BlueCross and BlueShield of Montana Medical Policy/Codes
Genetic Testing for Warfarin Dose
Chapter: Genetic Testing
Current Effective Date: October 25, 2013
Original Effective Date: December 21, 2010
Publish Date: October 25, 2013
Revised Dates: March 26, 2012; September 24, 2013

Warfarin is administered for preventing and treating thromboembolic events in high-risk individuals; warfarin dosing is a challenging process, due to the narrow therapeutic window, variable response to dosing, and serious bleeding events in 5% or more of patients (depending on definition). Patients are typically given a starting dose of 2–5 mg and monitored frequently with dose adjustments until a stable International Normalized Ratio (INR) value (a standardized indicator of clotting time) between 2 and 3 is achieved. During this adjustment period, a patient is at high risk for bleeding.

Stable or maintenance warfarin dose varies among individuals by more than an order of magnitude. Factors influencing stable dose include body mass index (BMI), age, interacting drugs, and indication for therapy. In addition, genetic variants of cytochrome p450 2C9 (CYP2C9) and vitamin K epoxide reductase subunit C1 (VKORC1) genes together account for a substantial proportion of inter-individual variability. More recently, a single nucleotide polymorphism (SNP; change in a single base-pair in a DNA sequence) in the CYP4F2 gene has been reported to account for a small proportion of the variability in stable dose.

Using the results of CYP2C9 and VKORC1 genetic testing to predict a warfarin starting dose that approximates the individual patient’s likely maintenance dose may benefit patients by decreasing the risk of serious bleeding events and the time to stable INR. Algorithms have also been developed that incorporate not only genetic variation but also other significant patient characteristics and clinical factors to predict the best starting dose.

Regulatory Status

Several tests to help assess warfarin sensitivity by determining presence or absence of the relevant CYP2C9, VKORC1, and CYP4F2 variants have been cleared by the U.S. Food and Drug Administration (FDA) for marketing (see Rationale). Similar tests may also be available as laboratory-developed tests in laboratories licensed under Clinical Laboratory Improvement Amendments (CLIA) for high-complexity testing. The tests are not all the same in terms of the specific variants and number of variants detected. In general, such tests are not intended to be stand-alone tools to determine optimum drug dosage but should be used along with clinical evaluation and other tools, including the INR, to predict the initial dose that best approximates the maintenance dose for patients.


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Genotyping to determine cytochrome p450 2C9 (CYP2C9) and vitamin K epoxide reductase subunit C1 (VKORC1) genetic polymorphisms is considered experimental, investigational and unproven for the purpose of managing the administration and dosing of warfarin, including use in guiding the initial warfarin dose to decrease time to stable International Normalized Ratio (INR) and reduce the risk of serious bleeding.


Test Validation

Validation of genotyping to improve pharmacologic treatment outcomes is a multistep process. In general, important steps in the validation process address the following:

  • Analytic validity: measures technical performance, i.e., whether the test accurately and reproducibly detects the gene markers of interest.
  • Clinical validity: measures the strength of the associations between the selected genetic markers and dose, therapeutic efficacy, and/or adverse events.
  • Clinical utility: determines whether the use of genotyping for specific genetic markers to guide prescribing and/or dosing improves patient outcomes such as therapeutic effect, time to effective dose, and/or adverse event rate compared to standard treatment without genotyping.

Literature Review

Warfarin is metabolized by the cytochrome p450 enzyme CYP2C9; genetic variants of CYP2C9 result in enzymes with decreased activity, increased serum warfarin concentration at standard doses, and a higher risk of serious bleeding. Information on cytochrome p450 pharmacogenetics is summarized in a 2004 Blue Cross Blue Shield Association (BCBSA) Technology Evaluation Center (TEC) Assessment (1); application to warfarin dosing and important nongenetic influences are discussed in several publications. (2-5) VKORC1 genetic variants alter the degree of warfarin effect on its molecular target and are associated with differences in maintenance doses. (6-10) CYP2C9 and VKORC1 genetic variation accounts for approximately 55% of the variability in warfarin maintenance dose. (10, 11) A genome-wide association study identified a single SNP (single nucleotide polymorphisms), found in the gene CYP4F2, that is also associated with warfarin dose (12); this association was confirmed in a separate, candidate gene study. (13) Recent studies predict that the CYP4F2 polymorphism explains 2–7% of the variability in warfarin dose in models including other genetic and nongenetic factors. (13, 14) Other factors influencing dose include body mass index (BMI), age, interacting drugs, and indication for therapy.

