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

Influence of polymorphisms in CYP2C9, VKORC1, MDR1 and APOE genes on the warfarin maintenance dose in Brazilian patients

Background: Polymorphisms in the CYP2C9, VKORC1, MDR1 and APOE genes may impact warfarin dose. Aim: To investigate the influence of sociodemographic, clinical factors and polymorphisms *1, *2 and *3 for CYP2C9, -1639G>A for VKORC1, 3435C>T for MDR1, and ϵ2, ϵ3 and ϵ4 for APOE genes on the mean weekly warfarin maintenance dose in adults. Methods: This cross-sectional study recruited a calculated sample of 315 patients in three anticoagulation clinics in Brazil. A model containing the variables significantly associated with warfarin dose was estimated. Results: The mean age of patients was 64.1 ± 13.1 years, with 173 (54.9%) women. Age, use of amiodarone, genotype VKORC1 GA, genotype VKORC1 AA, genotypes CYP2C9*1/*2 or *1/*3 and genotypes CYP2C9*2/*2 or *2/*3 or *3/*3 were associated with a reduced warfarin dose. Conclusion: This study pointed out factors that could impact the management of oral anticoagulation.

Opposite Response to Vitamin K Antagonists: A Report of Two Cases and Systematic Review of Literature

Vitamin K antagonists (VKAs) are used in the prophylaxis and treatment of thromboembolic disorders. Despite a high efficacy, their narrow therapeutic window and high response variability hamper their management. Several patients experience fluctuations in dose−response and are at increased risk of over- or under-anticoagulation. Therefore, it is essential to monitor the prothrombin time/international normalized ratio to determine the so-called stable dose and to adjust the dosage accordingly. Three polymorphisms, CYP2C9∗2, CYP2C9∗3 and VKORC1-1639G>A, are associated with increased sensitivity to VKAs. Other polymorphisms are associated with a request for a higher dose and VKA resistance. We described the clinical cases of two patients who were referred to the Clinical Pharmacology and Pharmacogenetics Unit of the University Hospital of Salerno for pharmacological counseling. One of them showed hypersensitivity and the other one was resistant to VKAs. A systematic review was performed to identify randomized clinical trials investigating the impact of pharmacogenetic testing on increased sensitivity and resistance to VKAs. Although international guidelines are available and information on the genotype-guided dosing approach has been included in VKA drug labels, VKA pharmacogenetic testing is not commonly required. The clinical cases and the results of the systematically reviewed RCTs demonstrate that the pharmacogenetic-based VKA dosing model represents a valuable resource for reducing VKA-associated adverse events.

Incremental Value of Genotype Bins over the HAS-BLED Score for the Prediction of Bleeding Risk in Warfarin-Treated Patients with Atrial Fibrillation

Background

This study aimed to analyse the role of the HAS-BLED score with the addition of genotype bins for bleeding risk prediction in warfarin-treated patients with atrial fibrillation (AF).

Methods and Results

Consecutive patients with AF on initial warfarin treatment were recruited. For each patient, CYP2C9 ^∗ 3 and VKORC1-1639 A/G genotyping was performed to create 3 genotype functional bins. The predictive values of the HAS-BLED score with or without the addition of genotype bins were compared. According to the carrier status of the genotype bins, the numbers of normal, sensitive, and highly sensitive responders among 526 patients were 64 (12.17%), 422 (80.23%), and 40 (7.60%), respectively. A highly sensitive response was independently associated with clinically relevant bleeding (HR: 3.85, 95% CI: 1.88-7.91, P=0.001) and major bleeding (HR:3.75, 95% CI: 1.17-11.97, P=0.03). With the addition of genotype bins, the performance of the HAS-BLED score for bleeding risk prediction was significantly improved (c-statistic from 0.60 to 0.64 for clinically relevant bleeding and from 0.64 to 0.70 for major bleeding, P < 0.01). Using the integrated discriminatory, net reclassification improvement, and decision curve analysis, the HAS-BLED score plus genotype bins could perform better in predicting any clinically relevant bleeding than the HAS-BLED score alone.

Conclusions

Genotypes have an incremental predictive value when combined with the HAS-BLED score for the prediction of clinically relevant bleeding in warfarin-treated patients with AF.

Comparison of the prediction performance of different warfarin dosing algorithms based on Chinese patients

Aim: To compare the prediction performance of different warfarin dosing algorithms based on Chinese patients. Materials & methods: A total of 18 algorithms were tested in 325 patients. The predictive efficacy of selected algorithms was evaluated by calculating the percentage of patients whose predicted dose fell within ±20% of their actual stable warfarin dose and the mean absolute error. Results: The percentage within ± 20% and the mean absolute error of the algorithms ranged from 11.9 to 41.2% and -0.20 (-0.29 to -0.11) mg/d to -1.63 (-1.75 to -1.50) mg/d. The algorithms established by Miao et al. and Wei et al. had optimal predictive performance. Conclusion: Algorithms based on geographical populations might be more suitable for the prediction of stable warfarin doses in local patients.

