Genetic-based dosing in orthopedic patients beginning warfarin therapy

Assessing evidence of interaction between smoking and warfarin: a systematic review and meta-analysis

BACKGROUND

Chronic smoking, theoretically, can interfere with warfarin metabolism through enzyme-inducing effects of polycyclic aromatic hydrocarbons. However, clinical evidence of interactions between warfarin and smoking are inconclusive. This study aimed to systematically review all relevant clinical evidence of this interaction.

METHODS

We performed a systematic search using computerized databases, including PubMed, Embase, Cochrane Central Register of Controlled Trials, CINAHL, Allied and Complementary Medicine, PsycINFO, International Pharmaceutical Abstracts, and ClinicalTrials.gov from 1966 to December 2008. Keywords included "warfarin" with "smoking," "tobacco," "cigarette," and "polycyclic aromatic hydrocarbons." Original articles reporting interaction between warfarin and smoking were included. All articles were reviewed independently by two investigators for study design, population, outcomes, and quality of evidence.

RESULTS

Of the 1,240 studies retrieved, one experimental pharmacokinetic study and 12 cross-sectional studies were included. The pooled analyses of multivariate studies suggested that smoking was associated with a 12.13% (95% CI, 6.999-17.265; P < .001) increase in warfarin dosage requirement and an additional 2.26 mg (95% CI, 2.529-7.042; P = .355) per week compared with nonsmoking. Additional sensitivity analysis of four multivariate studies with adjustment for pharmacogenomic factors suggested that smoking was associated with a 13.21% (95% CI, 8.59%-17.83%; P < .001) increase in warfarin dosage requirement compared with nonsmokers. Results of an experimental pharmacokinetic study lend theoretical support to the findings.

CONCLUSIONS

Evidence suggests that smoking may potentially cause significant interaction with warfarin by increasing warfarin clearance, which leads to reduced warfarin effects. Close monitoring of warfarin therapy should be instituted when there is a change in smoking status of patients requiring warfarin therapy.

Evaluation of the effects of VKORC1 polymorphisms and haplotypes, CYP2C9 genotypes, and clinical factors on warfarin response in Sudanese patients

OBJECTIVE

African populations, including the Sudanese, are underrepresented in warfarin pharmacogenetic studies. We designed a study to determine the associations between the polymorphisms and haplotype structures of CYP2C9 and VKORC1 and warfarin dose response in Sudanese patients, one of the most genetically diverse populations in Africa.

MATERIAL AND METHODS

The effect of the CYP2C9 polymorphisms (*2, *3, *5, *6, *8, *9, and *11), 20 VKORC1 tag SNPs and haplotypes, and clinical covariates were comprehensively assessed in 203 Sudanese warfarin-treated patients.

RESULTS

Patients with the CYP2C9*2,*5,*6, or *11 variant required a daily warfarin dose that was 21% lower than those with CYP2C9*1/*1 (4.7 vs 5.8 mg/day, P < 0.001). SNPs around the VKORC1 and POL3S genes were divided into two haplotype blocks in Sudanese populations. According to multiple linear regression results, rs8050984, rs7294, and rs7199949 in the VKORC1 and POL3S genes (P <0.001, <0.001, <0.001, respectively), CYP2C9 genotype (*2, *5, *6, *11; P < 0.001), body weight (P = 0.04), target INR (P = 0.007), and concurrent medications (P = 0.029) could explain about 36.7% of the total warfarin dose variation.

CONCLUSION

Our data revealed that VKORC1 and CYP2C9 polymorphisms are important factors that influence warfarin dose response in Sudanese patients. Our data suggest that combinations of the SNPs may improve predictions of warfarin dose requirements.

Warfarin dosing algorithm using clinical, demographic and pharmacogenetic data from Chinese patients

CYP2C9 and VKORC1 genotypes could be used to predict warfarin requirement. The objective was to develop and validate a warfarin dosing algorithm using genetic, clinical and demographic data of Chinese patients from an anticoagulation clinic in Hong Kong. Blood samples were collected from 100 patients on stable maintenance dose of warfarin, recruited from an anticoagulation clinic, for genotyping CYP2C9 and VKORC1. Clinical and demographic data were obtained by face-to-face interview and medical chart review. Data of 80 patients (study cohort) were randomly selected for deriving a dosing algorithm. Comparison between predicted dose and actual stable doses was conducted in a validation cohort (n = 20). Sixty-nine (69%) of all 100 patients were homozygous for VKORC1 1173-TT, 25 (25%) were VKORC1 1173-CT heterozygotes and six (6%) were homozygous for VKORC1 1173-CC. 6 (6%) patients were CYP2C9 1*/3* and 94 (94%) were CYP2C9 1*/1*. CYP2C9 and VKORC1 genotype, age, weight and vitamin K intake were identified by stepwise regression modelling to produce the best model for estimating warfarin dose (R (2) = 68%, P < 0.001). In the validation cohort (n = 20), actual stable dose was significantly associated with predicted dose (R = 0.6, P = 0.005). Five of 11 (45.6%) and 5/9 (55.6%) patients whose mean warfarin requirements were ≤ 3 mg/day and >3 mg/day, respectively, were within <20% of actual doses. In conclusion, a genotype-guided dosing algorithm for warfarin therapy was developed for Chinese patients to explain 68% of dosage variation. The predicted doses differed from the actual doses by no more than 20% in 50% of patients.

Predicting the warfarin maintenance dose in elderly inpatients at treatment initiation: accuracy of dosing algorithms incorporating or not VKORC1/CYP2C9 genotypes

BACKGROUND

Initiating warfarin is challenging in frail elderly patients because of low-dose requirements and interindividual variability.

OBJECTIVES

We investigated whether incorporating VKORC1 and CYP2C9 genotype information in different models helped to predict the warfarin maintenance dose when added to clinical data and INR values at baseline (Day 0), and during warfarin induction.

