Integration of genetic, clinical, and INR data to refine warfarin dosing

Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.

Kinetic-pharmacodynamic model of warfarin for prothrombin time-international normalized ratio in Japanese patients

AIMS

Genotype-guided dosing algorithms can explain about half of the interindividual variability in prothrombin time-international normalized ratio (PT-INR) under warfarin treatment. This study aimed to refine a published kinetic-pharmacodynamic model and guide warfarin dosage for an optimal PT-INR based on renal function.

METHODS

Using a retrospective cohort of adult patients (>20 years) who were administered warfarin and underwent PT-INR measurements, we refined the kinetic-pharmacodynamic model with age and the genotypes of cytochrome P450 2C9 and vitamin K epoxide reductase complex subunit 1 using the PRIOR subroutine in the nonlinear-mixed-effect modelling programme. We searched the significant covariates for parameters, such as the dose rate for 50% inhibition of coagulation (EDR50 ), using a stepwise forward and backward method. Monte Carlo simulation determined a required daily dose of warfarin with a target range of PT-INR (2.0-3.0 or 1.6-2.6) based on the significant covariates.

RESULTS

A total of 350 patients with 2762 PT-INR measurements were enrolled (estimated glomerular filtration rate [eGFR]: 47.5 [range: 2.6-199.0] mL/min/1.73 m2 ). The final kinetic-pharmacodynamic model showed that the EDR50 changed power functionally with body surface area, serum albumin level and eGFR. Monte Carlo simulation revealed that a lower daily dose of warfarin was required to attain the target PT-INR range as eGFR decreased.

CONCLUSIONS

Model-informed precision dosing of warfarin is a valuable approach for estimating its dosage in patients with renal impairment.

Application of a warfarin dosing calculator to guide individualized dosing versus empirical adjustment after fixed dosing: a pilot study

Background: Warfarin has a narrow therapeutic window and individual variation, and patients require regular follow-up and monitoring of the International Normalized Ratio (INR) for dose adjustment. The calculation method of Warfarin Dosing Calculator (WDC) software is based on the European and American populations, and its accuracy in the Chinese population is yet to be verified. Objective: This study was to evaluate the feasibility of applying Warfarin Dosing Calculator software intervention in a real-world clinical research setting in China. Methods: The pilot study divided the included patients after valve replacement into an experimental group and a control group, with 38 cases in each group. In the control group, the initial dose was fixed at 2.5 mg/d and the dose was adjusted empirically during the study period; in the experimental group, the Warfarin Dosing Calculator software was applied to guide the dosing, and patients in both groups were followed up for 3 months. Analysis of the incidence anticoagulation outcomes and excessive anticoagulation events in both groups. Kaplan-Meier survival curves were used to analyze the correlation between different dosing regimens and first International Normalized Ratio attainment, and Logrank tests were performed. Results: The mean time required for first International Normalized Ratio compliance in the experimental group was 4.38 days less than in the control group, and the mean number of tests was 1.43 less (p < 05). Time in therapeutic range (TTR) was significantly higher in the experimental group than in the control group (p < 05). Kaplan-Meier survival curve analysis showed that the first International Normalized Ratio attainment rate was significantly higher in the experimental group than in the control group (p = 01). No major bleeding events occurred in either group, but other excessive anticoagulation events (INR>3.5 and minor bleeding) were significantly reduced in the experimental group compared with the control group (p < 05). Conclusion: Application of Warfarin Dosing Calculator software to guide individualized warfarin dosing may be better than a fixed dose of 2.5 mg/d. It may be shorten the time to first International Normalized Ratio attainment, and the attainment rate in the same time, and can better improve the mean Time in therapeutic range level value and reduce excessive anticoagulation events, which improves the safety of warfarin anticoagulation therapy in clinical practice. Clinical Trial Registration: https://www.chictr.org.cn/showproj.html?proj=52793, ChiCTR2000032393.

Optimizing warfarin dosing using deep reinforcement learning

Warfarin is a widely used anticoagulant, and has a narrow therapeutic range. Dosing of warfarin should be individualized, since slight overdosing or underdosing can have catastrophic or even fatal consequences. Despite much research on warfarin dosing, current dosing protocols do not live up to expectations, especially for patients sensitive to warfarin. We propose a deep reinforcement learning-based dosing model for warfarin. To overcome the issue of relatively small sample sizes in dosing trials, we use a Pharmacokinetic/ Pharmacodynamic (PK/PD) model of warfarin to simulate dose-responses of virtual patients. Applying the proposed algorithm on virtual test patients shows that this model outperforms a set of clinically accepted dosing protocols by a wide margin. We tested the robustness of our dosing protocol on a second PK/PD model and showed that its performance is comparable to the set of baseline protocols.

Validation and comparison between two warfarin dosing clinical algorithms and warfarin fixed dosing in specialized heart center: cross-sectional study

Background

Warfarin is well known as a narrow therapeutic index that has prodigious variability in response which challenges dosing adjustment for the maintenance of therapeutic international normalized ratio. However, an appreciated population not on new oral anticoagulants may still need to be stabilized with warfarin dosing.

Objective

The current study's main objective was to validate and compare two models of warfarin clinical algorithm models namely the Gage and the International Warfarin Pharmacogenetics Consortium (IWPC) with warfarin 5 mg fixed standard dosing strategy in a sample of Sudanese subjects.

Method

We have conducted a cross-sectional study recruited from the out-patient clinic at a tertiary specialized heart center. We included subjects with unchanged warfarin dose (stabilized), and with therapeutic international normalized ratio. The predicted doses of warfarin in the two models were calculated by three different methods (accuracy, clinical practicality, and the clinical safety of the clinical algorithms).

Main outcome measure

The primary outcomes were the measurements of the clinical (accuracy, practicality, and safety) in each of the two clinical algorithms models compared to warfarin 5 mg fixed standard dose strategy.