Genetic testing for CYP2C9 and VKORC1 is available at a number of laboratories that have developed in-house tests; these do not require FDA clearance, and information on analytic validity may not be generally available. Some laboratory-developed assays use commercially available reagents that are individually cleared by the FDA as analyte-specific reagents. Test kits cleared for marketing by the FDA include eSensor Warfarin Sensitivity Test (GenMark); Rapid Genotyping Assay (ParagonDx); Verigene Warfarin Metabolism Nucleic Acid Test (Nanosphere); INFINITI 2C9-VKORC1 Multiplex Assay for Warfarin (AutoGenomics); and eQ-PCR LightCycler Warfarin Genotyping Kit (TrimGen) (Table 1). Kit inserts for FDA-cleared test kits summarize the extensive analytic validity data required for FDA clearance. Two studies compared kits with FDA clearance and laboratory-developed assays using commercially available reagents and assay platforms; in each, the authors concluded that the assays provided accurate and rapid genotype information for the most common polymorphisms evaluated. (15, 16) However, a recent review noted that due to lack of standardization, tests may detect as few as 2 CYP2C9 variants or as many as 6.(16) For VKORC1, several known polymorphisms are in strong linkage disequilibrium with one another, thus haplotypes (a combination of polymorphisms at nearby locations) formed from various combinations can be used to assess status. Whether specific haplotypes can improve predictive value is not known. (17)

Turnaround times for these assays range from approximately 1.5 to 8 hours, not including sample transportation, processing, and delays due to assay scheduling. It is not known how soon test results might be needed during the warfarin initiation phase should outcomes studies indicate net benefit of testing.

Table 1. Warfarin Tests Cleared by the U.S. FDA (18)

Name of Test

Alleles Tested

Estimated Time to Completion (hours)

Verigene Warfarin Metabolism Nucleic Acid Test (Nanosphere, Inc., Northbrook, Il) 

CYPC9*2 and *3, VKORC1 1173C/T 


Infiniti 2C9-VKORC1 Multiplex Assay for Warfarin (AutoGenomics, Inc., Vista, CA)A

CYP2C9*2 and *3, VKORC1 -1639G/A 


eSensor Warfarin Sensitivity (GenMark Dx, Carlsbad, CA)B

CYPC9*2 and *3, VKORC1-1639G/A 


eQ-PRC LC Warfarin Genotyping Kit (Trimgen Corp., Sparks, MD) 

CYP2C9*2 and *3, VKORC1-1639G/A 


A The expanded Infiniti CYP450 2C9 Assay offers testing for CYP2C9*2, *3, *4, *5, *6 and *11, VKORC1 – 1639G.A and six additional VKORC variants.

B eSensor Warfarin Plus Test offers testing for CYP2C9*2, *3, *5, *6, *11, *14, *15, and *16, VKORC1 -1639G>A, and CYP4F2

A systematic review, (19) commissioned by the American College of Medical Genetics, evaluated CYP2C9 and VKORC1 genetic testing prior to warfarin dosing and concluded the following:

  • Clinical validity: CYP2C9 and VKORC1 genotypes contribute significant and independent information to the stable warfarin dose and, compared to the most common combination, some individuals with other genotype combinations will need more than the usual dose, while others will require less.
  • Clinical utility: The purpose of genetic testing in this clinical scenario is to predict an individual’s likely stable warfarin dose by incorporating demographic, clinical, and genotype data (CYP2C9 and VKORC1), and initiate warfarin at that predicted dose as a way to limit high International Normalized Ratio (INR) values (over-anticoagulation) that are associated with an increased risk of serious bleeding events. No large study had at the time shown this to be acceptable or effective. Based on limited clinical data, the number needed to treat to avoid one serious bleeding event was estimated to range from 48 to 385.

Authors of several additional studies of clinical validity, mainly of Caucasian patient cohorts already at maintenance dose and evaluated retrospectively, have developed algorithms that incorporate VKORC1 and CYP2C9 genetic variant information, as well as patient characteristics and other clinical information, and have evaluated the extent to which these algorithms predict various outcomes such as maintenance dose, time to stable INR, time spent in target INR range, and serious bleeding events. These algorithms vary in the non-genetic variables included, and in general, account for up to approximately 60% of warfarin maintenance dose variance. (20-27) CYP4F2 genotyping was also added to a retrospective evaluation of several algorithms that already included CYP2C9 and VKORC1; CYP4F2 polymorphisms, however, added only 4% to the fraction of the variability in stable dose explained by the best performing algorithms. (28) A systematic review and meta-analysis by Liang et al. suggested a more substantial contribution of CYP4F2 genetic variants. Compared with wild type patients, carriers of CYP4F2 variants required warfarin doses 11% and 21% higher for heterozygous and homozygous patients, respectively. (29) Some cohort studies have evaluated the more relevant initiation phase of warfarin treatment, reporting the significance of genetic factors on time to therapeutic INR, time to first supratherapeutic (over-coagulation) INR, time above therapeutic range, etc. (30-32) Limdi et al. estimated that CYP2C9 and VKORC1 explained 6.3% of the variance in dose change over the first 30 days of therapy.(33) Pautas et al. reported that in elderly patients with multiple comorbidities and polypharmacy who were starting warfarin, individuals with multiple variant alleles were at highest risk for over-anticoagulation, at an odds ratio of 12.8. (34) Ferder et al. (35) reported the predictive ability of CYP2C9 and VKORC1 genetic variants from PREVENT (Prevention of Recurrent Venous Thromboembolism) Trial subjects to gradually diminish over time from warfarin initiation starting with 43% at day 0, 12% at day 7, 4% at day 14, and 1% at day 21. Moreau et al. (36) studied 187 elderly patients starting warfarin using a “geriatric dosing-algorithm.” Adding CYP2C9 and VKORC1 genotype variants to the initial dosing model increased the explained variance in the maintenance dose from less than 10% to 31%. By day 3, VKORC1 was no longer a significant predictor of maintenance dose; however, CYP2C9 genotype remained a significant predictor. By Day 6, neither CYP2C9 nor VKORC1 genotype variants were predictive of maintenance dose. These studies indicate that if genotyping results are clinically useful, it is likely only within the first week or less of beginning warfarin therapy.