PATIENTS

We prospectively enrolled 187 elderly inpatients (mean age, 85.6 years), all starting on warfarin using the same 'geriatric dosing-algorithm' based on the INR value measured on the day after three 4-mg warfarin doses (INR(3)) and on INR(6 ± 1).

RESULTS

On Day 0, the clinical model failed to accurately predict the maintenance dose (R(2) < 0.10). Adding the VKORC1 and CYP2C9 genotypes to the model increased R(2) to 0.31. On Day 3, the INR(3) value was the strongest predictor, completely embedding the VKORC1 genotype, whereas the CYP2C9 genotype remained a significant predictor (model- R(2) 0.55). On Day 6 ± 1, none of the genotypes predicted the maintenance dose. Finally, the simple 'geriatric dosing-algorithm' was the most accurate algorithm on Day 3 (R(2) 0.77) and Day 6 (R(2) 0.81), under-estimating (≥ 1 mg) and over-estimating the dose (≥ 1 mg) in fewer than 10% and 2% of patients, respectively. Clinical models and the 'geriatric dosing-algorithm' were validated on an independent sample.

CONCLUSIONS

Before starting warfarin therapy, the VKORC1 genotype is the best predictor of the maintenance dose. Once treatment is started using induction doses tailored for elderly patients, the contribution of VKORC1 and CYP2C9 genotypes in dose refinement is negligible compared with two INR values measured during the first week of treatment.

Global Formulary Review: How Do We Integrate Pharmacogenomic Information?

Objective:

To summarize a standard formulary decision process and provide recommendations for the integration of pharmacogenomic (PGx) information within the formulary decision-making process.

Data Sources:

With use of MEDLINE (1920-March 2010). the terms “formularies, hospital” and “pharmacogenetics” were searched in the MeSH database, yielding no results. The MeSH terms were then searched separately in addition to searching for “rational drug therapy” and “essential medicines list” through the main PubMed database.

Study Selection and Data Extraction:

Articles deemed relevant to both terms were assessed, interpreted, and incorporated as key pieces to the review of formularies and the integration of PGx information as a part of the formulary review process. The articles referenced were deemed appropriate and categorized into 5 areas: formulary management systems and pharmacy and therapeutics (P&T) committees, international formularies, formulary decision-making. PGx evidence, and recommendations regarding integrating PGx into formulary decision-making.

Data Synthesis:

The field of PGx is rapidly evolving as the evidence supporting genetically guided individualized therapy continues to grow. To bring this evidence from the bench to the bedside, institutions will need to evaluate PGx data to integrate individualized therapy into practice. Few standardized methods exist to analyze and apply clinical PGx data and incorporate the information into drug evaluation at the formulary level. Several online sites provide resources to aid in formulary review and can be used when incorporating clinically relevant PGx information into a formulary decision. In addition, there are key questions that organizations can ask as they evaluate the PGx information in each step of the decision-making process.

Conclusions:

P&T committees should formulate a plan to integrate a search for pharmacogenomic data with each drug evaluation and integrate the results into the formulary decision process to enhance the appraisal of drug efficacy, safety, and cost.

In pediatric patients, age has more impact on dosing of vitamin K antagonists than VKORC1 or CYP2C9 genotypes

Anticoagulation with vitamin K antagonists (VKAs) is problematic because of difficulties in safely managing dosing. Polymorphisms in cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase genes (VKORC1) have been shown to affect VKA dosing in adults. The association of these polymorphisms on VKA dosing in children has not been investigated. The objective of the study was to assess associations of CYP2C9 and VKORC1 polymorphisms and clinical variables on VKA dosing in children. A nonselected cohort of pediatric patients receiving VKA were tested for CYP2C9 and VKORC1 polymorphisms, and clinical data were collected. Multiple linear regression modeling was used to assess relationships of VKA dose with genetic and clinical variables. Fifty-nine patients were recruited; 55.9% were receiving warfarin, and 44.1% were on phenprocoumon. There was a negative association of age with VKA dose (P < .001). Comparing VKORC1 genotypes, the AA group required significantly lower daily doses than GG group (P = .011). In the full model including age, VKORC1 and CYP2C9 genotypes accounted for 38% of dose variation. Age explained 28.3% of VKA dose variations; VKORC1 and CYP2C9 explained only 3.7% and 0.4%, respectively. In children, the most critical factor in determining VKA dose is age. VKORC1/CYP2C9 genotypes only marginally explain dose variations.

Extending and evaluating a warfarin dosing algorithm that includes CYP4F2 and pooled rare variants of CYP2C9

OBJECTIVE

Warfarin dosing remains challenging because of its narrow therapeutic window and large variability in dose response. We sought to analyze new factors involved in its dosing and to evaluate eight dosing algorithms, including two developed by the International Warfarin Pharmacogenetics Consortium (IWPC).

METHODS

we enrolled 108 patients on chronic warfarin therapy and obtained complete clinical and pharmacy records; we genotyped single nucleotide polymorphisms relevant to the VKORC1, CYP2C9, and CYP4F2 genes using integrated fluidic circuits made by Fluidigm.

RESULTS

When applying the IWPC pharmacogenetic algorithm to our cohort of patients, the percentage of patients within 1 mg/d of the therapeutic warfarin dose increases from 54% to 63% using clinical factors only, or from 38% using a fixed-dose approach. CYP4F2 adds 4% to the fraction of the variability in dose (R) explained by the IWPC pharmacogenetic algorithm (P<0.05). Importantly, we show that pooling rare variants substantially increases the R for CYP2C9 (rare variants: P=0.0065, R=6%; common variants: P=0.0034, R=7%; rare and common variants: P=0.00018; R=12%), indicating that relatively rare variants not genotyped in genome-wide association studies may be important. In addition, the IWPC pharmacogenetic algorithm and the Gage (2008) algorithm perform best (IWPC: R=50%; Gage: R=49%), and all pharmacogenetic algorithms outperform the IWPC clinical equation (R=22%). VKORC1 and CYP2C9 genotypes did not affect long-term variability in dose. Finally, the Fluidigm platform, a novel warfarin genotyping method, showed 99.65% concordance between different operators and instruments.