Results

We have enrolled 71 Sudanese subjects with mean age (51.7 ± 14 years), of which (49, 69.0%) were females. There was no significant difference between the warfarin 5 mg fixed standard dose strategy and the predicted doses of the two clinical algorithm models (MAE 1.44, 1.45, and 1.49 mg/day [P =0.4]) respectively. In the clinical practicality, all of the three models had a high percent of subjects (95.0%, 51.9%, and 66.7%) in the ideal dose range in middle dose group (3-7 mg/ day) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithm models respectively. However, a small percent of subjects was exhibited in the warfarin low dose group ≤ 3 mg/day (0.0%, 15.0%, and 10.0%) and warfarin high dose group ≥ 7 mg/day (0.0%, 33.3%, and 33.3%) for warfarin 5 mg fixed standard dosing strategy, Gage, and IWPC clinical algorithms respectively. In terms of clinical safety, the percent of subjects with severely over-prediction were 28.2%, 22.5%, and 22.5% for warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively. While the percent of severely under-prediction was 12.7%, 7.0%, and 5.6% for the warfarin 5 mg fixed standard dosing, Gage, and IWPC, respectively.

Conclusion

The Gage and IWPC clinical algorithm models were accurate, more clinically practical, and clinically safe than warfarin 5 mg standard dosing in the study population. The cardiologist can use either models (Gage and IWPC) to stratify subjects for accurate, practical, and clinically safe warfarin dosing..

Long Short-Term Memory Network for Development and Simulation of Warfarin Dosing Model Based on Time Series Anticoagulant Data

Background

Warfarin is an effective treatment for thromboembolic disease but has a narrow therapeutic index, and dosage can differ tremendously among individuals. The study aimed to develop an individualized international normalized ratio (INR) model based on time series anticoagulant data and simulate individualized warfarin dosing.

Methods

We used a long short-term memory (LSTM) network to develop an individualized INR model based on data from 4,578 follow-up visits, including clinical and genetic factors from 624 patients whom we enrolled in our previous randomized controlled trial. The data of 158 patients who underwent valvular surgery and were included in a prospective registry study were used for external validation in the real world.

Results

The prediction accuracy of LSTM_INR was 70.0%, which was much higher than that of MAPB_INR (maximum posterior Bayesian, 53.9%). Temporal variables were significant for LSTM_INR performance (51.7 vs. 70.0%, P < 0.05). Genetic factors played an important role in predicting INR at the onset of therapy, while after 15 days of treatment, we found that it might unnecessary to detect genotypes for warfarin dosing. Using LSTM_INR, we successfully simulated individualized warfarin dosing and developed an application (AI-WAR) for individualized warfarin therapy.

Conclusion

The results indicate that temporal variables are necessary to be considered in warfarin therapy, except for clinical factors and genetic factors. LSTM network may have great potential for long-term drug individualized therapy.

Trial Registration

NCT02211326; www.chictr.org.cn:ChiCTR2100052089.

Warfarin sensitivity is associated with increased hospital mortality in critically Ill patients

Background

Warfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Warfarin sensitivity has been reported to be associated with increased incidence of international normalized ratio (INR) > 5. However, whether warfarin sensitivity is a risk factor for adverse outcomes in critically ill patients remains unknown. In the present study, we aimed to evaluate the utility of different machine learning algorithms for the prediction of warfarin sensitivity and to determine the impact of warfarin sensitivity on outcomes in critically ill patients.

Methods

Nine different machine learning algorithms for the prediction of warfarin sensitivity were tested in the International Warfarin Pharmacogenetic Consortium cohort and Easton cohort. Furthermore, a total of 7,647 critically ill patients was analyzed for warfarin sensitivity on in-hospital mortality by multivariable regression. Covariates that potentially confound the association were further adjusted using propensity score matching or inverse probability of treatment weighting.

Results

We found that logistic regression (AUC = 0.879, 95% CI: 0.834–0.924) was indistinguishable from support vector machine with a linear kernel, neural network, AdaBoost and light gradient boosting trees, and significantly outperformed all the other machine learning algorithms. Furthermore, we found that warfarin sensitivity predicted by the logistic regression model was significantly associated with worse in-hospital mortality in critically ill patients with an odds ratio (OR) of 1.33 (95% CI, 1.01–1.77).

Conclusions

Our data suggest that the logistic regression model is the best model for the prediction of warfarin sensitivity clinically and that warfarin sensitivity is likely to be a risk factor for adverse outcomes in critically ill patients.

Warfarin dosing strategies evolution and its progress in the era of precision medicine, a narrative review

Background For decades, vitamin K antagonists and specifically warfarin, have been the sole agents used orally to manage thromboembolic conditions, including stroke and venous thromboembolism (VTE). Several factors lead to warfarin dose variability, including genetic and non-genetic factors which made warfarin management challenging especially at the initiation phase. To overcome the challenges with warfarin dosing at initiation, strategies other than conventional or fixed dosing were introduced and explored. Aim In this narrative review, we aim to discuss and critique the different dosing strategies for warfarin at initiation with more focus on genotype-guided warfarin dosing and the most recent supporting evidence for and against its use. Method Medline database was searched from 1965 to July 2021. Articles addressing different warfarin dosing methods were screened for inclusion. Results A number of methods exist for warfarin initiation. Studies comparing different dosing methods for initiation yielded conflicting outcomes due to differences in study design, population studied, comparator, and outcomes measured. Conclusions Looking at the big picture, the use of genetic dosing for warfarin initiation can lead to better outcomes. Whether these better outcomes are clinically or economically beneficial remains controversial.

Profiling of warfarin pharmacokinetics-associated genetic variants: Black Africans portray unique genetic markers important for an African specific warfarin pharmacogenetics-dosing algorithm

BACKGROUND

Warfarin dose variability observed in patients is attributed to variation in genes involved in the warfarin metabolic pathway. Genetic variation in CYP2C9 and VKORC1 has been the traditional focus in evaluating warfarin dose variability, with little focus on other genes.

OBJECTIVE

We set out to evaluate 27 single nucleotide polymorphisms (SNPs) in the CYP2C cluster loci and 8 genes (VKORC1, ABCB1, CYP2C9, CYP2C19, CYP2C8, CYP1A2, CYP3A4, and CYP3A5) involved in pharmacokinetics of warfarin.

