 20.5% of the variability in warfarin dose required to achieve an INR of 2-3. The success of a prediction equation based on these variables was proved in a different cohort: the predicted dose correlated significantly with the maintenance dose and the equation was more successful among patients with a dose≥35 mg/week. The results of the warfarin algorithm we developed were comparable with those of the IWPC and Gage algorithms with the advantage of using one SNP (VKORC1 1173C>T) only. This represents an economic advantage in our community. Replication of this study in a larger cohort of patients is necessary before translation of this knowledge into clinical guidelines for warfarin prescription.

Genetic variants associated with warfarin dose in African-American individuals: a genome-wide association study

SummaryBackgroundVKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans.MethodsWe did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort.FindingsThe discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement).InterpretationA novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population.FundingNational Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.

Pharmacogenetics of warfarin safety and effectiveness in children

ObjectivesTo assess the contribution of CYP2C9/VKORC1 genotypes and variation in other genes involved in warfarin biotransformation and coagulation pathways to warfarin‐related outcomes in children. Furthermore, to validate the performance of a previously published pediatric pharmacogenetics‐dosing model when predicting the required dose in an independent cohort of children.MethodsClinical and genetic data was collected from 93 patients ≤18 years of age who received warfarin therapy. Genotyping was performed using a custom 96 SNP genotyping assay.ResultsTogether, VKORC1–1639G/A and CYP2C9 *2/*3 accounted for 21.1% of dose variability. There was a strong correlation (R2=0.64; P&lt;0.001) between actual and predicted warfarin dose using a pediatric pharmacogenetics‐dosing model. VKORC1 genotype also had a significant impact on time to therapeutic INR (P=0.047), time to INR&gt;;4 (P=0.028), and risk of over‐anticoagulation (INR&gt;;4) during the initiation of therapy (odds ratio, 3.3; P=0.014). An additional variant in CYP2C9 (rs7089580) was significantly associated with warfarin dose in a multivariate model.ConclusionsThis study confirms the importance of VKORC1/CYP2C9 genotype for warfarin outcomes in children and validates a pediatric‐specific genotype‐based dosing algorithm. Research funding provided by CIHR‐DSEN and CFI.

Warfarin dose prediction in children using pharmacometric bridging—comparison with published pharmacogenetic dosing algorithms

PurposeNumerous studies have investigated causes of warfarin dose variability in adults, whereas studies in children are limited both in numbers and size. Mechanism-based population modelling provides an opportunity to condense and propagate prior knowledge from one population to another. The main objectives with this study were to evaluate the predictive performance of a theoretically bridged adult warfarin model in children, and to compare accuracy in dose prediction relative to published warfarin algorithms for children.MethodAn adult population pharmacokinetic/pharmacodynamic (PK/PD) model for warfarin, with CYP2C9 and VKORC1 genotype, age and target international normalized ratio (INR) as dose predictors, was bridged to children using allometric scaling methods. Its predictive properties were evaluated in an external data set of children 0–18 years old, including comparison of dose prediction accuracy with three pharmacogenetics-based algorithms for children.ResultsOverall, the bridged model predicted INR response well in 64 warfarin-treated Swedish children (median age 4.3 years), but with a tendency to overpredict INR in children ≤2 years old. The bridged model predicted 20 of 49 children (41 %) within ± 20 % of actual maintenance dose (median age 7.2 years). In comparison, the published dosing algorithms predicted 33–41 % of the children within ±20 % of actual dose. Dose optimization with the bridged model based on up to three individual INR observations increased the proportion within ±20 % of actual dose to 70 %.ConclusionA mechanism-based population model developed on adult data provides a promising first step towards more individualized warfarin therapy in children.Electronic supplementary materialThe online version of this article (doi:10.1007/s00228-012-1466-4) contains supplementary material, which is available to authorized users.