Cohort studies that evaluated algorithm-guided dosing in patients beginning warfarin treatment report that algorithms explained up to 69–79% of the variance in maintenance dose. (37, 38) The International Warfarin Pharmacogenetics Consortium compared an algorithm based only on clinical variables with one that also included genetic factors in a validation cohort of 1,009 subjects treated with warfarin. The pharmacogenetic algorithm was significantly more accurate at predicting an initial dose that was close to the maintenance dose in the 46% of patients who required low (<21 mg/week) or high (>49 mg/week) warfarin doses. (39) The analysis did not address whether a more precise initial dose of warfarin results in improved clinical endpoints. Avery et al. found 41.8% of the variability in maintenance dose days 4-7 was explained by the algorithm and that 40.3% of maintenance dose variability was explained on days 8-15. (40)

Gong et al. (41) conducted a prospective cohort study of patients requiring warfarin therapy for atrial fibrillation or venous thromboembolism using a novel pharmacogenetic warfarin initiation protocol. Practical daily loading doses were prescribed for 2 days and were dependent on VKORC1 and CYP2C9 genotypes and, as it was found necessary, on weight. The maintenance dose was determined by combining key patient clinical parameters known to influence warfarin dose requirement along with genotypes in a regression model. Once VKORC1 and CYP2C9 genotypes were incorporated into warfarin initial dose determinations, they had no additional significant effect on time required to reach the first INR within therapeutic range, on risk of overcoagulation (INR≥4), or on time to stable anticoagulation.

A study by Horne and colleagues assessed if pharmacogenetic algorithms can contribute to dose refinements after INR response to warfarin is known. (42) A population (n=1,684) drawn from 3 continents and 16 study sites was utilized to derive an algorithm explaining warfarin dose including a novel treatment response index comprised of prior warfarin dose and INR measurements. The pharmacogenetic warfarin dose-refinement algorithm explained more variability in dosing (R2=71.8%) compared to the clinical algorithm (R2=64.8%). In addition to these patients, a prospective external validation cohort (n=43) was recruited to determine the safety and accuracy of the clinical algorithm. The pooled pharmacogenetic algorithm explained 58% to 79% of the variation in therapeutic dose, and the time in therapeutic range during days 11-30 was 62%. The new pooled clinical algorithm was significantly more accurate than previously validated algorithms.

A prospective, single-arm study (n=344) by Perlstein et al. assessed the validity of 3 warfarin dosing algorithms to predict time in therapeutic range and time to first therapeutic INR in a predominantly Caucasian population. (43) The dosing algorithms were developed sequentially to select both an initial warfarin dose and a titration scheme intended to maximize the likelihood of achieving and maintaining the target INR. Algorithm A determined the initial dosing with a decision tree including both clinical and genetic factors based on best practices in the hospital’s anticoagulation management service and the published literature. Algorithm B was generated from an analysis of warfarin dose, INR, genetic factors, demographic factors, and concomitant drug therapy from a group of 74 patients treated with Algorithm A. Algorithm C was an update to Algorithm B, with the chief difference being a revision of the half maximal inhibitory concentration for VKORC1 haplotypes. The authors found a significant (p=0.04) progressive improvement in mean percentage time in therapeutic range over the entire study period for Algorithm A (58.9), Algorithm B (59.7), and Algorithm C (65.8). The secondary endpoint of per-patient percentage of INRs outside of the therapeutic range had a similar statistically significant trend across algorithms (p=0.004) with Algorithm A reporting 21.6%, algorithm B 22.8%, and algorithm C 16.8%. Time to stable therapeutic anticoagulation decreased significantly across algorithms (p<0.001), but time to first therapeutic INR did not vary significantly among the 3 algorithm sub-groups. No differences in rates of adverse events were observed during this study.