PATIENTS/METHODS

503 participants were recruited among black Africans and Mixed Ancestry population groups, from South Africa and Zimbabwe, and a blood sample taken for DNA. Clinical parameters were obtained from patient medical records, and these were correlated with genetic variation.

RESULTS

Among black Africans, the SNPs CYP2C rs12777823G>A, CYP2C9 c.449G>A (*8), CYP2C9 c.1003C>T (*11) and CYP2C8 c.805A>T (*2) were significantly associated with warfarin maintenance dose. Conversely, CYP2C9 c.430C>T (*2), CYP2C8 c.792C>G (*4) and VKORC1 g.-1639G>A were significantly associated with maintenance dose among the Mixed Ancestry. The presence of CYP2C8*2 and CYP3A5*6 alleles was associated with increased mean warfarin maintenance dose, whereas CYP2C9*8 allele was associated with reduced warfarin maintenance dose.

CONCLUSION

African populations present with a diversity of variants that are important in predicting pharmacogenetics-based warfarin dosing in addition to those reported in CYP2C9 and VKORC1. It is therefore important, to include African populations in pharmacogenomics studies to be able to identify all possible biomarkers that are potential predictors for drug response.

A post-hoc interpretable ensemble model to feature effect analysis in warfarin dose prediction for Chinese patients

To interprete the importance of clinical features and genotypes for warfarin daily dose prediction, we developed a post-hoc interpretable framework based on an ensemble predictive model. This framework includes permutation importance for global interpretation and local interpretable model-agnostic explanation (LIME) and shapley additive explanations (SHAP) for local explanation. The permutation importance globally ranks the importance of features on the whole data set. This can guide us to build a predictive model with less variables and the complexity of final predictive model can be reduced. LIME and SHAP together explain how the predictive model give the predicted dosage for specific samples. This help clinicians prescribe accurate doses to patients using more effective clinical variables. Results showed that both the permutation importance and SHAP demonstrated that VKORC1, age, serum creatinine (SCr), left atrium (LA) size, CYP2C9 and weight were the most important features on the whole data set. In specific samples, both SHAP and LIME discovered that in Chinese patients, wild-type VKORC1-AA, mutant-type CYP2C9*3, age over 60, abnormal LA size, SCr within the normal range, and using amiodarone definitely required dosage reduction, whereas mutant-type VKORC1-AG/GG, small age, SCr out of normal range, normal LA size, diabetes and heavy weight required dosage enhancement.

Influence of renal insufficiency on anticoagulant effects and safety of warfarin in Chinese patients: analysis from a randomized controlled trial

This study aimed to analyze the influence of renal insufficiency on the anticoagulant effects and safety of warfarin in Chinese patients. Data on the creatinine levels of participants enrolled in a randomized controlled study were screened and divided into the non-renal insufficiency group, mild renal insufficiency group, and moderate renal insufficiency group, according to the creatinine clearance rate. The primary outcome measures were stable dose and average daily dose of warfarin. Secondary outcome measures were percentage of time in the therapeutic international normalized ratio (INR) (%TTR), and the first time to reach the therapeutic INR. Adverse events included bleeding events, thromboembolic events, and mortality. All participants with renal function test results and a baseline INR of less than 1.5 were included in the primary and secondary outcome analysis. The SPSS Statistics 21.0 software was used for statistical analysis. The randomized controlled trial was registered in Clinicaltrials.gov (NCT02211326). A total of 571 patients were included in this analysis. Multiple regression analysis showed that the renal function was correlated with stable dose, average daily dose, and the first time to reach therapeutic INR after adjusting for confounding factors. However, no correlation was noted between kidney function and %TTR. No significant differences were observed across the various safety parameters among the three groups. Renal function is an important consideration in patients using warfarin.

Differences in Predicted Warfarin Dosing Requirements Between Hmong and East Asians Using Genotype-Based Dosing Algorithms

INTRODUCTION

Warfarin's narrow therapeutic index and high variability in dosage requirements make dosage selection critical. Genetic factors are known to impact warfarin dosage selection. The Hmong are a unique Asian subpopulation numbering over 278,000 in the United States whose participation in genetics-based research is virtually nonexistent. The translational significance of early reports of warfarin pharmacogene differences in Hmong has not been evaluated.

OBJECTIVES

(i) To validate previously identified allele frequency differences relevant to warfarin dosing in Hmong versus East Asians and (ii) to compare predicted warfarin sensitivity and maintenance doses between a Hmong population and an East Asian cohort.

METHOD

DNA collected from two independent cohorts (n=236 and n=198) of Hmong adults were genotyped for CYP2C9 (*2, *3), VKORC1 (G-1639A), and CYP4F2 (*3). Allele frequencies between the combined Hmong cohort (n=433) and East Asians (n=1165) from the 2009 International Warfarin Pharmacogenetics Consortium (IWPC) study were compared using a χ² test. Percentages of Hmong and East Asian participants predicted to be very sensitive to warfarin were compared using a χ² test, and the predicted mean warfarin maintenance dose was compared with a t test.

RESULTS

The allele frequencies of CYP2C9*3 in the combined Hmong cohort and CYP4F2*3 in the VIP-Hmong cohort are significantly different from those in East Asians (18.9% vs 3.0%, p<0.001 and 9.8% vs 22.1%, p<0.001, respectively). Comparing the combined Hmong cohort to the East Asian cohort, the percentage of participants predicted to be very sensitive to warfarin was significantly higher (28% vs 5%, p<0.01) and the mean predicted warfarin maintenance dose was significantly lower (19.8 vs 21.3 mg/week, p<0.001), respectively.

CONCLUSION

The unique allele frequencies related to warfarin when combined with nongenetic factors observed in the Hmong translate into clinically relevant differences in predicted maintenance dose requirements for Hmong versus East Asians.

Warfarin dosing algorithms: A systematic review

Aims

Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.

Methods

We systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.

Results

Of 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.

Conclusion

Most warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under‐served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under‐represented populations should be prioritized.