CONCLUSION

CYP4F2 and pooled rare variants of CYP2C9 significantly improve the ability to estimate warfarin dose.

Pharmacogenetics of anticoagulants

Warfarin, acenocoumarol, and phenprocoumon are among the major anticoagulant drugs worldwide. Because of their low therapeutic index and serious adverse reactions (ADRs), their wide use, and their varying kinetics and pharmacogenetic dependence, it is of great importance to explore further possibilities to forecast the dose beyond conventional INR measurements. Here, we describe particulars of the relative pharmacogenetic influence on the kinetics of these agents, the population distribution of genetics risk groups, and novel data on clinical features with influence on dose requirement and ADR risk. The usefulness of genetic information prior to and soon after start of therapy is also discussed. The current renewed focus on these issues is caused not only because of new genetic knowledge and genotyping facilities but also because of the high rate of serious ADRs. Application of these measures in the care of patients with anticoagulant therapy is important awaiting new therapeutic principles to be introduced, which may take long time still.

Pharmacogenetic testing and therapeutic drug monitoring are complementary tools for optimal individualization of drug therapy

Genetic factors contribute to the phenotype of drug response, but the translation of pharmacogenetic outcomes into drug discovery, drug development or clinical practice has proved to be surprisingly disappointing. Despite significant progress in pharmacogenetic research, only a few drugs, such as cetuximab, dasatinib, maraviroc and trastuzumab, require a pharmacogenetic test before being prescribed. There are several gaps that limit the application of pharmacogenetics based upon the complex nature of the drug response itself. First, pharmacogenetic tests could be more clinically applicable if they included a comprehensive survey of variation in the human genome and took into account the multigenic nature of many phenotypes of drug disposition and response. Unfortunately, much of the existing research in this area has been hampered by limitations in study designs and the nonoptimal selection of gene variants. Secondly, although responses to drugs can be influenced by the environment, only fragmentary information is currently available on how the interplay between genetics and environment affects drug response. Third, the use of a pharmacogenetic test as a standard of care for drug therapy has to overcome significant scientific, economic, commercial, political and educational barriers, among others, in order for clinically useful information to be effectively communicated to practitioners and patients. Meanwhile, the lack of efficacy is in this process is quite as costly as drug toxicity, especially for very expensive drugs, and there is a widespread need for clinically and commercially robust pharmacogenetic testing to be applied. In this complex scenario, therapeutic drug monitoring of parent drugs and/or metabolites, alone or combined with available pharmacogenetic tests, may be an alternative or complementary approach when attempts are made to individualize dosing regimen, maximize drug efficacy and enhance drug safety with certain drugs and populations (e.g. antidepressants in older people).

Progress toward genetic tailoring of heart failure therapy

Heart failure (HF) is a modern epidemic and a heterogeneous disorder with many therapeutic options. While the average response to each individual treatment is favorable, significant interindividual variation exists in the response to HF therapeutics. As a result, the optimal regimen for an individual patient or subgroup of patients is elusive, with current treatment being mainly empirical. Pharmacogenetic customization of HF therapy may provide an important opportunity to improve the treatment of HF. Common genetic variations exist in genes related to most classes of HF drugs, many of which have known functional consequences for or established relationships with drug response. This review summarizes the current understanding of the pharmacogenetics of HF therapeutics, including angiotensin-converting enzyme inhibitors and beta-blockers, and focuses on recent advances and medium-term expectations for the field.

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

Well-characterized genes that affect warfarin metabolism (cytochrome P450 (CYP) 2C9) and sensitivity (vitamin K epoxide reductase complex 1 (VKORC1)) explain one-third of the variability in therapeutic dose before the international normalized ratio (INR) is measured. To determine genotypic relevance after INR becomes available, we derived clinical and pharmacogenetic refinement algorithms on the basis of INR values (on day 4 or 5 of therapy), clinical factors, and genotype. After adjusting for INR, CYP2C9 and VKORC1 genotypes remained significant predictors (P < 0.001) of warfarin dose. The clinical algorithm had an R(2) of 48% (median absolute error (MAE): 7.0 mg/week) and the pharmacogenetic algorithm had an R(2) of 63% (MAE: 5.5 mg/week) in the derivation set (N = 969). In independent validation sets, the R(2) was 26-43% with the clinical algorithm and 42-58% when genotype was added (P = 0.002). After several days of therapy, a pharmacogenetic algorithm estimates the therapeutic warfarin dose more accurately than one using clinical factors and INR response alone.

A pharmacometric model describing the relationship between warfarin dose and INR response with respect to variations in CYP2C9, VKORC1, and age

The objective of the study was to update a previous NONMEM model to describe the relationship between warfarin dose and international normalized ratio (INR) response, to decrease the dependence of the model on pharmacokinetic (PK) data, and to improve the characterization of rare genotype combinations. The effects of age and CYP2C9 genotype on S-warfarin clearance were estimated from high-quality PK data. Thereafter, a temporal dose-response (K-PD) model was developed from information on dose, INR, age, and CYP2C9 and VKORC1 genotype, with drug clearance as a covariate. Two transit compartment chains accounted for the delay between exposure and response. CYP2C9 genotype was identified as the single most important predictor of required dose, causing a difference of up to 4.2-fold in the maintenance dose. VKORC1 accounted for a difference of up to 2.1-fold in dose, and age reduced the dose requirement by ~6% per decade. This reformulated K-PD model decreases dependence on PK data and enables robust assessment of INR response and dose predictions, even in individuals with rare genotype combinations.

Validation and comparison of pharmacogenetics-based warfarin dosing algorithms for application of pharmacogenetic testing

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

The genetics of ischaemic stroke

In this review, we discuss the genetic factors in both the aetiology and treatment of ischaemic stroke. We discuss candidate gene association studies, family linkage studies and the more recent whole genome association studies and whole genome expression studies. We also briefly discuss genetic testing for stroke risk and genetic analysis of treatment complications.