Several studies have compared the ability of different algorithms to accurately predict stable warfarin dose. (16, 44-47) In general, there does not appear to be consensus for a single algorithm at this time. Rather, it may be necessary to select the algorithm best suited to the treatment population due to differences. (46)

Several studies have included ethnically diverse populations but it is not clear whether one or several algorithms are needed to address ethnicity. The algorithm developed by Gage et al. (22) explained 55% of the variance in a Caucasian validation cohort but only 40% of the variation in a small African-American cohort. Schelleman et al. (21) developed separate predictive algorithms for Caucasian and African-American populations, which explained 42% of the variance in Caucasians but only 28% in African-Americans. Wu et al. (23) included several different ethnicities in developing their predictive algorithm, which included an ethnicity variable, and overall explained 59% of warfarin dose variation. Limdi et al. reported that the contribution of VKORC1 toward dose requirements is higher in whites than in nonwhites but that genotype predicts similar dose requirements across Caucasian, African-American, and Asian populations; genotyping for additional VKORC1 variants does not improve dose prediction in any population. (48)

Cavallari et al. tested the performance of published warfarin dosing algorithms derived from non-Hispanic cohorts in the Hispanic population. The combination of the VKORC1 and CYP2C9 genotypes and clinical factors explained 56% of patient variability in warfarin dose. The predicted dosage was within 1.0 mg/day of the therapeutic dose for 40-50% of the patients. (49) Gan et al. studied Asian populations and found that Indians, compared to Chinese and Malay patients, required a dose of 4.9 versus 3.5 and 3.3mg/day, respectively. The higher warfarin doses correlated with particular VKORC1 genotypes more often found in the Indian population. (50)

Perera et al. identified novel genetic markers in VKORC1 and CYP2C9 associated with higher warfarin dosing in African-Americans. A regression model, encompassing both genetic and clinical variables, explained 40% of the variability in warfarin maintenance dose. (51) Ramirez et al. developed a predictive algorithm for calculating dose variation in African-Americans including variants in CYP2C9*6 and CALU. (52) The authors validated an expanded pharmacogenomic dosing algorithm and compared it to the previously established International Warfarin Pharmacogenomics Consortium (IWPC) algorithm with the algorithms explaining 41% and 29% of variation, respectively. Additional studies have identified new genetic variants and/or evaluated clinical-genetic algorithms for warfarin dose in Thai, (53) Egyptian, (54) Chinese, (55) and Japanese populations. (56) In general, genetic factors helped models explain 30-54% of the overall variance but were not always significant.

A retrospective cohort of Puerto Rican patients (n=97) were recruited to determine the influence of CYP2C9 and VKORC1 polymorphisms on warfarin dose for this population. (57) Blood samples were collected during routine INR testing and underwent HILOmet PhyzioType assay to detect 5 SNPs in CYP2C9 and 7 SNPs in VKORC1.(57) Median actual effective warfarin doses were compared between CYP2C9 and VKORC1 carrier status as (wild type/non-carriers, single, double, triple and quadruple carriers). Significant differences (p<0.001) in warfarin dose were observed between wild type (5.71 mg/day), single carrier (4.64 mg/day), double carrier (3.43 mg/day), triple carriers (2.36 mg/day) and quadruple carriers (1.86 mg/day). No significant difference in time to target INR was identified between groups (p=0.34). Predicted daily warfarin dose was assessed by comparing IWPC pharmacogenomic-guided algorithm, clinical algorithm, and fixed-dose approach. In the low-dose subgroup, the pharmacogenetic algorithm provided dose estimates that were more accurate, and closer to the actual doses required, than the estimates derived from fixed-dose or clinical algorithm (p<0.001 for both comparisons). No differences were detected among the intermediate-dose patients between algorithms, and in the high-dose subgroup, a marginal difference between pharmacogenetic algorithm and clinical algorithm was found (p<0.042). This study is the first time that the association between SNPs in CYP2C9 and VKORC1 genes and effective warfarin dose has been described in Puerto Rican patients.

Not all algorithms include the use of drugs that interact with warfarin; in fact, some studies have excluded these populations. Hatch et al. (24) applied an algorithm developed in patients not taking interacting drugs and showed that when applied to a small number of patients taking interacting drugs, 10% less of dose variance was explained by the algorithm.

Thus, no single dosing algorithm has yet been agreed on that is readily generalizable to a diverse population and that has been prospectively tested in a large, representative validation cohort.

Few large, well-designed randomized clinical trials have been completed and published that address clinical utility i.e., evaluate the net benefit of using genetic factors or algorithms that include genetic factors to guide initial dosing compared to empirical initial dosing. Such trials should also address the degree to which INR must continue to be monitored to ensure that physicians do not overly rely on dosing algorithms and monitor too infrequently, potentially resulting in adverse events.

Anderson et al. (58) conducted a small, randomized controlled trial comparing algorithm (including genetic variables)-guided initial warfarin dosing (n=101) to empirical dosing (n=99). The primary outcome measure was “per-patient percentage of out-of-range INRs.” Algorithm-predicted doses more accurately approximated maintenance doses, resulting in significantly fewer dose changes, but the primary endpoint was not achieved (p=0.47); nor was the secondary outcome of serious adverse events different between study arms (p=0.71). Study patients were carefully managed by a dedicated anticoagulation service, and patients treated with empirical dosing had better than expected outcomes. The authors speculate that “Empirical therapy might be less successful in less closely managed and outpatient-based initiation programs” and that a larger trial would be needed to demonstrate utility. McMillin et al. conducted a small study (n=229) in which a gene-based dosing algorithm was compared with standard dosing in patients receiving warfarin after joint replacement surgery. (59) The primary endpoint of reduction in the incidence of adverse events was not reached; nor were secondary endpoints related to INR. Patients in this study were also managed by a dedicated and experienced anticoagulation services team. The results of these studies suggest that larger, community-based studies are needed to determine clinical utility.