Genetic polymorphisms and dosing of vitamin K antagonist in Indian patients after heart valve surgery

Purpose

Vitamin K antagonists (VKAs), such as warfarin and acenocoumarol, exert their anti-coagulant effect by inhibiting the subunit 1 of vitamin K epoxide reductase complex (VKORC1). CYP2C9 is a hepatic drug-metabolizing enzyme in the CYP450 superfamily and is the primary metabolizing enzyme of warfarin. Three single nucleotide polymorphisms, two in the CYP2C9 gene, namely CYP2C9*2 and CYP2C9*3, and one in the VKORC1 gene (c.- 1639G > A, rs9923231), have been identified to reduce VKA metabolism and enhance their anti-coagulation effect. The purpose of this study is to evaluate the prevalence of CYP2C9 and VKORC1 polymorphism in Indians receiving VKA-based anti-coagulation after valve surgery and to evaluate the usefulness of genetic information in managing VKA-based anti-coagulation.

Methods

In the current prospective observational study, 150 patients who underwent heart valve surgery and had stable INR were genotyped for VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3. The VKA dosage was estimated from published algorithms and compared to the clinically stabilized dosage.

Results

Out of 150 patients, 101 (67.33%) were on warfarin and 49 (32.66%) were on acenocoumarol. Majority of the patients, the 83 in warfarin group and the 40 in acenocoumarol group, had a wild CYP2C9 diplotype. The rest had a mutant (CYP2C9*2 or CYP2C9*3) diplotype. Similarly, 67 patients in the warfarin group and 35 patients in the acenocoumarol group had wild type (G/G) of VKORC1 genotype. The rest had a mutant (G/A or A/A) VKORC1 genotype. In the warfarin group, based on the genotype, 51.5% of the patients were extensive or normal metabolizers, and 47.4% of the patients were intermediate metabolizers of VKAs. In the acenocoumarol group, 61.2% of the patients were extensive or normal metabolizers, and 38.8% of the patients were intermediate metabolizers. Individually, alleles of VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3 had mean dosage reduction effect on VKA dosage, which co-related to the clinically stabilized dosages (P < 0.0001). Among the VKORC1 (- 1639 G > A) cohort, the reduction in warfarin mean weekly dosage was 13.48 mg as compared to the wild-type category (P < 0.0001) and similarly, the reduction in the mean weekly acenocoumarol dose was 6.07 mg (P < 0.03) as compared to the wild type after adjusting for age, gender, and body mass index.

Conclusion

Single nucleotide polymorphism in the CYP2C9 gene and in the VKORC1 gene is present in nearly 40% of Indian patients. VKORC1 (- 1639 G > A), CYP2C9*2, and CYP2C9*3 genotypes have significant dosage-lowering effects on VKA-based anti-coagulation therapy. The trend in estimated dosages of VKAs co-related to that of observed the clinically stabilized dosage in the cohort. The pharmacogenomic calculators used in this study tend to overestimate the VKA dosages as compared to clinical dosage due to the limitations in the algorithms and in our study. A new algorithm based on a larger dataset capturing the vast genetic variability across the Indian population and relevant clinical factors could provide better results.

Quality of oral anticoagulation control in Chinese patients with non-valvular atrial fibrillation: a prospective controlled study

OBJECTIVE

The sex, age, medical history, treatment, tobacco use, race risk (SAMe-TT₂R₂) Score; the sex, age, medical history, treatment, tobacco use, genotype combination (SAMe-TT₂G₂) Score; and the so-called modified SAMe-TT₂R₂ scores have been proposed to predict the anticoagulation quality for patients with non-valvular atrial fibrillation (NVAF). The data from a prospective controlled study is used to validate the SAMe-TT₂R₂ and SAMe-TT₂G₂ scores in Chinese NVAF patients treated with warfarin and to evaluate the association of factors with time in therapeutic range (TTR) to predict the quality of oral anticoagulation control.

METHODS

A total of 379 patients with NVAF under warfarin treatment for a three-month follow-up were included in this prospective, multicenter study. The quality of oral anticoagulation control was evaluated by the TTR. The TTR was dichotomized for binary logistic regression analysis, using a cutoff point for classification as an inadequate (TTR < 65.0%) control.

RESULTS

The 379 NVAF patients had a mean TTR of 58.35 ± 26.33% and median SAMe-TT₂R₂ and SAMe-TT₂G₂ scores of 3 and 2, respectively. The discrimination performances of the SAMe-TT₂R₂ and SAMe-TT₂G₂ scores for inadequate anticoagulation control (TTR < 65.0%) were poor (c-index < 0.60). The gene frequency of CYP2C9*3 was 3.2% and that of VKORC1-1639 G > A was 89.3%. Genetic variation of CYP2C9*3 and VKORC1-1639 G > A did not affect TTR after initial treatment. The condition TTR < 65.0% was associated with an age below 60 without genotype-guided warfarin dose initiation and concomitant torasemide.

CONCLUSIONS

A warfarin-dosing algorithm used for initial treatment of patients older than 60 helps to achieve a better quality of oral anticoagulation control, whereas concomitant torasemide can produce a negative effect. These findings provide useful information for future investigations on the quality of oral anticoagulation control in Chinese anticoagulation clinical practice.

Development and Validation of a Novel Warfarin Dosing Algorithm for Korean Patients With VKORC1 1173C

BACKGROUND

Differences in the performance of suggested warfarin dosing algorithms among different ethnicities and genotypes have been reported; this necessitates the development of an algorithm with enhanced performance for specific population groups. Previous warfarin dosing algorithms underestimated warfarin doses in VKORC1 1173C carriers. We aimed to develop and validate a new warfarin dosing algorithm for Korean patients with VKORC1 1173C.

METHODS

A total of 109 patients carrying VKORC1 1173CT (N=105) or 1173CC (N=4) were included in this study. Multiple regression analysis was performed to deduce a new dosing algorithm. Following literature searches for genotype-guided warfarin dosing algorithms, 21 algorithms were selected and evaluated using the correlation coefficient (ρ) of actual dose and estimated dose, mean error, and root mean square error.

RESULTS

The developed algorithm is as follows: maintenance dose (mg/week)=exp [3.223-0.009×(age)+0.577×(body surface area [BSA])+0.178×(sex)-0.481×(CYP2C9 genotype)+0.227×(VKORC1 genotype)]. Integrated variables explained 44% of the variance in the maintenance dose. The predicted and actual doses showed moderate correlation (ρ=0.641) with the best performance with a mean error of -1.30 mg/week. The proportion of underestimated groups was 17%, which was lower than with the other algorithms.

