International Warfarin Pharmacogenetics Consortium Algorithm Research Articles

Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans.

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model’s ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10−15). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone (n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms.

Pharmacogenetic-Guided Algorithm to Improve Daily Dose of Warfarin in Elder Han-Chinese Population.

ObjectivesTo verify the accuracy of the International Warfarin Pharmacogenetics Consortium (IWPC) algorithm, identify the effects of genetic and clinical factors on warfarin stable dose, and to establish a new warfarin stable dose prediction algorithm for the elderly Han-Chinese population under the guidance of pharmacogenetics.MethodsAccording to the inclusion criteria, 544 non-valvular atrial fibrillation patients taking warfarin for anticoagulation treatment were enrolled. Data information of three groups including the whole population, people under 65 years old and over 65 years old were substituted into the IWPC algorithm respectively to verify its accuracy. The basic data and clinical information of 360 elderly people were collected for statistical analysis and the genotypes of VKORC1-G1639A and CYP2C9 were detected by Sanger sequencing. The new algorithm of the elder pharmacogenetics warfarin dosing was obtained by stepwise multiple regression. The determination coefficient (R2), root mean squared error (RMSE), and the proportion of the predicted value within the true value range of ±20%(20%-p) were used to evaluate the accuracy of the IWPC algorithm and the new algorithm.ResultsAmong the three different age groups, the warfarin stable dose predictive accuracy of IWPC algorithm was the lowest in the elderly patients above 65-year-old. In this study, the important factors influencing the stable dose of warfarin in the elderly Han-Chinese were height, weight, body surface area, serum creatinine level, amiodarone usage, CYP2C9 (*1*2, *1*3), and VKORC1 (GG/GA) genotypes. By means of stepwise multiple regression analysis, we established a new elder warfarin dosing algorithm (R2=0.3714) containing height, creatinine, amiodarone usage, CYP2C9 (*1*2 or *1*3), and VKORC1 (GA or GG) genotypes. The prediction accuracy and clinical availability of the Elderly algorithm was significantly better than that of IWPC algorithm verified by RMSE, R2, and (20%-p) methods.ConclusionsThe IWPC model may not be suitable for the elder Han-Chinese population. Polymorphism of CYP2C9 and VKORC1 obviously affected warfarin stable dose of the elder Han-Chinese. Combination of genetic data with demographic and clinical factors could help to better improve warfarin doses in the elder Han-Chinese population.

Chinese Patients With Heart Valve Replacement Do Not Benefit From Warfarin Pharmacogenetic Testing on Anticoagulation Outcomes.

Genotype-guided warfarin dosing has been shown in some randomized trials to improve anticoagulation outcomes in individuals of European ancestry; yet, its utility in Chinese patients with heart valve replacement remains unresolved. A total of 2264 patients who underwent heart valve replacement at Wuhan Asia Heart Hospital were enrolled in this study. Patients were randomly divided into 2 groups, namely, a genotype-guided and a traditional clinically guided warfarin dosing group. In the genotype-guided group (n = 1134), genotyping for CYP2C9 and VKORC1 (-1639 G→A) was performed using TaqMan genotyping assay. Warfarin doses were predicted with the International Warfarin Pharmacogenetics Consortium algorithm. Patients in the control group (n = 1130) were clinically guided. The primary outcome was to compare the incidence of adverse events (major bleeding and thrombotic) during a 90-day follow-up period between 2 groups. Secondary objectives were to describe effects of the pharmacogenetic intervention on the first therapeutic-target-achieving time, the stable maintenance dose, and the hospitalization days. A total of 2245 patients were included in the analysis. Forty-nine events occurred during follow-up. Genotype-guided dosing strategy did not result in a reduction in major bleeding (0.26% versus 0.63%; hazard ratio, 0.44; 95% confidence interval, 0.13-1.53; P = 0.20) and thrombotic events (0.89% versus 1.61%; hazard ratio, 0.56; 95% confidence interval, 0.27-1.17; P = 0.12) compared with clinical dosing group. Compared with traditional dosing, patients in the genotype-guided group reached their therapeutic international normalized ratio in a shorter time (3.8 ± 2.0 versus 4.4 ± 2.0 days, P < 0.001). There was no difference in hospitalization days (P = 0.28). Warfarin pharmacogenetic testing according to the International Warfarin Pharmacogenetics Consortium algorithm cannot improve anticoagulation outcomes in Chinese patients with heart valve replacement.

Warfarin dose requirement in patients having severe thrombosis or thrombophilia.