Burmester et al. (60) in association with the Agency for Healthcare Research and Quality (AHRQ) and Third Wave Technologies conducted a prospective, randomized, blinded, 2-arm trial to determine whether initial warfarin dosing based on an algorithm using relevant genetic polymorphisms and clinical parameters (genetic and clinical arm) was superior to an algorithm using only usual clinical parameters (clinical-only arm) in predicting stable therapeutic dose of warfarin and in anticoagulation outcomes. A total of 230 primarily hospitalized patients were enrolled. The model including genotype predicted therapeutic dose better than the clinical-only model (p=0.0001); both models predicted dose better than the standard starting dose of 5 mg/day. However, the median percent time in INR range was the same at 28.6% in each arm. Observed times to stable therapeutic dose were also very similar in the 2 arms. During the trial, INR exceeded 4.0 in 35% of subjects in the clinical-only arm and in 38% of subjects in the genetic clinical arm. Thus, clinical outcomes were similar despite improved prediction with genetic information. Patients in this trial may have had frequent INR measurements and dose adjustments in a hospital setting; results may not reflect those likely to be obtained in an out-patient community setting.

Epstein et al., in association with Medco, a pharmacy benefits management organization, conducted a comparative cohort study in which patients initiating warfarin therapy were invited to participate with free genotyping. (61) Their hospitalization rates (the primary outcome) during the next 6 months were compared with those of a historical control group of similar patients who had initiated warfarin therapy the previous year. The authors reported that the genotyped cohort had 31% fewer hospitalizations overall compared to controls (adjusted hazard ratio [HR]: 0.69, 95% confidence interval [CI]: 0.58 to 0.82, p=0.001) and 28% fewer hospitalizations for bleeding or thromboembolism (HR: 0.72, 95% CI: 0.53 to 0.97, p=0.029). However, the number of patients who were offered enrollment but declined was omitted from the publication, making it impossible to exclude the possibility that the results of the study are heavily influenced by selection bias. A high patient refusal rate could produce a highly selected population, not comparable to unselected historical controls. Additionally, hospitalizations related to bleeding or thromboembolism were reduced by 2.16% in absolute terms, while all-cause hospitalizations had a much larger reduction of 7.07%. The latter is more than triple that expected if only due to reductions in hospitalizations from bleeding or thromboembolism by improved warfarin dosing. In the absence of selection bias, changes in warfarin dosing would not be expected to impact hospitalizations for non-hematologic reasons. The question of selection bias could have been avoided in this study if test results had been sent randomly to only half of the physicians caring for patients tested.

A blinded, randomized clinical trial (CoumaGen-II) by Anderson et al. investigated if 2 pharmacogenetic-guided (PG) testing algorithms were better than standard empiric warfarin dosing.(62) A parallel control group (n=1,866) included patients initiating warfarin treatment during the study period, and for these patients, warfarin dose was determined by physician/health-care provider. Same day genotyping of CYP2C9 and VKORC1 was provided to 504 patients randomized to 257 in the 1-step arm (IWPC algorithm) and 247 in the 3-step arm (modified IWPC algorithm). The vast majority of patients (91.4% in the control group and 95.4% in the PG group) were of Caucasian ancestry. Primary endpoints were the percentage out-of-range of INRs and time in therapeutic range during the first month and through the third month of warfarin therapy. Both PG approaches were observed to be equivalent at 1 and 3 months for all outcomes with a stable maintenance dose determined in 444 patients. There was an inverse relation between the number of reduced function alleles and the ability to predict a stable maintenance dose (p<0.001). Pharmacogenomic guidance was more accurate in wild-type patients and those with multiple variants (p<0.001). Both PG arms were pooled and were observed to be superior to the standard dosing approach with significant (p<0.001) reductions in percent of time out of INR range and percentage of time in therapeutic range at 1 and 3 months after controlling for relevant variables. Adverse events (hemorrhagic events, thromboembolic events, or other serious adverse events) were greater in the control group (4.5%) compared to the PG group (9.4%), with an adjusted relative risk of .44 (95% CI: 0.28-0.70, p<0.001).

Several large clinical trials, including some randomized, comparative clinical trials, designed to address clinical utility, are currently in progress (63) and are summarized below:

  • Warfarin Adverse Event Reduction For Adults Receiving Genetic Testing at Therapy INITIATION (WARFARIN) Trial conducted by Iverson Genetic Diagnostics, Inc. (NCT01305148). The trial will determine if the use of genetic information can predict warfarin dosing that will result in fewer hospitalizations and deaths related to warfarin. Setting: 16 hospitals/research centers in 7 states. Targeted enrollment: 4,300 participants. Currently recruiting. Additional information online at:
  • Clarification of Optimal Anticoagulation Through Genetics (COAG) Trial conducted by the National Heart, Lung, and Blood Institute in collaboration with Bristol-Myers Squibb (NCT00839657). The trial will compare genotype-guided and clinical-guided dosing algorithms for warfarin dose. Setting: 12 hospital/university medical centers in 12 states. Targeted enrollment: 1,238 participants. Currently recruiting. The trial design was published by French, et al. (64)
  • European Pharmacogenetics of AntiCoagulant Therapy – Warfarin (EU-PACT) Trial conducted by the Utrecht Institute for Pharmaceutical Sciences (NCT01119300). The trial will determine whether a dosing algorithm containing genetic information increases the time within therapeutic INR range during anticoagulant therapy with warfarin (and other anticoagulant drugs) compared to a dosing regimen not using genetic information. Setting: university medical centers and hospitals. Target enrollment: 970 participants. Not yet recruiting. The trial design was published by van Schie, et al. (65)
  • Clinical and Economic Implications of Genetic Testing for Warfarin Management trial conducted by the University of Chicago, in collaboration with AHRQ (NCT00964353). The trial will determine clinical outcomes and costs associated with the use of genotype-guided warfarin dose algorithms compared to current standards of care. Setting: University medical center. Targeted enrollment: 268 participants. Currently recruiting.
  • Genotype-Guided Warfarin Therapy Trial (WARFPGX) conducted by the University of North Carolina in collaboration with UNC Institute for Pharmacogenomics and Individualized Therapy (NCT00904293). The trial will determine the clinical utility of a warfarin-dosing algorithm that incorporates genetic information for adult patients initiating warfarin therapy. Setting: 2 anticoagulation clinics at UNC Hospitals. Targeted enrollment: 198 participants. Currently active, not recruiting.
  • Genetics Informatics Trial (GIFT) of Warfarin to Prevent DVT Trial conducted by the Washington University School of Medicine, in collaboration with Intermountain Health Care, University of Utah, Hospital for Special Surgery, New York, and National Heart, Lung, and Blood Institute (NCT01006733). The trial will develop strategies to improve the safety and effectiveness of clot prevention by customizing anticoagulants to individual genetic and clinical profiles. Setting: 4 hospital/university medical centers. Targeted enrollment: 1,600 participants. Currently recruiting. The trial design was published by Lenzini, et al. (26)
  • Pharmacogenetics of Warfarin in Puerto Rican Patients Using a Physiogenomics Approach Trial conducted by the University of Puerto Rico, in collaboration with National Heart, Lung, and Blood Institute, Hartford Hospital, and VA Caribbean Healthcare System (NCT01318057). The trial will determine the variants of CYP2C9 and VKORC1 alleles associated with warfarin treatment clinical responses in order to develop a better method of dose estimation in Puerto Ricans. Setting: hospital. Targeted enrollment: 350 participants. Currently recruiting.


While the evidence supports a strong association between genetic variants and stable warfarin dose, and to a lesser extent, between genetic variants and INR and bleeding outcomes, the evidence is not sufficient to conclude that testing for CYP2C9 and VKORC1 (and possibly CYP4F2) genetic variants improves health outcomes. Genetic testing may help predict the initial warfarin dose within the first week of warfarin treatment, but the evidence does not support the conclusion that clinically relevant outcomes, such as rates of bleeding or thromboembolism, are improved.

U.S. Food and Drug Administration (FDA) Label Updates

On August 16, 2007, the FDA approved updated labeling for Coumadin®, to include information on genetic testing for gene variants that may help “personalize” the starting dose for each patient and reduce the number of serious bleeding events. The label was updated again on January 22, 2010. With each update, manufacturers of warfarin (generic for Coumadin®) were directed to add similar information to their products’ labels. The 2010 update added information on personalizing initial dose according to genotyping results for CYP2C9 and VKORC1, providing a table of genotypes and suggested initial dose ranges for each. However, suggested starting doses are also provided for when genotyping information is not available, indicating that genetic testing is not required. Furthermore, the FDA did not include information on genetic variation in the label’s black box warning.

Practice Guidelines and Position Statements

The 2008 American College of Medical Genetics (ACMG) policy statement concluded: "There is insufficient evidence, at this time, to recommend for or against routine CYP2C9 and VKORC1 testing in warfarin-naive patients." (66)

The 8th edition of the “American College of Chest Physicians Evidence-Based Clinical Practice Guidelines on Antithrombotic and Thrombolytic Therapy,” published in 2008 and reviewed in 2009, states, “At the present time, for patients beginning [vitamin K antagonist] therapy, without evidence from randomized trials, we suggest against the use of pharmacogenetic-based initial dosing to individualize warfarin dosing (Grade 2C).” (67)

The 3rd European Science Foundation–University of Barcelona (ESF–UB) Conference in Biomedicine on Pharmacogenetics and Pharmacogenomics published a summary on CYP2C9 and VKORCI genotyping for warfarin dosing. The report noted the FDA’s addition of genetic information to the warfarin label but stated that the European Medicines Agency (EMA) has not yet decided whether to include this information in European drug labels.” (68)