CONCLUSIONS

This is the first study to develop and validate a warfarin dosing algorithm based on data from VKORC1 1173C carriers; it showed superior predictive performance compared with previously published algorithms.

Impact of CYP2C9-Interacting Drugs on Warfarin Pharmacogenomics

Precise dosing of warfarin is important to achieve therapeutic benefit without adverse effects. Pharmacogenomics explains some interindividual variability in warfarin response, but less attention has been paid to drug‐drug interactions in the context of genetic factors. We investigated retrospectively the combined effects of cytochrome P450 (CYP)2C9 and vitamin K epoxide reductase complex (VKORC)1 genotypes and concurrent exposure to CYP2C9‐interacting drugs on long‐term measures of warfarin anticoagulation. Study participants predicted to be sensitive responders to warfarin based on CYP2C9 and VKORC1 genotypes, had significantly greater international normalized ratio (INR) variability over time. Participants who were concurrently taking CYP2C9‐interacting drugs were found to have greater INR variability and lesser time in therapeutic range. The associations of INR variability with genotype were driven by the subgroup not exposed to interacting drugs, whereas the effect of interacting drug exposure was driven by the subgroup categorized as normal responders. Our findings emphasize the importance of considering drug interactions in pharmacogenomic studies.

Oral Anticoagulant Therapy-When Art Meets Science

Anticoagulant treatment is extremely important and frequently encountered in the therapy of various cardiovascular diseases. Vitamin K antagonists (VKA) are in use for the prevention and treatment of arterial and venous thromboembolism, despite the introduction of new direct-acting oral anticoagulants (NOAC). The VKA still have the clear recommendation in patients with a mechanical prosthetic heart valve replacement or moderate to severe mitral stenosis of the rheumatic origin, in deep vein thrombosis associated with congenital thrombophilia, and in cases where NOAC are prohibited by social condition (financial reason) or by comorbidities (extreme weight, severe renal or liver disease). VKA dosing required to reach the targeted therapeutic range varies largely between patients (inter-individual variability). This inter-individual variability depends on multiple environmental factors such as age, mass, diet, etc. but it is also influenced by genetic determinism. About 30 genes implicated in the metabolism coumarins derivatives were identified, the most important being CYP2C9 and VKORC, each with several polymorphisms. Herein, we review the data regarding genetic alterations in general and specific populations, highlight the diagnosis options in particular cases presenting with genetic alteration causing higher sensitivity and/or resistance to VKA therapy and underline the utility of NOAC in solving such rare and difficult problems.

Clinical Model for Predicting Warfarin Sensitivity

Warfarin is a widely used anticoagulant with a narrow therapeutic index and large interpatient variability in the therapeutic dose. Complications from inappropriate warfarin dosing are one of the most common reasons for emergency room visits. Approximately one third of warfarin dose variability results from common genetic variants. Therefore, it is very necessary to recognize warfarin sensitivity in individuals caused by genetic variants. Based on combined polymorphisms in CYP2C9 and VKORC1, we established a clinical classification for warfarin sensitivity. In the International Warfarin Pharmacogenetic Consortium (IWPC) with 5542 patients, we found that 95.1% of the Black in the IWPC cohort were normal warfarin responders, while 74.8% of the Asian were warfarin sensitive (P < 0.001). Moreover, we created a clinical algorithm to predict warfarin sensitivity in individual patients using logistic regression. Compared to a fixed-dose approach, the clinical algorithm provided significantly better performance. In addition, we validated the derived clinical algorithm using the external Easton cohort with 106 chronic warfarin users. The AUC was 0.836 vs. 0.867 for the Easton cohort and the IWPC cohort, respectively. With the use of this algorithm, it is very likely to facilitate patient care regarding warfarin therapy, thereby improving clinical outcomes.

Warfarin Dosing and Outcomes in Chronic Kidney Disease: A Closer Look at Warfarin Disposition

BACKGROUND

Chronic Kidney Disease (CKD) is a prevalent worldwide health problem. Patients with CKD are more prone to developing cardiovascular complications such as atrial fibrillation and stroke. This warrants the use of oral anticoagulants, such as warfarin, in this population. While the efficacy and safety of warfarin in this setting remain controversial, a growing body of evidence emphasizes that warfarin use in CKD can be problematic. This review discusses 1) warfarin use, dosing and outcomes in CKD patients; and 2) possible pharmacokinetic mechanisms for altered warfarin dosing and response in CKD.

METHODS

Structured search and review of literature articles evaluating warfarin dosing and outcomes in CKD. Data and information about warfarin metabolism, transport, and pharmacokinetics in CKD were also analyzed and summarized.

RESULTS

The literature data suggest that changes in warfarin pharmacokinetics such as protein binding, nonrenal clearance, the disposition of warfarin metabolites may partially contribute to altered warfarin dosing and response in CKD.

CONCLUSION

Although the evidence to support warfarin use in advanced CKD is still unclear, this synthesis of previous findings may help in improving optimized warfarin therapy in CKD settings.

Pharmacogenetics of anticoagulants used for stroke prevention in patients with atrial fibrillation

Introduction: The inclusion of pharmacogenetics alongside clinical information in anticoagulant therapy offers the opportunity for a tailored approach to treatment according to individual patient characteristics. Areas covered: Literature was searched using PubMed database, focusing on pharmacogenetics of oral anticoagulants. Original research articles and review articles in English language were included in the literature reviewed. This article includes all information available for the genetic cause of inter-individual variability in anticoagulation response to oral anticoagulant drugs. The pharmacogenetics of VKAs and NOACs are described in detail. Expert opinion: There have been numerous studies focusing on the pharmacogenetics of VKAs, particularly warfarin. Current evidence suggests that known genetic and clinical factors explain a large proportion of the inter-individual variability in response to warfarin. Pharmacogenetic-based algorithms have been validated to determine their clinical utility with equivocal results. To date, only a limited number of mostly small studies on the pharmacogenetics of NOACs exists. The latter have highlighted genetic polymorphisms in specific genes that may affect clinical outcomes. Further evaluations of these polymorphisms are needed before firm conclusions can be drawn about the significance of pharmacogenetics on NOAC therapy.

