Development of a pharmacogenetic-guided warfarin dosing algorithm for Puerto Rican patients

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.

Warfarin Dosing in Patients with CYP2C9*5 Variant Alleles

Pharmacogenetic dosing improves the accuracy of warfarin dosing, but current pharmacogenetic dosing algorithms are less accurate in populations of African ancestry. The cytochrome P450 2C9*5 (CYP2C9*5) allele is found almost exclusively in populations of African ancestry, and in-vitro studies suggest CYP2C9*5 is associated with reduced clearance of warfarin. The clinical relevance of this SNP is uncertain. In this multi-centered study of 2298 patients (49% female, 35% Black) taking warfarin, we quantified the association between the CYP2C9*5 allele and warfarin requirements. The CYP2C9*5 SNP was present in 2.3% of Black and 0.07% of White patients. Without taking CYP2C9*5 into account, pharmacogenetic algorithms that include other SNPs overestimated the warfarin dose by 30% (95% CI [19%-40%], p<0.001), an average of 1.87 mg/d (SD 1.64) in heterozygotes (p < 0.001). Non-carriers required a slightly (0.23 mg/d, SD 2.09) higher than predicted dose. Genotyping for CYP2C9*5 corrected the potential overdose and halved overall dosing error in heterozygotes. Patients carrying CYP2C9*5 require a clinically relevant reduction in warfarin dose. Given the potential to improve the accuracy and safety of warfarin dosing in populations of African ancestry, we have incorporated this SNP into a non-profit website to assist warfarin initiation (www.WarfarinDosing.org).

Multi-site Investigation of Genetic Determinants of Warfarin Dose Variability in Latinos

We conducted a multi‐site investigation of genetic determinants of warfarin dose variability in Latinos from the U.S. and Brazil. Patients from four institutions in the United States (n = 411) and Brazil (n = 663) were genotyped for VKORC1 c.‐1639G> A, common CYP2C9 variants, CYP4F2*3, and NQO1*2. Multiple regression analysis was used in the U.S. cohort to test the association between warfarin dose and genotype, adjusting for clinical factors, with further testing in an independent cohort of Brazilians. In the U.S. cohort, VKORC1 and CYP2C9 variants were associated with lower warfarin dose (β = −0.29, P < 2.0 × 10⁻¹⁶; β = −0.21, P = 4.7 × 10⁻⁷, respectively) whereas CYP4F2 and NQO1 variants were associated with higher dose (β = 0.10, P = 2 × 10⁻⁴; β = 0.10, P = 0.01, respectively). Associations with VKORC1 (β = −0.14, P = 2.0 × 10⁻¹⁶), CYP2C9 (β = −0.07, P = 5.6 × 10⁻¹⁰), and CYP4F2 (β = 0.03, P = 3 × 10⁻³), but not NQO1*2 (β = 0.01, P = 0.30), were replicated in the Brazilians, explaining 43–46% of warfarin dose variability among the cohorts from the U.S. and Brazil, respectively. We identified genetic associations with warfarin dose requirements in the largest cohort of ancestrally diverse, warfarin‐treated Latinos from the United States and Brazil to date. We confirmed the association of variants in VKORC1, CYP2C9, and CYP4F2 with warfarin dose in Latinos from the United States and Brazil.

Genotype-driven pharmacokinetic simulations of warfarin levels in Puerto Ricans

Objectives The inter-individual variability of warfarin dosing has been linked to genetic polymorphisms. This study was aimed at performing genotype-driven pharmacokinetic (PK) simulations to predict warfarin levels in Puerto Ricans. Methods Analysis of each individual dataset was performed by one-compartmental modeling using WinNonlin®v6.4. The k e of warfarin given a cytochrome P450 2C9 (CYP2C9) genotype ranged from 0.0189 to 0.0075 h-1. K a and V d parameters were taken from literature. Data from 128 subjects were divided into two groups (i.e., wild-types and carriers) and statistical analyses of PK parameters were performed by unpaired t-tests. Results In the carrier group (n=64), 53 subjects were single-carriers and 11 double-carriers (i.e., *2/*2, *2/*3, *2/*5, *3/*5, and *3/*8). The mean peak concentration (Cmax) was higher for wild-type (0.36±0.12 vs. 0.32±0.14 mg/L). Likewise, the average clearance (CL) parameter was faster among non-carriers (0.22±0.03 vs. 0.17±0.05 L/h; p=0.0001), with also lower area under the curve (AUC) when compared to carriers (20.43±6.97 vs. 24.78±11.26 h mg/L; p=0.025). Statistical analysis revealed a significant difference between groups with regard to AUC and CL, but not for Cmax. This can be explained by the variation of k e across different genotypes. Conclusions The results provided useful information for warfarin dosing predictions that take into consideration important individual PK and genotyping data.