Ability of VKORC1 and CYP2C9 to predict therapeutic warfarin dose during the initial weeks of therapy

BACKGROUND

CYP2C9 and VKORC1 genotypes predict therapeutic warfarin dose at initiation of therapy; however, the predictive ability of genetic information after a week or longer is unknown. Experts have hypothesized that genotype becomes irrelevant once international normalized ratio (INR) values are available because INR response reflects warfarin sensitivity.

METHODS

We genotyped the participants in the Prevention of Recurrent Venous Thromboembolism (PREVENT) trial, who had idiopathic venous thromboemboli and began low-intensity warfarin (therapeutic INR 1.5-2.0) using a standard dosing protocol. To develop pharmacogenetic models, we quantified the effect of genotypes, clinical factors, previous doses and INR on therapeutic warfarin dose in the 223 PREVENT participants who were randomized to warfarin and achieved stable therapeutic INRs.

RESULTS

A pharmacogenetic model using data from day 0 (before therapy initiation) explained 54% of the variability in therapeutic dose (R(2)). The R(2) increased to 68% at day 7, 75% at day 14, and 77% at day 21, because of increasing contributions from prior doses and INR response. Although CYP2C9 and VKORC1 genotypes were significant independent predictors of therapeutic dose at each weekly interval, the magnitude of their predictive ability diminished over time: partial R(2) of genotype was 43% at day 0, 12% at day 7, 4% at day 14, and 1% at day 21.

CONCLUSION

Over the first weeks of warfarin therapy, INR and prior dose become increasingly predictive of therapeutic dose, and genotype becomes less relevant. However, at day 7, genotype remains clinically relevant, accounting for 12% of therapeutic dose variability.

Effects of CYP4F2 genetic polymorphisms and haplotypes on clinical outcomes in patients initiated on warfarin therapy

BACKGROUND

A variant in the CYP4F2 gene, rs2108622, has been recently shown to determine stable warfarin dose requirements. CYP4F2 has also been shown recently to metabolize vitamin K.

METHODS

Three hundred and eleven patients were recruited prospectively from two UK hospitals and followed-up for 6 months. Fine mapping of the whole CYP4F2 region was performed to try and define the haplotype structure of CYP4F2. Genotyping was performed on the Sequenom platform. Univariate and multiple regression analyses were undertaken to assess the effect of CYP4F2 on predefined clinical outcomes of warfarin response.

RESULTS

Fifty-nine single nucleotide polymorphisms in the CYP4F2 gene were analyzed. There was a high degree of linkage disequilibrium in the gene with two haplotype blocks. No association was found with warfarin stable dose and rs2108622 in our prospective cohort of patients even after adjustments to reduce patient heterogeneity. Interestingly, a single nucleotide polymorphism (rs2189784), which is in strong linkage disequilibrium with rs2108622, showed an association with time-to-therapeutic international normalized ratio which remained significant after the correction for multiple testing (Pc = 0.03). No association was shown with the haplotypes after false discovery rate correction.

CONCLUSION

Although we were unable to demonstrate an association between rs2108622 and stable warfarin dose, our finding of an association between rs2189784 and time-to-therapeutic international normalized ratio is consistent with the recent finding that CYP4F2 plays a role in vitamin K metabolism. However, the effect of CYP4F2 is relatively small in all studies undertaken so far, and thus seems unlikely to be of clinical relevance.

10 years of oral anticoagulant pharmacogenomics: what difference will it make? A critical appraisal

Since the first report on warfarin pharmacogenetics in 1999, genetic variants have emerged as an important predictor of warfarin maintenance doses before therapy is initiated, raising expectations of greatly improved clinical outcomes. However, much of the information on warfarin sensitivity conveyed by genetic variants is captured by early international normalized ratio values traditionally used to guide dose titration. Thus, inclusion of early international normalized ratios in prediction models reduces the contribution of genetics. Moreover, in large population cohorts, genetics explained only 20–30% of variance in warfarin doses. Finally, even pharmacogenetic prediction models did not predict doses reliably in the majority of at-risk patients with warfarin requirements at the low or high end of the dose range. Currently, the clinical utility and cost–effectiveness of pharmacogenetic-based dosing are being assessed in large prospective trials in various settings. In the interim, enthusiasm for warfarin pharmacogenetics should not supersede strict adherence to traditional measures used to optimize coumarin anticoagulation.

Genomic and personalized medicine: foundations and applications

The last decade has witnessed a steady embrace of genomic and personalized medicine by senior government officials, industry leadership, health care providers, and the public. Genomic medicine, which is the use of information from genomes and their derivatives (RNA, proteins, and metabolites) to guide medical decision making-is a key component of personalized medicine, which is a rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. As medicine begins to embrace genomic tools that enable more precise prediction and treatment disease, which include "whole genome" interrogation of sequence variation, transcription, proteins, and metabolites, the fundamentals of genomic and personalized medicine will require the development, standardization, and integration of several important tools into health systems and clinical workflows. These tools include health risk assessment, family health history, and clinical decision support for complex risk and predictive information. Together with genomic information, these tools will enable a paradigm shift to a comprehensive approach that will identify individual risks and guide clinical management and decision making, all of which form the basis for a more informed and effective approach to patient care. DNA-based risk assessment for common complex disease, molecular signatures for cancer diagnosis and prognosis, and genome-guided therapy and dose selection are just among the few important examples for which genome information has already enabled personalized health care along the continuum from health to disease. In addition, information from individual genomes, which is a fast-moving area of technological development, is spawning a social and information revolution among consumers that will undoubtedly affect health care decision making. Although these and other scientific findings are making their way from the genome to the clinic, the full application of genomic and personalized medicine in health care will require dramatic changes in regulatory and reimbursement policies as well as legislative protections for privacy for system-wide adoption. Thus, there are challenges from both a scientific and a policy perspective to personalized health care; however, they will be confronted and solved with the certainty that the science behind genomic medicine is sound and the practice of medicine that it informs is evidence based.