Precision dosing of warfarin: open questions and strategies

Warfarin has a very narrow therapeutic window and obvious interindividual variability in its effects, with many factors contributing to the body's response. Algorithms incorporating multiple genetic, environment and clinical factors have been established to select a precision dose for each patient. A number of randomized controlled trials (RCTs) were conducted to explore whether patients could benefit from these algorithms; however, the results were inconsistent. Some questions remain to be resolved. Recently, new genetic and non-genetic factors have been discovered to contribute to variability in optimal warfarin doses. The results of further RCTs have been unveiled, and guidelines for pharmacogenetically guided warfarin dosing have been updated. Based on these most recent advancements, we summarize some open questions in this field and try to propose possible strategies to resolve them.

Evaluation of the predictive performance of Bayesian dosing for warfarin in Chinese patients

Aim: To evaluate the accuracy and predictive performance of Bayesian dosing for warfarin in Chinese patients. Materials & methods: Six multiple linear regression algorithms (Wei, Lou, Miao, Huang, Gage and IWPC) and a Bayesian method implemented in Warfarin Dose Calculator were compared with each other. Results: Six multiple linear regression warfarin dosing algorithms had similar predictive ability, except Miao and Lou. The mean prediction error of Bayesian priori and posteriori method were 0.01 mg/day (95% CI: -0.18 to 0.19) and 0.17 mg/day (95% CI: -0.05 to 0.29), respectively, and Bayesian posteriori method demonstrated better performance in all dose ranges. Conclusion: The Bayesian method showed a good potential for warfarin maintenance dose prediction in Chinese patients requiring less than 6 mg/day.

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.

Impact of CYP2C9 and VKORC1 Polymorphisms on Warfarin Sensitivity and Responsiveness in Jordanian Cardiovascular Patients during the Initiation Therapy

Warfarin is an oral anticoagulant frequently used in the treatment of different cardiovascular diseases. Genetic polymorphisms in the CYP2C9 and VKORC1 genes have produced variants with altered catalytic properties. A total of 212 cardiovascular patients were genotyped for 17 Single Nucleotide Polymorphisms (SNPs) within the CYP2C9 and VKORC1 genes. This study confirmed a genetic association of the CYP2C9*3 and VKORC1 rs10871454, rs8050894, rs9934438, and rs17708472 SNPs with warfarin sensitivity. This study also found an association between CYP2C9 and VKORC1 genetic haplotype blocks and warfarin sensitivity. The initial warfarin dose was significantly related to the CYP2C9*3 polymorphism and the four VKORC1 SNPs (p < 0.001). There were significant associations between rs4086116 SNP and TAT haplotype within CYP2C9 gene and rs17708472 SNP and CCGG haplotype within VKORC1 gene and warfarin responsiveness. However, possessing a VKORC1 variant allele was found to affect the international normalized ratio (INR) outcomes during initiation of warfarin therapy. In contrast, there was a loose association between the CYP2C9 variant and INR measurements. These findings can enhance the current understanding of the great variability in response to warfarin treatment in Arabs.

Evaluation of oral anticoagulants with vitamin K epoxide reductase in its native milieu

Warfarin, acenocoumarol, phenprocoumon, and fluindione are commonly prescribed oral anticoagulants for the prevention and treatment of thromboembolic disorders. These anticoagulants function by impairing the biosynthesis of active vitamin K-dependent coagulation factors through the inhibition of vitamin K epoxide reductase (VKOR). Genetic variations in VKOR have been closely associated with the resistant phenotype of oral anticoagulation therapy. However, the relative efficacy of these anticoagulants, their mechanisms of action, and their resistance variations among naturally occurring VKOR mutations remain elusive. Here, we explored these questions using our recently established cell-based VKOR activity assay with the endogenous VKOR function ablated. Our results show that the efficacy of these anticoagulants on VKOR inactivation, from most to least, is: acenocoumarol > phenprocoumon > warfarin > fluindione. This is consistent with their effective clinical dosages for stable anticoagulation control. Cell-based functional studies of how each of the 27 naturally occurring VKOR mutations responds to these 4 oral anticoagulants indicate that phenprocoumon has the largest resistance variation (up to 199-fold), whereas the resistance of acenocoumarol varies the least (<14-fold). Cell-based kinetics studies show that fluindione appears to be a competitive inhibitor of VKOR, whereas warfarin is likely to be a mixed-type inhibitor of VKOR. The anticoagulation effect of these oral anticoagulants can be reversed by the administration of a high dose of vitamin K, apparently due to the existence of a different enzyme that can directly reduce vitamin K. These findings provide new insights into the selection of oral anticoagulants, their effective dosage management, and their mechanisms of anticoagulation.

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.

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with devastating adverse events. Remarkable efforts have been made to develop the machine learning based warfarin dosing algorithms incorporating clinical factors and genetic variants such as polymorphisms in CYP2C9 and VKORC1. The most widely validated pharmacogenetic algorithm is the IWPC algorithm based on multivariate linear regression (MLR). However, with only a single algorithm, the prediction performance may reach an upper limit even with optimal parameters. Here, we present novel algorithms using stacked generalization frameworks to estimate the warfarin dose, within which different types of machine learning algorithms function together through a meta-machine learning model to maximize the prediction accuracy. Compared to the IWPC-derived MLR algorithm, Stack 1 and 2 based on stacked generalization frameworks performed significantly better overall. Subgroup analysis revealed that the mean of the percentage of patients whose predicted dose of warfarin within 20% of the actual stable therapeutic dose (mean percentage within 20%) for Stack 1 was improved by 12.7% (from 42.47% to 47.86%) in Asians and by 13.5% (from 22.08% to 25.05%) in the low-dose group compared to that for MLR, respectively. These data suggest that our algorithms would especially benefit patients requiring low warfarin maintenance dose, as subtle changes in warfarin dose could lead to adverse clinical events (thrombosis or bleeding) in patients with low dose. Our study offers novel pharmacogenetic algorithms for clinical trials and practice.