Impact of genetic and clinical factors on warfarin therapy in patients early after heart valve replacement surgery

PURPOSE

Factors influencing responsiveness to warfarin at treatment onset time were not well identified in Chinese patients undergoing heart valve replacement. We sought to select the most relevant factors that associated with patient response to warfarin early after heart valve surgery.

METHODS

In this observational study, 289 patients starting warfarin therapy early after heart valve replacement surgery were enrolled. CYP2C9 *1, *2, *3, and *5; VKORC1-1639 G>A, CYP4F2 V433M, and GGCX rs11676382 genotypes; clinical characteristics, response to therapy, and bleeding and thrombosis events were collected. The primary outcomes were the time to the first INR equal to or more than lower limit of therapeutic range and the warfarin dose requirements. Stepwise multiple linear regression was performed to develop a dosing algorithm to predict the warfarin dose requirements.

RESULTS

The results of univariate analysis showed lone VKORC1-1639 G>A, CYP2C9 *1/*3, cefazolin, cefoperazone-sulbactam, increased BMI, Δhemoglobin, and white blood cell count could significantly affect patient responsiveness to warfarin in the initial period of anticoagulation. Multivariate analysis resulted in an equation: Accumulated warfarin doses (mg) = 17.068 VKORC1-1639 G>A - 4.261 hypertension + 0.593 BMI - 0.115 age - 4.852 CYP2C9 *1/*3 - 2.617 cefazolin - 4.902 cefoperazone-sulbactam - 4.537, which could explain 40.2% of the variability in warfarin dose needed to reach the first INR equal to or more than lower limit of therapeutic range.

CONCLUSIONS

Both genetic and clinical factors contributed to anticoagulation effect of warfarin in the initial period of treatment. Our findings could provide a basis for the personalized management of warfarin use in the early stage of anticoagulation in northern Chinese patients.

Pharmacogenetic-guided dosing of coumarin anticoagulants: algorithms for warfarin, acenocoumarol and phenprocoumon

Coumarin derivatives, such as warfarin, acenocoumarol and phenprocoumon are frequently prescribed oral anticoagulants to treat and prevent thromboembolism. Because there is a large inter-individual and intra-individual variability in dose-response and a small therapeutic window, treatment with coumarin derivatives is challenging. Certain polymorphisms in CYP2C9 and VKORC1 are associated with lower dose requirements and a higher risk of bleeding. In this review we describe the use of different coumarin derivatives, pharmacokinetic characteristics of these drugs and differences amongst the coumarins. We also describe the current clinical challenges and the role of pharmacogenetic factors. These genetic factors are used to develop dosing algorithms and can be used to predict the right coumarin dose. The effectiveness of this new dosing strategy is currently being investigated in clinical trials.

A pharmacogenetics-based warfarin maintenance dosing algorithm from Northern Chinese patients

Inconsistent associations with warfarin dose were observed in genetic variants except VKORC1 haplotype and CYP2C9*3 in Chinese people, and few studies on warfarin dose algorithm was performed in a large Chinese Han population lived in Northern China. Of 787 consenting patients with heart-valve replacements who were receiving long-term warfarin maintenance therapy, 20 related Single nucleotide polymorphisms were genotyped. Only VKORC1 and CYP2C9 SNPs were observed to be significantly associated with warfarin dose. In the derivation cohort (n = 551), warfarin dose variability was influenced, in decreasing order, by VKORC1 rs7294 (27.3%), CYP2C9*3(7.0%), body surface area(4.2%), age(2.7%), target INR(1.4%), CYP4F2 rs2108622 (0.7%), amiodarone use(0.6%), diabetes mellitus(0.6%), and digoxin use(0.5%), which account for 45.1% of the warfarin dose variability. In the validation cohort (n = 236), the actual maintenance dose was significantly correlated with predicted dose (r = 0.609, P<0.001). Our algorithm could improve the personalized management of warfarin use in Northern Chinese patients.

Methodological issues in the development of a pharmacogenomic algorithm for warfarin dosing: comparison of two regression approaches

Aim: To ascertain whether multiple polynomial regression (MPR) has any advantage over multiple linear regression (MLR) in developing pharmacogenomic algorithms. Materials & methods: Two pharmacogenomic algorithms were developed based on MPR and MLR models from a warfarin pharmacogenomic data set (derivation cohort [n = 125] and validation cohort [n = 115]). Results: The MPR model showed better correlation with therapeutic dose (r = 0.62 vs 0.52); better diagnostic utility in distinguishing the warfarin-sensitive and warfarin-resistant patients (area under the receiver operating characteristic curves: 0.89 vs 0.81); and lower rate of underestimation (13.9 vs 20%) compared with the MLR model. Rate of overestimation was higher in the MPR than the MLR (10 vs 6.7%) model. Conclusion: The MPR approach has advantages over the MLR approach in predicting accurate and safe dose.

Original submitted 12 December 2013; Revision submitted 24 March 2014

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%.