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ICD-9 Codes

427.31, 427.32, V12.51, V12.52

ICD-10 Codes

I48.0, I48.1, Z86.71, Z86.72

Procedural Codes: 81227, 81335, G9143
  1. Blue Cross and Blue Shield Association Technology Evaluation Center (TEC). Special Report: Genotyping for Cytochrome P450 Polymorphisms to Determine Drug-metabolizer Status: TEC Assessments 2004; Volume 19, Tab 9.
  2. Wadelius M, Sorlin K, Wallerman O et al. Warfarin sensitivity related to CYP2C9, CYP3A5, ABCB1 (MDR1) and other factors. Pharmacogenomics J 2004; 4(1):40-8.
  3. Gage BF, Eby C, Milligan PE et al. Use of pharmacogenetics and clinical factors to predict the maintenance dose of warfarin. Thromb Haemost 2004; 91(1):87-94.
  4. Hillman MA, Wilke RA, Caldwell MD et al. Relative impact of covariates in prescribing warfarin according to CYP2C9 genotype. Pharmacogenetics 2004; 14(8):539-47.
  5. Jonas DE, McLeod HL. Genetic and clinical factors relating to warfarin dosing. Trends Pharmacol Sci 2009; 30(7):375-86.
  6. Rieder MJ, Reiner AP, Gage BF et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N Engl J Med 2005; 352(22):2285-93.
  7. Yuan HY, Chen JJ, Lee MT et al. A novel functional VKORC1 promoter polymorphism is associated with inter-individual and inter-ethnic differences in warfarin sensitivity. Hum Mol Genet 2005; 14(13):1745-51.
  8. Geisen C, Watzka M, Sittinger K et al. VKORC1 haplotypes and their impact on the inter-individual and inter-ethnical variability of oral anticoagulation. Thromb Haemost 2005; 94(4):773-9.
  9. D'Andrea G, D'Ambrosio RL, Di Perna P et al. A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood 2005; 105(2):645-9.
  10. Wadelius M, Chen LY, Downes K et al. Common VKORC1 and GGCX polymorphisms associated with warfarin dose. Pharmacogenomics J 2005; 5(4):262-70.
  11. Sconce EA, Khan TI, Wynne HA et al. The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood 2005; 106(7):2329-33.
  12. Takeuchi F, McGinnis R, Bourgeois S et al. A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. PLoS Genet 2009; 5(3):e1000433.
  13. Caldwell MD, Awad T, Johnson JA et al. CYP4F2 genetic variant alters required warfarin dose. Blood 2008; 111(8):4106-12.
  14. Borgiani P, Ciccacci C, Forte V et al. CYP4F2 genetic variant (rs2108622) significantly contributes to warfarin dosing variability in the Italian population. Pharmacogenomics 2009; 10(2):261-6.
  15. King CR, Porche-Sorbet RM, Gage BF et al. Performance of commercial platforms for rapid genotyping of polymorphisms affecting warfarin dose. Am J Clin Pathol 2008; 129(6):876-83.
  16. Langley MR, Booker JK, Evans JP et al. Validation of clinical testing for warfarin sensitivity: comparison of CYP2C9-VKORC1 genotyping assays and warfarin-dosing algorithms. J Mol Diagn 2009; 11(3):216-25.
  17. Rosove MH, Grody WW. Should we be applying warfarin pharmacogenetics to clinical practice? No, not now. Ann Intern Med 2009; 151(4):270-3, W95.
  18. Cavallari LH, Shin J, Perera MA. Role of pharmacogenomics in the management of traditional and novel oral anticoagulants. Pharmacotherapy 2011; 31(12):1192-207.
  19. McClain MR, Palomaki GE, Piper M et al. A rapid-ACCE review of CYP2C9 and VKORC1 alleles testing to inform warfarin dosing in adults at elevated risk for thrombotic events to avoid serious bleeding. Genet Med 2008; 10(2):89-98.
  20. Zhu Y, Shennan M, Reynolds KK et al. Estimation of warfarin maintenance dose based on VKORC1 (-1639 G>A) and CYP2C9 genotypes. Clin Chem 2007; 53(7):1199-205.
  21. Schelleman H, Chen J, Chen Z et al. Dosing algorithms to predict warfarin maintenance dose in Caucasians and African Americans. Clin Pharmacol Ther 2008; 84(3):332-9.
  22. Gage BF, Eby C, Johnson JA et al. Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin. Clin Pharmacol Ther 2008; 84(3):326-31.
  23. Wu AH, Wang P, Smith A et al. Dosing algorithm for warfarin using CYP2C9 and VKORC1 genotyping from a multi-ethnic population: comparison with other equations. Pharmacogenomics 2008; 9(2):169-78.
  24. Hatch E, Wynne H, Avery P et al. Application of a pharmacogenetic-based warfarin dosing algorithm derived from British patients to predict dose in Swedish patients. J Thromb Haemost 2008; 6(6):1038-40.
  25. Wadelius M, Chen LY, Eriksson N et al. Association of warfarin dose with genes involved in its action and metabolism. Hum Genet 2007; 121(1):23-34.