Genetic and environmental factors determining clinical outcomes and cost of warfarin therapy: a prospective study

BACKGROUND

In this prospective cohort study, we have undertaken a comprehensive evaluation of clinical parameters along with variation in 29 genes (including CYP2C9 and VKORC1) to identify factors determining interindividual variability in warfarin response.

METHODS

Consecutive patients (n=311) were followed up prospectively for 26 weeks. Several outcomes chosen to capture both warfarin efficacy and toxicity were assessed. Univariate and multiple regression analyses were undertaken to assess the combined effect of clinical and genetic factors.

RESULTS

CYP2C9 was the most important gene determining initial anticoagulant control, whereas VKORC1 was more important for stable anticoagulation. Novel associations with some clinical outcomes were found with single nucleotide polymorphisms in the cytochrome 450 genes CYP2C18 and CYP2C19, which were independent of the associations observed with CYP2C9 and in genes encoding CYP3A5, protein S and clotting factor V, although the variability explained by these genes was small. On the basis of the results of microcosting, adverse events were shown to be a significant predictor of total cost.

CONCLUSION

Accurate prediction of warfarin dose requirement needs to take into account multiple genetic and environmental factors, the contributions of which vary in the induction and maintenance phases of treatment.

Interactive modeling for ongoing utility of pharmacogenetic diagnostic testing: application for warfarin therapy

BACKGROUND

The application of pharmacogenetic results requires demonstrable correlations between a test result and an indicated specific course of action. We developed a computational decision-support tool that combines patient-specific genotype and phenotype information to provide strategic dosage guidance. This tool, through estimating quantitative and temporal parameters associated with the metabolism- and concentration-dependent response to warfarin, provides the necessary patient-specific context for interpreting international normalized ratio (INR) measurements.

METHODS

We analyzed clinical information, plasma S-warfarin concentration, and CYP2C9 (cytochrome P450, family 2, subfamily C, polypeptide 9) and VKORC1 (vitamin K epoxide reductase complex, subunit 1) genotypes for 137 patients with stable INRs. Plasma S-warfarin concentrations were evaluated by VKORC1 genotype (-1639G>A). The steady-state plasma S-warfarin concentration was calculated with CYP2C9 genotype-based clearance rates and compared with actual measurements.

RESULTS

The plasma S-warfarin concentration required to yield the target INR response is significantly (P < 0.05) associated with VKORC1 -1639G>A genotype (GG, 0.68 mg/L; AG, 0.48 mg/L; AA, 0.27 mg/L). Modeling of the plasma S-warfarin concentration according to CYP2C9 genotype predicted 58% of the variation in measured S-warfarin concentration: Measured [S-warfarin] = 0.67(Estimated [S-warfarin]) + 0.16 mg/L.

CONCLUSIONS

The target interval of plasma S-warfarin concentration required to yield a therapeutic INR can be predicted from the VKORC1 genotype (pharmacodynamics), and the progressive changes in S-warfarin concentration after repeated daily dosing can be predicted from the CYP2C9 genotype (pharmacokinetics). Combining the application of multivariate equations for estimating the maintenance dose with genotype-guided pharmacokinetics/pharmacodynamics modeling provides a powerful tool for maximizing the value of CYP2C9 and VKORC1 test results for ongoing application to patient care.

Pharmacogenetics and stroke

Genetic variations have been shown to influence drug metabolism, risk of adverse drug events, and pharmacodynamic responses for many drugs routinely used to treat patients with stroke or at risk for stroke. Examples include clopidogrel, statins, antihypertensive medications, and coumadin. Further validation studies are needed to assess the clinical utility of selecting drugs and doses based on genetic tests. Physicians, pharmaceutical companies, regulatory agencies, and health insurers continue to grapple with how best to translate this burgeoning field into effective individualized medicine.

Predicting warfarin maintenance dose in patients with venous thromboembolism based on the response to a standardized warfarin initiation nomogram

BACKGROUND

Polymorphisms in the VKORC1 and CYP2C9 genes influence warfarin requirements. It has been suggested that dosing algorithms incorporating them might outperform usual care. Standardized warfarin initiation nomograms are safe and effective and patients' responses to them could be used to predict warfarin requirements without the need for genetic testing.

OBJECTIVES

To develop a model to predict warfarin dose requirements based on the response to a standard nomogram without using genetic testing.

PATIENTS/METHODS

We included 363 outpatients with acute venous thromboembolism who were started on treatment using a standardized warfarin nomogram and achieved a stable maintenance warfarin dose defined as a dose prescribed twice consecutively after two consecutive INR measurements between 2.0 and 3.0. Linear regression was used to derive equations predicting the maintenance dose and models were validated using non-parametric bootstrapping and tested in an independent cohort.

RESULTS

Three models were constructed for patients completing the nomogram until day 3 (warfarin dose (mg week(-1)) = Exp [2.737 + 1.896(INR(3)(-1))-0.008(Age)]; R2adj = 0.462), day 5 (warfarin dose (mg week(-1)) = Exp[2.261 + 2.412(INR(3)(-1)) -0.285(DeltaINR(5-3))]; R2adj = 0.603) and day 8 (warfarin dose (mg week(-1)) = Exp[1.574 + 1.788(INR(8)(-1)) + 0.024(cumulated warfarin dose until nomogram day 7)]; R2adj = 0.643), where Exp is the exponential function; INR3 and INR8 are the INR on days 3 or 8 of the nomogram, and DeltaINR(5-3) is the difference in the INR on days 5 and 3. All models were internally and externally validated and were accurate to within 25% of the actual dose in >60% of patients.

CONCLUSION

Maintenance warfarin dose can be accurately predicted using individual response to a standard warfarin initiation nomogram without the need for costly genetic testing.