Genotype-driven pharmacokinetic simulations of warfarin levels in Puerto Ricans

OBJECTIVES

The inter-individual variability of warfarin dosing has been linked to genetic polymorphisms. This study was aimed at performing genotype-driven pharmacokinetic (PK) simulations to predict warfarin levels in Puerto Ricans.

METHODS

Analysis of each individual dataset was performed by one-compartmental modeling using WinNonlin®v6.4. The k _e of warfarin given a cytochrome P450 2C9 (CYP2C9) genotype ranged from 0.0189 to 0.0075 h^-1. K _a and V _d parameters were taken from literature. Data from 128 subjects were divided into two groups (i.e., wild-types and carriers) and statistical analyses of PK parameters were performed by unpaired t-tests.

RESULTS

In the carrier group (n=64), 53 subjects were single-carriers and 11 double-carriers (i.e., *2/*2, *2/*3, *2/*5, *3/*5, and *3/*8). The mean peak concentration (Cmax) was higher for wild-type (0.36±0.12 vs. 0.32±0.14 mg/L). Likewise, the average clearance (CL) parameter was faster among non-carriers (0.22±0.03 vs. 0.17±0.05 L/h; p=0.0001), with also lower area under the curve (AUC) when compared to carriers (20.43±6.97 vs. 24.78±11.26 h mg/L; p=0.025). Statistical analysis revealed a significant difference between groups with regard to AUC and CL, but not for Cmax. This can be explained by the variation of k _e across different genotypes.

CONCLUSIONS

The results provided useful information for warfarin dosing predictions that take into consideration important individual PK and genotyping data.

Genetic Factors Influencing Warfarin Dose in Black-African Patients: A Systematic Review and Meta-Analysis

Warfarin is the most commonly used oral anticoagulant in sub-Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high interindividual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in black-Africans, we performed a meta-analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week, respectively. VKORC1 variants rs9923231 (-1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively, whereas rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in black-Africans to evaluate genetic factors determining warfarin response.

Functionally Significant Coumarin-Related Variant Alleles and Time to Therapeutic Range in Chilean Cardiovascular Patients

Despite the development of new oral agents over the last decade, vitamin K antagonists (VKAs) remain the most widely used anticoagulants for treating and preventing thromboembolism worldwide. In Chile, the Ministry of Health indicates that acenocoumarol should be used in preference to any other coumarin. Complications of inappropriate dosing are among the most frequently reported adverse events associated with this medication. It is well known that polymorphisms in pharmacokinetic and pharmacodynamic proteins related to coumarins (especially warfarin) influence response to these drugs. This work analyzed the impact of CYP2C19*2 (rs4244285), CYP1A2*1F (rs762551), GGCx (rs11676382), CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), CYP4F2 (rs2108622), VKORC1 (rs9923231), VKORC1 (rs7294), CYP3A4*1B (rs2740574), and ABCB1 (rs1045642) polymorphisms on time to therapeutic range for oral anticoagulants in 304 Chilean patients. CYP2C9*3 polymorphisms were associated with time to therapeutic range for acenocoumarol in Chilean patients, and the CYP4F2 TT genotype, MDR1 A allele, CYP1A2 A allele, and CYP3A4T allele are promising variants that merit further analysis. The presence of polymorphisms explained only 4.1% of time to therapeutic range for acenocoumarol in a multivariate linear model. These results improve our understanding of the basis of ethnic variations in drug metabolism and response to oral anticoagulant therapy. We hope that these findings will contribute to developing an algorithm for VKA dose adjustment in the Chilean population in the near future, decreasing the frequency of stroke, systemic embolism, and bleeding-related adverse events.