User considerations in assessing pharmacogenomic tests and their clinical support tools

Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management. However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users. Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support. Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients. Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation.

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.

Impact of incorporating ABCB1 and CYP4F2 polymorphisms in a pharmacogenetics-guided warfarin dosing algorithm for the Brazilian population

PURPOSE

Interpatient variation of warfarin dose requirements may be explained by genetic variations and general and clinical factors. In this scenario, diverse population-calibrated dosing algorithms, which incorporate the main warfarin dosing influencers, have been widely proposed for predicting supposed warfarin maintenance dose, in order to prevent and reduce adverse events. The aim of the present study was to evaluate the impact of the inclusion of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms as additional covariates in a previously developed pharmacogenetic-based warfarin dosing algorithm calibrated for the Brazilian population.

METHODS

Two independent cohorts of patients treated with warfarin (n = 832 and n = 133) were included for derivation and replication of the algorithm, respectively. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms was performed by polymerase chain reaction followed by melting curve analysis and TaqMan® assay, respectively. A multiple linear regression was performed for the warfarin stable doses as a dependent variable, considering clinical, general, and genetic data as covariates.

RESULTS

The inclusion of ABCB1 and CYP4F2 polymorphisms was able to improve the algorithm's coefficient of determination (R²) by 2.6%. In addition, the partial determination coefficients of these variants revealed that they explained 3.6% of the warfarin dose variability. We also observed a marginal improvement of the linear correlation between observed and predicted doses (from 59.7 to 61.4%).

CONCLUSION

Although our study indicates that the contribution of the combined ABCB1 and CYP4F2 genotypes in explaining the overall variability in warfarin dose is not very large, we demonstrated that these pharmacogenomic data are statistically significant. However, the clinical relevance and cost-effective impact of incorporating additional variants in warfarin dosing algorithms should be carefully evaluated.

Personalized Anticoagulation: Optimizing Warfarin Management Using Genetics and Simulated Clinical Trials

BACKGROUND

Clinical trials testing pharmacogenomic-guided warfarin dosing for patients with atrial fibrillation have demonstrated conflicting results. Non-vitamin K antagonist oral anticoagulants are expensive and contraindicated for several conditions. A strategy optimizing anticoagulant selection remains an unmet clinical need.

METHODS AND RESULTS

Characteristics from 14 206 patients with atrial fibrillation were integrated into a validated warfarin clinical trial simulation framework using iterative Bayesian network modeling and a pharmacokinetic-pharmacodynamic model. Individual dose-response for patients was simulated for 5 warfarin protocols-a fixed-dose protocol, a clinically guided protocol, and 3 increasingly complex pharmacogenomic-guided protocols. For each protocol, a complexity score was calculated using the variables predicting warfarin dose and the number of predefined international normalized ratio (INR) thresholds for each adjusted dose. Study outcomes included optimal time in therapeutic range ≥65% and clinical events. A combination of age and genotype identified different optimal protocols for various subpopulations. A fixed-dose protocol provided well-controlled INR only in normal responders ≥65, whereas for normal responders <65 years old, a clinically guided protocol was necessary to achieve well-controlled INR. Sensitive responders ≥65 and <65 and highly sensitive responders ≥65 years old required pharmacogenomic-guided protocols to achieve well-controlled INR. However, highly sensitive responders <65 years old did not achieve well-controlled INR and had higher associated clinical events rates than other subpopulations.

CONCLUSIONS

Under the assumptions of this simulation, patients with atrial fibrillation can be triaged to an optimal warfarin therapy protocol by age and genotype. Clinicians should consider alternative anticoagulation therapy for patients with suboptimal outcomes under any warfarin protocol.

Genotype-guided versus traditional clinical dosing of warfarin in patients of Asian ancestry: a randomized controlled trial

BACKGROUND

Genotype-guided warfarin dosing has been shown in some randomized trials to improve anticoagulation outcomes in individuals of European ancestry, yet its utility in Asian patients remains unresolved.

METHODS

An open-label, non-inferiority, 1:1 randomized trial was conducted at three academic hospitals in South East Asia, involving 322 ethnically diverse patients newly indicated for warfarin (NCT00700895). Clinical follow-up was 90 days. The primary efficacy measure was the number of dose titrations within the first 2 weeks of therapy, with a mean non-inferiority margin of 0.5 over the first 14 days of therapy.

RESULTS

Among 322 randomized patients, 269 were evaluable for the primary endpoint. Compared with traditional dosing, the genotype-guided group required fewer dose titrations during the first 2 weeks (1.77 vs. 2.93, difference -1.16, 90% CI -1.48 to -0.84, P < 0.001 for both non-inferiority and superiority). The percentage of time within the therapeutic range over 3 months and median time to stable international normalized ratio (INR) did not differ between the genotype-guided and traditional dosing groups. The frequency of dose titrations (incidence rate ratio 0.76, 95% CI 0.67 to 0.86, P = 0.001), but not frequency of INR measurements, was lower at 1, 2, and 3 months in the genotype-guided group. The proportions of patients who experienced minor or major bleeding, recurrent venous thromboembolism, or out-of-range INR did not differ between both arms. For predicting maintenance doses, the pharmacogenetic algorithm achieved an R² = 42.4% (P < 0.001) and mean percentage error of -7.4%.

CONCLUSIONS

Among Asian adults commencing warfarin therapy, a pharmacogenetic algorithm meets criteria for both non-inferiority and superiority in reducing dose titrations compared with a traditional dosing approach, and performs well in prediction of actual maintenance doses. These findings imply that clinicians may consider applying a pharmacogenetic algorithm to personalize initial warfarin dosages in Asian patients.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00700895 . Registered on June 19, 2008.

Pharmacogenetic studies with oral anticoagulants. Genome-wide association studies in vitamin K antagonist and direct oral anticoagulants

Oral anticoagulants (OAs) are the recommended drugs to prevent cardiovascular events and recurrence in patients with atrial fibrillation (AF) and cardioembolic stroke. We conducted a literature search to review the current state of OAs pharmacogenomics, focusing on Genome Wide Association Studies (GWAs) in patients treated with vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs).