VKORC1 variant genotypes influence warfarin response in patients undergoing total joint arthroplasty: a pilot study

Warfarin dosing algorithms do not account for genetic mutations that can affect anticoagulation response. We retrospectively assessed to what extent the VKORC1 variant genotype would alter the likelihood of being a hyperresponder or hyporesponder to warfarin in patients undergoing total joint arthroplasty. We used the international normalized ratio (INR) on the third postoperative day of 3.0 or greater to define warfarin hyperresponders and 1.07 or less to define hyporesponders. A control group of normal responders was identified. From a cohort of 1125 patients receiving warfarin thromboprophylaxis, we identified 30 free of predisposing factors that could affect warfarin response: 10 hyperresponders, eight hyporesponders, and 12 normal responders. Homozygous carriers of the VKORC1 mutant AA genotype were more likely (compared with carriers of GA or GG genotypes) to be hyperresponders (odds ratio, 7.5; 95% confidence interval, 1.04-54.1). Homozygous carriers of the GG (normal) genotype were more likely (compared with carriers of AA or GA genotypes) to be hyporesponders (odds ratio, 9; 95% confidence interval, 1.14-71). Preoperative screening for the VKORC-1 genotype could identify patients with a greater potential for being a hyperresponder or hyporesponder to warfarin. This may allow an adjusted pharmacogenetic-based warfarin dose to optimize anticoagulation, reducing postoperative risks of bleeding and thrombosis or embolism.

LEVEL OF EVIDENCE

Level III, diagnostic study.

Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin

BACKGROUND

Genotype-guided initial warfarin dosing may reduce over-anticoagulation and serious bleeding compared to a one-dose-fits-all dosing method.

OBJECTIVE

The objective of this review was to investigate the safety and efficacy of genotype-guided dosing of warfarin in reducing the occurrence of serious bleeding events and over-anticoagulation.

DATA SOURCES

The authors searched PubMed, EMBASE and International Pharmaceutical Abstracts through January 23, 2009, without language restrictions. Selected articles were randomized trials comparing pharmacogenetic dosing of warfarin versus a "standard" dose control algorithm in adult patients taking warfarin for the first time.

REVIEW METHODS

Two reviewers independently extracted data and assessed study quality using a validated instrument. The primary outcomes were major bleeding and time spent within the therapeutic range International Normalized Ratio (INR). Secondary outcomes included minor bleeding, thrombotic events and other measures of anticoagulation quality.

RESULTS

Three of 2,014 studies (423 patients) met the inclusion and exclusion criteria. Differences in study quality, dosing algorithms, length of follow-up and outcome measures limited meta-analysis. Summary estimates revealed no statistically significant difference in bleeding rates or time within the therapeutic range INR. The highest quality study found no significant difference in primary or secondary outcomes, although there was a trend towards more rapid achievement of a stable dose (14.1 vs. 19.6 days, p = 0.07) in the pharmocogenetic arm.

CONCLUSIONS

We did not find sufficient evidence to support the use of pharmacogenetics to guide warfarin therapy. Additional clinical trials are needed to define the optimal approach to use warfarin pharmacogenetics in clinical practice.

Should we test for CYP2C9 before initiating anticoagulant therapy in patients with atrial fibrillation?

BACKGROUND

Genetic variants of the warfarin sensitivity gene CYP2C9 have been associated with increased bleeding risk during warfarin initiation. Studies also suggest that such patients remain at risk throughout treatment.

OBJECTIVE

Would testing patients with non-valvular atrial fibrillation (AF) for CYP2C9 before initiating warfarin improve outcomes?

DESIGN

Markov state transition decision model.

SETTING

Ambulatory or inpatient settings necessitating new initiation of anticoagulation.

PATIENTS

The base case was a 69-year-old man with newly diagnosed non-valvular AF. Interventions included: (1) warfarin, (2) aspirin, or (3) no antithrombotic therapy without genetic testing; and genetic testing followed by (4) aspirin or (5) no antithrombotic therapy in those with culprit CYP2C9 alleles.

MEASURES

Quality-adjusted life years (QALYs).

RESULTS

In the base case, testing and treating patients with CYP2C9*2 and/or CYP2C9*3 with aspirin rather than warfarin was best (8.97 QALYs). However, warfarin without genetic testing was a close second (8.96 QALYs), a difference of roughly 5 days. Sensitivity analyses demonstrated that genetic testing followed by aspirin was best for patients at lower risk of embolic events. Warfarin without testing was preferred if the rate of embolic events was greater than 5% per year, or the risk of major bleeding while receiving warfarin was lower.

CONCLUSION

For patients at average risk for ischemic stroke due to AF and at average risk for major hemorrhage, treatment based on genetic testing offers no benefit compared to warfarin initiation without testing. The gain from testing may be larger in patients at lower risk of embolic events or at greater risk of bleeding.

Validation of clinical testing for warfarin sensitivity: comparison of CYP2C9-VKORC1 genotyping assays and warfarin-dosing algorithms

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 -1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses.

A regulatory science perspective on warfarin therapy: a pharmacogenetic opportunity

Warfarin is a challenging drug to accurately dose, both initially and for maintenance, because of its narrow therapeutic range, wide interpatient variability, and long list of factors that can influence dosing. Two million people in the United States are initiated on warfarin therapy annually, and this number is steadily increasing because of the increase in number of eligible patients. Recently, warfarin was reported to be the fourth leading cause of adverse events. The U.S. Food and Drug Administration recognizes that the adverse event rate of warfarin can be improved through better initial dosing, because many of the serious adverse events of warfarin occur soon after starting treatment. A substantial number of studies demonstrate that common variants of two genes, VKORC1 and CYP2C9, along with other nongenetic factors, correlate significantly with warfarin dosing. The genotypes of VKORC1 and CYP2C9 alone account for nearly 3 times more of the variability ( approximately 30%) in warfarin dosing than do age, weight, gender, and other clinical factors combined ( approximately 12%). Therefore, the purpose of this report is to review the current recommendations for warfarin therapy that involve genetic testing.