A Pharmacogenetically Guided Acenocoumarol Dosing Algorithm for Chilean Patients: A Discovery Cohort Study

Background

Vitamin K antagonists (VKA) are used as prophylaxis for thromboembolic events in patients with cardiovascular diseases. The most common VKA are warfarin and acenocoumarol. These drugs have a narrow therapeutic margin and high inter-individual response variability due to clinical and pharmacogenetic variables.

Objective

The authors aim to develop an algorithm comprised of clinical and genetic factors to explain the variability in the therapeutic dose of acenocoumarol among Chilean patients

Methodology

DNA was obtained from 304 patients as a discovery cohort with an international normalized ratio (INR) range of 2.0–3.0. The non-genetic (demographic and clinical) variables were also recorded. Genotype analyses were performed using real-time PCR for VKORC1 (rs9923231), VKORC1 (rs7294), GGCx (rs11676382), CYP4F2 (rs2108622), ABCB1 (rs1045642), CYP2C9*2 (rs1799853), ApoE (rs429358), and CYP2C9*3 (rs1057910).

Results

The clinical variables that significantly influenced the weekly therapeutic dose of VKA were age, sex, body mass index (BMI), and initial INR, collectively accounting for 19% of the variability, and the genetic variables with a significant impact were VKORC1 (rs9923231), CYP2C9*2 (rs1799853), and CYP2C9*3 (rs1057910), explaining for another 37% of the variability.

Conclusion

We developed an algorithm that explains 49.99% of the variability in therapeutic VKA dosage in the Chilean population studied. Factors that significantly affected the dosage included VKORC1, CYP2C9*2, and CYP2C9*3 polymorphisms, as well as age, sex, BMI, and initial INR.

Machine Learning Algorithm for Predicting Warfarin Dose in Caribbean Hispanics Using Pharmacogenetic Data

Despite some previous examples of successful application to the field of pharmacogenomics, the utility of machine learning (ML) techniques for warfarin dose predictions in Caribbean Hispanic patients has yet to be fully evaluated. This study compares seven ML methods to predict warfarin dosing in Caribbean Hispanics. This is a secondary analysis of genetic and non-genetic clinical data from 190 cardiovascular Hispanic patients. Seven ML algorithms were applied to the data. Data was divided into 80 and 20% to be used as training and test sets. ML algorithms were trained with the training set to obtain the models. Model performance was determined by computing the corresponding mean absolute error (MAE) and % patients whose predicted optimal dose were within ±20% of the actual stabilization dose, and then compared between groups of patients with “normal” (i.e., > 21 but <49 mg/week), low (i.e., ≤21 mg/week, “sensitive”), and high (i.e., ≥49 mg/week, “resistant”) dose requirements. Random forest regression (RFR) significantly outperform all other methods, with a MAE of 4.73 mg/week and 80.56% of cases within ±20% of the actual stabilization dose. Among those with “normal” dose requirements, RFR performance is also better than the rest of models (MAE = 2.91 mg/week). In the “sensitive” group, support vector regression (SVR) shows superiority over the others with lower MAE of 4.79 mg/week. Finally, multivariate adaptive splines (MARS) shows the best performance in the resistant group (MAE = 7.22 mg/week) and 66.7% of predictions within ±20%. Models generated by using RFR, MARS, and SVR algorithms showed significantly better predictions of weekly warfarin dosing in the studied cohorts than other algorithms. Better performance of the ML models for patients with “normal,” “sensitive,” and “resistant” to warfarin were obtained when compared to other populations and previous statistical models.

CYP2C9*61, a rare missense variant identified in a Puerto Rican patient with low warfarin dose requirements

Warfarin continues to be the mainstay therapy for preventing thrombus formation. Although pharmacogenetic algorithms have shown higher predictability of the optimal warfarin dose and lower occurrence of bleeding episodes, they often do not include ethno-specific genetic variants relevant to non-Europeans. This case report describes a rare missense variant at exon 9 of CYP2C9 (rs202201137; c.1370A>G transition; p.Asn457Ser) found in a Puerto Rican patient with low warfarin dose requirements (3 mg/day). The haplotype characterized by two amino acid changes, Asn457Ser and Arg144Cys (rs1799853; c.430C>T), has been designated CYP2C9*61 by the Pharmacogene Variation Consortium. According to prediction scores assessed with the Combined Annotation Dependent Depletion tool, CYP2C9*61 (p.Asn457Ser) was classified as nondeleterious, therefore its impact on CYP2C9 enzymatic activity cannot be postulated.