Warfarin dose requirement varies significantly. We compared the clinically established doses based on international normalized ratio (INR) among patients with severe thrombosis and/or thrombophilia with estimates from genetic dosing algorithms. Fifty patients with severe thrombosis and/or thrombophilia requiring permanent anticoagulation, referred to the Helsinki University Hospital Coagulation Center, were screened for thrombophilias and genotyped for CYP2C9*2 (c.430C>T, rs1799853), CYP2C9*3 (c.1075A>C, rs1057910) and VKORC1 c.-1639G>A (rs9923231) variants. The warfarin maintenance doses (target INR 2.0-3.0 in 94%, 2.5-3.5 in 6%) were estimated by the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) algorithms. The individual warfarin maintenance dose was tailored, supplementing estimates with comprehensive clinical evaluation and INR data. Mean patient age was 47years (range 20-76), and BMI 27 (SD 6), 68% being women. Forty-six (92%) had previous venous or arterial thrombosis, and 26 (52%) had a thrombophilia, with 22% having concurrent aspirin. A total of 40% carried the CYP2C9*2 or *3 allele and 54% carried the VKORC1-1639A allele. The daily mean maintenance dose of warfarin estimated by the Gage algorithm was 5.4mg (95% CI 4.9-5.9mg), and by the IWPC algorithm was 5.2mg (95% CI 4.7-5.7mg). The daily warfarin maintenance dose after clinical visits and follow-up was higher than the estimates, mean 6.9mg (95% CI 5.6-8.2mg, P<0.006), with highest dose in patients having multiple thrombophilic factors (P<0.03). In severe thrombosis and/or thrombophilia, variation in thrombin generation and pharmacodynamics influences warfarin response. Pharmacogenetic dosing algorithms seem to underestimate dose requirement.

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.

DNA sensors to assess the effect of VKORC1 and CYP2C9 gene polymorphisms on warfarin dose requirement in Chinese patients with atrial fibrillation.

The optimal dose of warfarin depends on polymorphisms in the VKORC1 (the vitamin K epoxide reductase complex subunit (1) and CYP2C9 (cytochrome P450 2C9) genes. To minimize the risk of adverse reactions, warfarin dosages should be adjusted according to results from rapid and simple monitoring methods. However, there are few pharmacogenetic-guided warfarin dosing algorithms that are based on large cohorts from the Chinese population, especially patients with atrial fibrillation. This study aimed to validate a pharmacogenetic-guided warfarin dosing algorithm based on results from a new rapid electrochemical detection method used in a multicenter study. Three SNPs (CYP2C9 *2, *3 and VKORC1 c.-1639G > A) were genotyped by electrochemical detection using a sandwich-type format that included a 3' short thiol capture probe and a 5' ferrocene-labeled signal probe. A total of 1285 samples from four clinical hospitals were evaluated. Concordance rates between the results from the electrochemical DNA biosensor and the sequencing test were 99.8%. The results for gene distribution showed that most Chinese patients had higher warfarin susceptibility because mutant-type and heterozygotes were present in the majority of subjects (99.4%) at locus c.-1639G > A. When the International Warfarin Pharmacogenetics Consortium algorithm was used to estimate therapeutic dosages for 362 patients with AF and the values were compared with their actual dosages, the results revealed that 56.9% were similar to actual dosages (within the 20% range). A novel electrochemical detection method of CYP2C9 *2, *3and VKORC1 c.-1639G > A alleles was evaluated. The warfarin dosing algorithm based on data gathered from a large patient cohort can facilitate the reasonable and effective use of warfarin in Chinese patients with AF.

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...

Validation of pharmacogenetic algorithms and warfarin dosing table in Egyptian patients

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. 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. 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. 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. 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. 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

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. 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. 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). 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.

Validation and Comparison of Pharmacogenetics-Based Warfarin Dosing Algorithms for Application of Pharmacogenetic Testing

Warfarin is a widely prescribed drug that is difficult to use because of its narrow therapeutic window. Genetic polymorphisms associated with warfarin metabolism have been identified, but the clinical utility of genetic testing in warfarin dosing has not been established. External validation of published algorithms is critical to determine the best prediction for warfarin dosing in prospective trials. We used two independent datasets totaling 1095 patients to evaluate four published algorithms and a simple prediction algorithm developed in this study based on the CYP2C9*2, CYP2C9*3, and VKORC1 -1639 polymorphisms in 150 patients taking warfarin. Predicted warfarin doses were calculated and compared for accuracy with actual maintenance doses. All evaluated pharmacogenetics-based dosing algorithms performed similarly for both datasets. The proportion of variation explained (R(2)) was high (60% to 65%) in the small white-only Connecticut dataset but low (36% to 46%) in the large dataset on a diverse ethnic population from the International Warfarin Pharmacogenetics Consortium (IWPC). When comparing the percentage of patients whose predicted dosage are within 20% of actual, the IWPC algorithm performed the best overall (45.9%) for the two datasets combined while other algorithms performed nearly as well. Because no algorithm could be considered the best for all dosing ranges, it may be important to consider the nature of a local service population in choosing the most appropriate pharmacogenetics-based dosing algorithm.