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

BACKGROUND

In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs.

DISCUSSION

Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government.

SUMMARY

A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.

Influence of CYP2C9 and VKORC1 on warfarin response during initiation of therapy

BACKGROUND

Although multiple reports have documented the influence of CYP2C9 and VKORC1 variants on warfarin dose, risk of over-anticoagulation and hemorrhage, their influence on anticoagulation maintenance and individual proportion of time spent in target INR range (PPTR) is limited. Moreover the potential benefit of genotype-guided dosing implemented after initiation of therapy in a racially diverse population has not been explored. Herein we present the influence of CYP2C9 and VKORC1 C1173T on warfarin response during the first 30 days of therapy.

METHODS

Warfarin dose was empirically determined in 250 African Americans 271 European Americans. The influence of CYP2C9 and VKORC1 on rate of INR increase, anticoagulation maintenance, risk of over-anticoagulation, and change in dose over 30 days was evaluated after adjustment for socio-demographic, lifestyle and clinical factors. Possession of variant VKORC1 (+/- variant CYP2C9) genotype was associated with a more rapid attainment of target INR and higher frequency of dose adjustments. Patients possessing variant genotypes spent less time in target range. However adjustment for rate of INR increase rendered the association non-significant. European Americans (but not African Americans) possessing variant VKORC1 (+/- variant CYP2C9) genotype had a higher risk of over-anticoagulation. Neither CYP2C9 nor VKORC1 influenced the risk of minor hemorrhage. CYP2C9 and VKORC1 explained 6.3% of the variance in dose change over the first 30 days of therapy demonstrating that the usefulness of genotype-guided dosing may extend beyond first day of therapy.

CONCLUSION

The benefit of genotype-based dose prediction may extend beyond first few days of therapy. Whether genotype-guided dosing will decrease the risk of over-anticoagulation, improve anticoagulation control and most importantly improve outcomes for chronic warfarin users remains to be proven.

Clinical pharmacy consultation for pharmacogenetic testing

The clinical application of pharmacogenetic testing will help to bring personalized medicine into clinical practice. Due to the complex process involved in delivering pharmacogenetic testing, optimal clinical implementation of pharmacogenetic tests will require the coordinated effort of multiple disciplines including medicine, clinical laboratory medicine and clinical pharmacy. This will help to bridge the gap between the basic and laboratory science, and the clinical application of these results. How may clinical pharmacy contribute to the clinical application of pharmacogenetic testing as a member of a multidisciplinary team? In this perspective, we propose a potential new role for pharmacists: as an interpreter of pharmacogenetic test results. Interpreting the results of pharmacogenetic tests, particularly, those intended to guide drug dosing, requires an understanding of pharmacogenetics, pharmacokinetics and pharmacodynamics. Pharmacists who are knowledgeable in these areas may play an important role in interpretation of the test results.

Estimation of the warfarin dose with clinical and pharmacogenetic data

BACKGROUND

Genetic variability among patients plays an important role in determining the dose of warfarin that should be used when oral anticoagulation is initiated, but practical methods of using genetic information have not been evaluated in a diverse and large population. We developed and used an algorithm for estimating the appropriate warfarin dose that is based on both clinical and genetic data from a broad population base.

METHODS

Clinical and genetic data from 4043 patients were used to create a dose algorithm that was based on clinical variables only and an algorithm in which genetic information was added to the clinical variables. In a validation cohort of 1009 subjects, we evaluated the potential clinical value of each algorithm by calculating the percentage of patients whose predicted dose of warfarin was within 20% of the actual stable therapeutic dose; we also evaluated other clinically relevant indicators.

RESULTS

In the validation cohort, the pharmacogenetic algorithm accurately identified larger proportions of patients who required 21 mg of warfarin or less per week and of those who required 49 mg or more per week to achieve the target international normalized ratio than did the clinical algorithm (49.4% vs. 33.3%, P<0.001, among patients requiring < or = 21 mg per week; and 24.8% vs. 7.2%, P<0.001, among those requiring > or = 49 mg per week).

CONCLUSIONS

The use of a pharmacogenetic algorithm for estimating the appropriate initial dose of warfarin produces recommendations that are significantly closer to the required stable therapeutic dose than those derived from a clinical algorithm or a fixed-dose approach. The greatest benefits were observed in the 46.2% of the population that required 21 mg or less of warfarin per week or 49 mg or more per week for therapeutic anticoagulation.

Pharmacogenomic dosing of warfarin: ready or not?

Warfarin is a medication with a narrow therapeutic index, nonlinear intrapatient pharmacokinetics, and high interpatient variability in its dose-response relationship. These characteristics create great difficulty in determining an appropriate dose; sub- or supratherapeutic doses can increase the risk of bleeding and venous thromboembolism complications. Algorithms based on nongenetic factors of patient age, gender, body weight, diseases, diet, smoking, and medication traditionally have been used to determine warfarin dose requirements. However, these formulas account for less than 20% of the variability in warfarin response. Following completion of the Human Genome Project, several genetic variants of CYP2C9 and VKORC1 have been identified that account for a greater proportion of the variability in patient response to warfarin than is explained by nongenetic factors. Moreover, algorithms that analyze both patient genetic and nongenetic factors, i.e., pharmacogenomics, in warfarin response account for 55% to 60% of the variability. This raises the prospect of enhancing the ability to predict warfarin dose requirements and, thereby, improving its safety, effectiveness, and therapy efficiency. This review evaluates the impact of combining genetic and nongenetic factors in accounting for the variability in warfarin response and the prospect that pharmacogenomic algorithms will improve warfarin dosing early in therapy, possibly achieving a more rapid attainment of the therapeutic dose, improving safety, and increasing effectiveness. The most comprehensive and widely available pharmacogenomic algorithms for estimating warfarin dose requirements when initiating therapy, www.WarfarinDosing.org, is reviewed.