Pharmacogenetics of warfarin dosing in patients of African and European ancestry

Despite the introduction of direct acting oral anticoagulants, warfarin remains the most commonly prescribed oral anticoagulant. However, warfarin therapy is plagued by the large inter- and intrapatient variability. The variability in dosing fueled research to identify clinical and genetic predictors and develop more accurate dosing algorithms. Observational studies have demonstrated the significant impact of single nucleotide polymorphisms in CYP2C9 and VKORC1 on warfarin dose in patients of European ancestry and African-Americans. This evidence supported the design and conduct of clinical trials to assess whether genotype-guided dosing results in improved anticoagulation control and outcomes. The trial results have shown discordance by race, with pharmacogenetic algorithms improving dose and anticoagulation control among European ancestry patients compared with African-American patients. Herein, we review the evidence from observational and interventional studies, highlight the need for inclusion of minority race groups and propose the need to develop race specific dosing algorithms.

Creating and validating a warfarin pharmacogenetic dosing algorithm for Colombian patients

Purpose

Warfarin is an oral anticoagulant associated with adverse reaction to drugs due to wide inter- and intra-individual dosage variability. Warfarin dosage has been related to non-genetic and genetic factors. CYP2C9 and VKORC1 gene polymorphisms affect warfarin metabolism and dosage. Due to the central role of populations’ ethnical and genetic origin on warfarin dosage variability, novel algorithms for Latin American subgroups are necessary to establish safe anticoagulation therapy.

Patients and methods

We genotyped CYP2C9*2 (c.430C > T), CYP2C9*3 (c.1075A > C), CYP4F2 (c.1297G > A), and VKORC1 (−1639 G > A) polymorphisms in 152 Colombian patients who received warfarin. We evaluated the impact on the variability of patients’ warfarin dose requirements. Multiple linear regression analysis, using genetic and non-genetic variables, was used for creating an algorithm for optimal warfarin maintenance dose.

Results

Median weekly prescribed warfarin dosage was significantly lower in patients having the VKORC1-1639 AA genotype and poor CYP2C9*2/*2,*2/*3 metabolizers than their wild-type counterparts. We found a 2.3-fold increase in mean dose for normal sensitivity patients (wild-type VKORC1/CYP2C9 genotypes) compared to the other groups (moderate and high sensitivity); 31.5% of the patients in our study group had warfarin sensitivity-related genotypes. The estimated regression equation accounted for 44.4% of overall variability in regard to warfarin maintenance dose. The algorithm was validated, giving 45.9% correlation (R²=0.459).

Conclusion

Our results describe and validate the first algorithm for predicting warfarin maintenance in a Colombian mestizo population and have contributed toward the understanding of pharmacogenetics in a Latin American population subgroup.

A factor VII-based method for the prediction of anticoagulant response to warfarin

Warfarin dosing methods based on existing models for warfarin and the international normalised ratio (INR) give biased maintenance dose predictions at the upper and lower quantiles of dose requirements. The aim of this work is to propose a conceptually different approach to predict INR after warfarin dosing. Factor VII concentration was proposed as the principal driving force for the INR. The time to steady-state INR (t_SS,INR) was determined based on the INR response to changes in factor VII concentrations following warfarin initiation, and from this the steady-state INR (INR_SS) was derived. The proposed method requires timed, paired blood samples of INR and factor VII. At different simulated warfarin dose rates, the prediction error associated with the proposed method was shown to be within clinically acceptable limits for both the t_SS,INR (±2 days) and INR_SS (±0.2). The use of the method was demonstrated in two patients who were initiated with 5 mg of warfarin daily. The difference in predicted versus actual steady-state INR were 0.0 and −0.4. The proposed method represents a unique approach to predict the INR. It considers factor VII as the main driver for INR and provides valuable information about the time to steady state INR.