VKAs: Warfarin, acenocoumarol, fluindione and phenprocoumon have long been used, but their interindividual variability and narrow therapeutic/safety ratio makes their dosage difficult. GWAs have been useful in finding genetic variants associated with VKAs response. The main genes involved in VKAs pharmacogenetics are: VKORC1, CYP2C19 and CYP4F2. Variants in these genes have been included in pharmacogenetic algorithms to predict the VKAs dose individually in each patient depending on their genotype and clinical variables.

DOACs: Dabigatran, apixaban, rivaroxaban and edoxaban have been approved for patients with AF. They have stable pharmacokinetics and do not require routine blood checks, thus avoiding most of the drawbacks of VKAs. Except for a GWAs performed in patients treated with dabigatran, there is no Genome Wide pharmacogenomics data for DOACs. Pharmacogenomics could be useful to predict the better clinical response and avoid adverse events in patients treated with anticoagulants, identifying the most appropriate anticoagulant drug for each patient. Current pharmacogenomics data show that the polymorphisms affecting VKAs or DOACs are different, concluding that personalized medicine based on pharmacogenomics could be possible. However, more studies are required to implement personalized medicine in clinical practice with OA and based on pharmacogenetics of DOACs.

Economic evaluation of prescribing conventional and newer oral anticoagulants in older adults

INTRODUCTION

Anticoagulants refer to a variety of agents that inhibit one or more steps in the coagulation cascade. Generally, clinical conditions that require the prescribing of an oral anticoagulant increase in frequency with age. However, a major challenge of anticoagulation use among older patients is that this group of patients also experience the highest bleeding risk. To date, economic evaluation of prescribing of anticoagulants that includes the novel or newer oral anticoagulants (NOACs) in older adults has not been conducted and is warranted.

AREAS COVERED

A review of articles that evaluated the cost of prescribing conventional (e.g. vitamin K antagonists) and NOACs (e.g. direct thrombin inhibitors and direct factor Xa inhibitors) in older adults.

EXPERT COMMENTARY

While the use of NOACs significantly increases the cost of the initial treatment for thromboembolic disorders, they are still considered cost-effective relative to warfarin since they offer reduced risk of intracranial haemorrhagic events. The optimum anticoagulation with warfarin can be achieved by providing specialised care; clinics managed by pharmacists have been shown to be cost-effective relative to usual care. There are suggestions that genotyping the CYP2C9 and VKORC1 genes is useful for determining a more appropriate initial dose and thereby increasing the effectiveness and safety of warfarin.

Pharmacogenomics of CYP2C9: Functional and Clinical Considerations

CYP2C9 is the most abundant CYP2C subfamily enzyme in human liver and the most important contributor from this subfamily to drug metabolism. Polymorphisms resulting in decreased enzyme activity are common in the CYP2C9 gene and this, combined with narrow therapeutic indices for several key drug substrates, results in some important issues relating to drug safety and efficacy. CYP2C9 substrate selectivity is detailed and, based on crystal structures for the enzyme, we describe how CYP2C9 catalyzes these reactions. Factors relevant to clinical response to CYP2C9 substrates including inhibition, induction and genetic polymorphism are discussed in detail. In particular, we consider the issue of ethnic variation in pattern and frequency of genetic polymorphisms and clinical implications. Warfarin is the most well studied CYP2C9 substrate; recent work on use of dosing algorithms that include CYP2C9 genotype to improve patient safety during initiation of warfarin dosing are reviewed and prospects for their clinical implementation considered. Finally, we discuss a novel approach to cataloging the functional capabilities of rare 'variants of uncertain significance', which are increasingly detected as more exome and genome sequencing of diverse populations is conducted.

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

Pharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic dose more accurately;however, most of them are based on standard intensity of warfarin anticoagulation, and their utility outside this range is limited. This study was designed to develop and validate a PG refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under stable warfarin treatment were randomly divided into a derivation (n=207) and a validation cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation, respectively. In the derivation cohort, a PG algorithm was constructed on the basis of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of international normalised ratio (INR) values (INR on day 4 of therapy and target INR) and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and explained 54% of warfarin dose variability. In the validation cohort, warfarin dose prediction was more accurate (p <0.01) with the PG refinement algorithm than with the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the PG refinement algorithm could accurately identify larger proportions of patients with lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction in Chinese patients mainly under low-intensity anticoagulation.

Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool

BACKGROUND

A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions.

METHODS

The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values.

RESULTS

The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations.

CONCLUSIONS

Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.

Tissue Specific Modulation of cyp2c and cyp3a mRNA Levels and Activities by Diet-Induced Obesity in Mice: The Impact of Type 2 Diabetes on Drug Metabolizing Enzymes in Liver and Extra-Hepatic Tissues

Various diseases such as type 2 diabetes (T2D) may alter drug clearance. The objective of this study was to evaluate the effects of T2D on CYP450 expressions and activities using high-fat diet (HFD) as a model of obesity-dependent diabetes in C57BL6 mice. The cyp450 mRNA expression levels for 15 different isoforms were determined in the liver and extra-hepatic tissues (kidneys, lungs and heart) of HFD-treated animals (n = 45). Modulation of cyp450 metabolic activities by HFD was assessed using eight known substrates for specific human ortholog CYP450 isoforms: in vitro incubations were conducted with liver and extra-hepatic microsomes. Expression levels of cyp3a11 and cyp3a25 mRNA were decreased in the liver (>2-14-fold) and kidneys (>2-fold) of HFD groups which correlated with a significant reduction in midazolam metabolism (by 21- and 5-fold in hepatic and kidney microsomes, respectively, p < 0.001). HFD was associated with decreased activities of cyp2b and cyp2c subfamilies in all organs tested except in the kidneys (for tolbutamide). Other cyp450 hepatic activities were minimally or not affected by HFD. Taken together, our data suggest that substrate-dependent and tissue-dependent modulation of cyp450 metabolic capacities by early phases of T2D are observed, which could modulate drug disposition and pharmacological effects in various tissues.

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%).