Warfarin pharmacogenetics

Significant interest in the pharmacogenetics of warfarin therapy has been triggered with the recent package insert update that highlights the potential role of pharmacogenetics in improving the safety and effectiveness of warfarin. We review the evidence of the influence of the two key genes of interest, the cytochrome P450 2C9 gene, CYP2C9, and the vitamin K epoxide reductase complex 1 gene, VKORC1, on warfarin response and discuss the implications of current knowledge for clinical practice. The influence of CYP2C9 and VKORC1 genotypes on warfarin dose requirements has been consistently demonstrated in diverse racial and ethnic patient groups in observational studies and randomized clinical trials. Dosing algorithms have been developed that incorporate clinical, demographic, and genetic information to help select a warfarin starting dose. Furthermore, CYP2C9 variant genotypes have been associated with a significantly increased risk of serious bleeding events. However, evidence to date from prospective, controlled studies has not demonstrated an added benefit of incorporating genotype-guided therapy in improving anticoagulation control or in preventing or reducing the risk of hemorrhagic or thromboembolic complications. Research efforts designed to evaluate the effectiveness of genotype-guided therapy in improving outcomes are under way. However, the routine use of CYP2C9 and VKORC1 genotyping in the general patient population who begin warfarin therapy is not supported by evidence currently available.

Relative contribution of CYP2C9 and VKORC1 genotypes and early INR response to the prediction of warfarin sensitivity during initiation of therapy

Genetic variants in CYP2C9 and VKORC1 strongly affect steady-state warfarin dose. However, these variants also affect early international normalized ratio (INR) values during warfarin initiation. We examined whether CYP2C9/VKORC1 genotypes provide information about warfarin sensitivity additional to that provided by early INR responses. In 214 patients starting warfarin with INR-guided dose adjustments, we determined whether CYP2C9 and VKORC1 genotypes were associated with early measures of warfarin sensitivity (time to INR >/= lower limit of therapeutic range; time to INR > 4; and first stable warfarin dose) after adjusting for early (days 4-6) and week 1 (days 7-9) INR values. Early INRs were associated with all outcomes (all P < .001) and were more informative than genotypes. For time to INR more than or equal to the lower limit of therapeutic range, adding either early INRs or genotypes to a baseline model (clinical variables only) increased the goodness-of-fit (R(2)) from 0.05 to 0.42 and 0.19, respectively (full model, R(2) = 0.46). For first stable warfarin dose, adding either early INRs or genotypes to the baseline model increased the R(2) from 0.08 to 0.32 and 0.27, respectively (full model, R(2) = 0.40). After inclusion of week 1 INRs, CYP2C9 (P = .08) and VKORC1 (P = .30) were not associated with stable warfarin dose. Thus, much of the information provided by CYP2C9 and VKORC1 genotypes during warfarin initiation is captured by the early INR response.

Pharmacogenetic predictors of statin-mediated low-density lipoprotein cholesterol reduction and dose response

BACKGROUND

There is interindividual variation in low-density lipoprotein cholesterol (LDLc) lowering by statins and limited study into the genetic associations of the dose dependant LDLc lowering by statins.

METHODS AND RESULTS

Five hundred nine patients with hyperlipidemia were randomly assigned atorvastatin 10 mg, simvastatin 20 mg, or pravastatin 10 mg (low-dose phase) followed by 80 mg, 80 mg, and 40 mg (high-dose phase), respectively. Thirty-one genes in statin, cholesterol, and lipoprotein metabolism were sequenced and 489 single nucleotide polymorphisms with minor allele frequencies >2% were tested for associations with percentage LDLc lowering at low doses using multivariable adjusted general linear regression. Significant associations from the analysis at low dose were then repeated at high-dose statins. At low doses, only 1 single nucleotide polymorphism met our experiment-wide significance level, ABCA1 rs12003906. Twenty-six subjects carried the minor allele of rs12003906, which was associated with an attenuated LDLc reduction (LDLc reduction in carriers versus noncarriers -24.1+/-2.6% versus -32.2+/-1.5%; P=0.0001). In addition, we replicated the association with the APOE epsilon3 allele and a reduced LDLc reduction. At high doses, carriers of the minor allele of ABCA1 rs12003906 and the APOE epsilon3 allele improved their LDLc reduction but continued to have a diminished LDLc reduction compared with noncarriers (-30.5+/-4.0% versus -42.0+/-2.4%; P=0.005) and (-38.5+/-1.9% versus -45.3+/-2.8%; P=0.009), respectively.

CONCLUSIONS

An intronic single nucleotide polymorphism in ABCA1 and the APOE epsilon3 allele are associated with reduced LDLc lowering by statins and identify individuals who may be resistant to maximal LDLc lowering by statins.

Influence of CYP2C9 genotype on warfarin dose requirements--a systematic review and meta-analysis

PURPOSE

To quantify the influence of common cytochrome P450 2C9 (CYP2C9) polymorphisms on warfarin dose requirements.

METHODS

A systematic review and a meta-analysis, calculating the warfarin dose reduction associated with the five most common variant CYP2C9 genotypes.

RESULTS

Thirty-nine studies (7,907 patients) were included in the meta-analysis. Compared to the CYP2C9*1/*1 genotype, the CYP2C9*1/*2, CYP2C9*1/*3, CYP2C9*2/*2, CYP2C9*2/*3, and CYP2C9*3/*3 required warfarin doses that were 19.6 (95% confidence interval 17.4, 21.9), 33.7 (29.4, 38.1), 36.0 (29.9, 42.0), 56.7 (49.1, 64.3), and 78.1% (72.0, 84.3) lower, respectively. The impact of CYP2C9 genotype tended to be larger in patients without interacting drugs.

CONCLUSIONS

Previous studies have rarely been powered to determine the quantitative influence of specific CYP2C9 genotypes on warfarin dose requirements. The results from our pooled analysis are likely to be the most accurate to date and the methodology could serve as a model for future pharmacogenetic meta-analyses.