Warfarin Pharmacogenomics in Diverse Populations

Genotype-guided warfarin dosing algorithms are a rational approach to optimize warfarin dosing and potentially reduce adverse drug events. Diverse populations, such as African Americans and Latinos, have greater variability in warfarin dose requirements and are at greater risk for experiencing warfarin-related adverse events compared with individuals of European ancestry. Although these data suggest that patients of diverse populations may benefit from improved warfarin dose estimation, the vast majority of literature on genotype-guided warfarin dosing, including data from prospective randomized trials, is in populations of European ancestry. Despite differing frequencies of variants by race/ethnicity, most evidence in diverse populations evaluates variants that are most common in populations of European ancestry. Algorithms that do not include variants important across race/ethnic groups are unlikely to benefit diverse populations. In some race/ethnic groups, development of race-specific or admixture-based algorithms may facilitate improved genotype-guided warfarin dosing algorithms above and beyond that seen in individuals of European ancestry. These observations should be considered in the interpretation of literature evaluating the clinical utility of genotype-guided warfarin dosing. Careful consideration of race/ethnicity and additional evidence focused on improving warfarin dosing algorithms across race/ethnic groups will be necessary for successful clinical implementation of warfarin pharmacogenomics. The evidence for warfarin pharmacogenomics has a broad significance for pharmacogenomic testing, emphasizing the consideration of race/ethnicity in discovery of gene-drug pairs and development of clinical recommendations for pharmacogenetic testing.

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

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

Pharmacogenetic research activity in Central America and the Caribbean: a systematic review

AIM

The present review was aimed at analyzing the pharmacogenetic scientific activity in Central America and the Caribbean.

MATERIALS & METHODS

A literature search for pharmacogenetic studies in each country of the region was conducted on three databases using a list of the most relevant pharmacogenetic biomarkers including 'phenotyping probe drugs' for major drug metabolizing enzymes. The review included 132 papers involving 47 biomarkers and 35,079 subjects (11,129 healthy volunteers and 23,950 patients).

RESULTS

The country with the most intensive pharmacogenetic research was Costa Rica. The most studied medical therapeutic area was oncology, and the most investigated biomarkers were CYP2D6 and HLA-A/B. Conclusion: Research activity on pharmacogenetics in Central American and the Caribbean populations is limited or absent. Therefore, strategies to promote effective collaborations, and foster interregional initiatives and research efforts among countries from the region could help for the rational clinical implementation of pharmacogenetics and personalized medicine.

Pharmacogenetics of drug-metabolizing enzymes in US Hispanics

Although the Hispanic population is continuously growing in the United States, they are underrepresented in pharmacogenetic studies. This review addresses the need for compiling available pharmacogenetic data in US Hispanics, discussing the prevalence of clinically relevant polymorphisms in pharmacogenes encoding for drug-metabolizing enzymes. CYP3A5*3 (0.245-0.867) showed the largest frequency in a US Hispanic population. A higher prevalence of CYP2C9*3, CYP2C19*4, and UGT2B7 IVS1+985 A>G was observed in US Hispanic vs. non-Hispanic populations. We found interethnic and intraethnic variability in frequencies of genetic polymorphisms for metabolizing enzymes, which highlights the need to define the ancestries of participants in pharmacogenetic studies. New approaches should be integrated in experimental designs to gain knowledge about the clinical relevance of the unique combination of genetic variants occurring in this admixed population. Ethnic subgroups in the US Hispanic population may harbor variants that might be part of multiple causative loci or in linkage-disequilibrium with functional variants. Pharmacogenetic studies in Hispanics should not be limited to ascertain commonly studied polymorphisms that were originally identified in their parental populations. The success of the Personalized Medicine paradigm will depend on recognizing genetic diversity between and within US Hispanics and the uniqueness of their genetic backgrounds.

A Novel Admixture-Based Pharmacogenetic Approach to Refine Warfarin Dosing in Caribbean Hispanics

AIM

This study is aimed at developing a novel admixture-adjusted pharmacogenomic approach to individually refine warfarin dosing in Caribbean Hispanic patients.