Effect of NQO1 and CYP4F2 Genotypes on Warfarin Dose Requirements in Hispanic–Americans and African–Americans

The objective of this study was to determine the additional contribution of NQO1 and CYP4F2 genotypes to warfarin dose requirements across two racial groups after accounting for known clinical and genetic predictors. The following were assessed in a cohort of 260 African-Americans and 53 Hispanic-Americans: clinical data; NQO1 p.P187S (*1/*2); CYP2C9*2, *3, *5, *6, *8 and *11; CYP4F2 p.V433M; and VKORC1 c.-1639G>A genotypes. Both the CYP4F2 433M (0.23 vs 0.06; p < 0.05) and NQO1*2 (0.27 vs 0.18; p < 0.05) allele frequencies were higher in Hispanic-Americans compared with African-Americans. Multiple regression analysis in the Hispanic-American cohort revealed that each CYP4F2 433M allele was associated with a 22% increase in warfarin maintenance dose (p = 0.019). Possession of the NQO1*2 allele was associated with a 34% increase in warfarin maintenance dose (p = 0.004), while adjusting for associated genetic (CYP2C9, CYP4F2 and VKORC1) and clinical factors. In this population, the inclusion of CYP4F2 and NQO1*2 genotypes improved the dose variability explained by the model from 0.58 to 0.68 (p = 0.001), a 17% relative improvement. By contrast, there was no association between CYP4F2 or NQO1*2 genotype and therapeutic warfarin dose in African-Americans after adjusting for known genetic and clinical predictors. In our cohort of inner-city Hispanic-Americans, the CYP4F2 and NQO1*2 genotypes significantly contributed to warfarin dose requirements. If our findings are confirmed, they would suggest that inclusion of the CYP4F2 and NQO1*2 genotypes in warfarin dose prediction algorithms may improve the predictive ability of such algorithms in Hispanic-Americans.

The influence of VKORC1 3730 G &gt; A polymorphism on warfarin dose: reply

Dear Sirs, Skov et al. object that the effect of the variant allele rs7294 which is associated with higher warfarin requirements is not relevant in our dosing algorithm, its effect being significant at the univariate but not at the multivariate analysis. Skov et al. also show that there is not a complete linkage disequilibrium but a significant correlation between rs 7294 and the variant allele rs 9934438 which is associated with warfarin sensitivity, based on the data of their study [1]. The frequency of the variant allele rs 7294 was 9.6% in their study vs 7.3% in our derivation group and 10% in the validation group. The partial linkage disequilibrium between the rs 7294 and the rs 9934438 is also consistent with data previously published by Wadelius et al [2]. In the algorithm recently elaborated by Pavani et al. [3], various parameters were included in the multiple linear regression model, and they concluded that the incorporation of VKORC1*3 (rs 7294) and VKORC1*4 (6009 C/T) could help in a precise prediction of therapeutic warfarin dose. Moreover, in a recent meta-analysis [4], Jorgensen et al. showed that for the Caucasian ethnic group, the pooled effect estimate of the VKORC SNP rs 7294 on warfarin dosing was nonsignificant for heterozygotes versus wild-types, but was statistically significant for mutant-types versus wild-types. In our study [5], we chose to employ a simultaneous multivariate regression as our analysis was exploratory and hypothesis generating. The loss of significance of the effect of rs 7294 at the multivariate analysis could be due to our limited sample size, as acknowledged in our discussion, and larger studies are required to confirm our algorithm.

COMPARATIVE PERFORMANCE OF GENE-BASED WARFARIN DOSING ALGORITHMS IN CHINESE PATIENTS

ObjectivesMultiple warfarin pharmacogenetic algorithms have been published and been confirmed to predict warfarin dose more accurately than clinical algorithm or fixed-dose approach. However, their performance in Chinese patients has never...

CONSTRUCTION AND VALIDATION OF A PHARMACOGENETIC REFINEMENT ALGORITHM FOR THE ESTIMATION OF THE WARFARIN DOSE IN CHINESE PATIENTS

ObjectivesPharmacogenetic refinement algorithm on the basis of early international normalised ratio (INR), clinical factors, and genotypes is promising for the accurate prediction of warfarin dose. However, it has never been...

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

A few warfarin pharmacogenetic dosing algorithms have been proposed,based on multiethnic or homogeneous populations, to estimate warfarin therapeutic doses. However, it remains to be proven that which algorithm is accurate in predicting warfarin dose in Chinese people. We selected eight warfarin dose predictive pharmacogenetic algorithms and retrospectively assessed the predictive accuracy of each algorithm in a total of 368 eligible outpatients by comparing the actual stable therapeutic dose to the dose predicted by the algorithm. Our results showed that a high level of performance was demonstrated by three algorithms,Gage et al., Anderson et al., and Wu et al., having a similar performance in coefficient of determination (R2) and percentage of patients predicted dose within 20% of actual dose. The Gage et al. algorithm had the lowest mean absolute error (MAE). These results indicated that the algorithm by Gage et al. provided a more accurate prediction than did the others,which suggests that this pharmacogenetic algorithm might be used in clinical practice to guide rational administration of warfarin.

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.