PATIENTS & METHODS

A multiple linear regression analysis of effective warfarin doses versus relevant genotypes, admixture, clinical and demographic factors was performed in 255 patients and further validated externally in another cohort of 55 individuals.

RESULTS

The admixture-adjusted, genotype-guided warfarin dosing refinement algorithm developed in Caribbean Hispanics showed better predictability (R2 = 0.70, MAE = 0.72mg/day) than a clinical algorithm that excluded genotypes and admixture (R2 = 0.60, MAE = 0.99mg/day), and outperformed two prior pharmacogenetic algorithms in predicting effective dose in this population. For patients at the highest risk of adverse events, 45.5% of the dose predictions using the developed pharmacogenetic model resulted in ideal dose as compared with only 29% when using the clinical non-genetic algorithm (p<0.001). The admixture-driven pharmacogenetic algorithm predicted 58% of warfarin dose variance when externally validated in 55 individuals from an independent validation cohort (MAE = 0.89 mg/day, 24% mean bias).

CONCLUSIONS

Results supported our rationale to incorporate individual's genotypes and unique admixture metrics into pharmacogenetic refinement models in order to increase predictability when expanding them to admixed populations like Caribbean Hispanics.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01318057.

Methods for Predicting Warfarin Dose Requirements

BACKGROUND

The aim of this study was to compare the predictive performance of different warfarin dosing methods.

METHODS

Data from 46 patients who were initiating warfarin therapy were available for analysis. Nine recently published dosing tools including 8 dose prediction algorithms and a Bayesian forecasting method were compared with each other in terms of their ability to predict the actual maintenance dose. The dosing tools included 4 algorithms that were based on patient characteristics (2 clinical and 2 genotype-driven algorithms), 4 algorithms based on international normalized ratio (INR) response feedback and patient characteristics (2 clinical and 2 genotype-driven algorithms), and a Bayesian forecasting method. Comparisons were conducted using measures of bias (mean prediction error) and imprecision [root mean square error (RMSE)].

RESULTS

The 2 genotype-driven INR feedback algorithms by Horne et al and Lenzini et al produced more precise maintenance dose predictions (RMSE, 1.16 and 1.19 mg/d, respectively; P < 0.05) than the genotype-driven algorithms by Gage et al and Klein et al and the Bayesian method (RMSE, 1.60, 1.62, and 1.81 mg/d respectively). The dose predictions from clinical and genotype-driven algorithms by Gage et al, Klein et al, and Horne et al were all negatively biased. Only the INR feedback algorithms (clinical and genotype) by Lenzini et al produced unbiased dose predictions. The Bayesian method produced unbiased dose predictions overall (mean prediction error, +0.37 mg/d; 95% confidence interval, 0.89 to -0.15) but overpredicted doses in patients requiring >8 mg/d.

CONCLUSIONS

Overall, warfarin dosing methods that included some measure of INR response (INR feedback algorithms and Bayesian methods) produced unbiased and more precise dose predictions. The Bayesian forecasting method produced positively biased dose predictions in patients who required doses >8 mg/d. Further research to assess differences in clinical endpoints when warfarin doses are predicted using Bayesian or INR-driven algorithms is warranted.

Development of a pharmacogenetic-based warfarin dosing algorithm and its performance in Brazilian patients: highlighting the importance of population-specific calibration

BACKGROUND

The main aims of the present study were to develop a pharmacogenetic-based warfarin dosing algorithm and to validate it in a highly admixed population.

MATERIALS & METHODS

We included two patient cohorts treated with warfarin (first cohort, n = 832; and second cohort, n = 133).

RESULTS

Our algorithm achieved a determination coefficient of 40% including the variables age, gender, weight, height, self-declared race, amiodarone use, enzyme inducers use, VKORC1 genotypes and predicted phenotypes according to CYP2C9 polymorphisms.

CONCLUSION

Data suggest that our developed algorithm is more accurate than the IWPC algorithm when the application is focused on patients from the Brazilian population. Population-specific derivation and/or calibration of warfarin dosing algorithms may lead to improved performance compared with general use dosing algorithms currently available. Original submitted 26 November 2014; Revision submitted 9 April 2015.

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.

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.