  26. Lenzini P, Wadelius M, Kimmel S et al. Integration of genetic, clinical, and INR data to refine warfarin dosing. Clin Pharmacol Ther 2010; 87(5):572-8.
  27. Wells PS, Majeed H, Kassem S et al. A regression model to predict warfarin dose from clinical variables and polymorphisms in CYP2C9, CYP4F2, and VKORC1: Derivation in a sample with predominantly a history of venous thromboembolism. Thromb Res 2010; 125(6):e259-64.
  28. Sagreiya H, Berube C, Wen A et al. Extending and evaluating a warfarin dosing algorithm that includes CYP4F2 and pooled rare variants of CYP2C9. Pharmacogenet Genomics 2010; 20(7):407-13.
  29. Liang R, Wang C, Zhao H et al. Influence of CYP4F2 genotype on warfarin dose requirement-a systematic review and meta-analysis. Thromb Res 2012; 130(1):38-44.
  30. Schwarz UI, Ritchie MD, Bradford Y et al. Genetic determinants of response to warfarin during initial anticoagulation. N Engl J Med 2008; 358(10):999-1008.
  31. Wadelius M, Chen LY, Lindh JD et al. The largest prospective warfarin-treated cohort supports genetic forecasting. Blood 2009; 113(4):784-92.
  32. Meckley LM, Wittkowsky AK, Rieder MJ et al. An analysis of the relative effects of VKORC1 and CYP2C9 variants on anticoagulation related outcomes in warfarin-treated patients. Thromb Haemost 2008; 100(2):229-39.
  33. Limdi NA, Wiener H, Goldstein JA et al. Influence of CYP2C9 and VKORC1 on warfarin response during initiation of therapy. Blood Cells Mol Dis 2009; 43(1):119-28.
  34. Pautas E, Moreau C, Gouin-Thibault I et al. Genetic factors (VKORC1, CYP2C9, EPHX1, and CYP4F2) are predictor variables for warfarin response in very elderly, frail inpatients. Clin Pharmacol Ther 2010; 87(1):57-64.
  35. Ferder NS, Eby CS, Deych E et al. Ability of VKORC1 and CYP2C9 to predict therapeutic warfarin dose during the initial weeks of therapy. J Thromb Haemost 2010; 8(1):95-100.
  36. Moreau C, Pautas E, Gouin-Thibault I et al. Predicting the warfarin maintenance dose in elderly inpatients at treatment initiation: accuracy of dosing algorithms incorporating or not VKORC1/CYP2C9 genotypes. J Thromb Haemost 2011; 9(4):711-8.
  37. Wen MS, Lee M, Chen JJ et al. Prospective study of warfarin dosage requirements based on CYP2C9 and VKORC1 genotypes. Clin Pharmacol Ther 2008; 84(1):83-9.
  38. Millican EA, Lenzini PA, Milligan PE et al. Genetic-based dosing in orthopedic patients beginning warfarin therapy. Blood 2007; 110(5):1511-5.
  39. Klein TE, Altman RB, Eriksson N et al. Estimation of the warfarin dose with clinical and pharmacogenetic data. N Engl J Med 2009; 360(8):753-64.
  40. Avery PJ, Jorgensen A, Hamberg AK et al. A proposal for an individualized pharmacogenetics-based warfarin initiation dose regimen for patients commencing anticoagulation therapy. Clin Pharmacol Ther 2011; 90(5):701-6.
  41. Gong IY, Tirona RG, Schwarz UI et al. Prospective evaluation of a pharmacogenetics-guided warfarin loading and maintenance dose regimen for initiation of therapy. Blood 2011; 118(11):3163-71.
  42. Horne BD, Lenzini PA, Wadelius M et al. Pharmacogenetic warfarin dose refinements remain significantly influenced by genetic factors after one week of therapy. Thromb Haemost 2012; 107(2):232-40.
  43. Perlstein TS, Goldhaber SZ, Nelson K et al. The Creating an Optimal Warfarin Nomogram (CROWN) Study. Thromb Haemost 2012; 107(1):59-68.
  44. Shaw PB, Donovan JL, Tran MT et al. Accuracy assessment of pharmacogenetically predictive warfarin dosing algorithms in patients of an academic medical center anticoagulation clinic. J Thromb Thrombolysis 2010; 30(2):220-5.
  45. Lubitz SA, Scott SA, Rothlauf EB et al. Comparative performance of gene-based warfarin dosing algorithms in a multiethnic population. J Thromb Haemost 2010; 8(5):1018-26.
  46. Roper N, Storer B, Bona R et al. Validation and comparison of pharmacogenetics-based warfarin dosing algorithms for application of pharmacogenetic testing. J Mol Diagn 2010; 12(3):283-91.
  47. Zambon CF, Pengo V, Padrini R et al. VKORC1, CYP2C9 and CYP4F2 genetic-based algorithm for warfarin dosing: an Italian retrospective study. Pharmacogenomics 2011; 12(1):15-25.
  48. Limdi NA, Wadelius M, Cavallari L et al. Warfarin pharmacogenetics: a single VKORC1 polymorphism is predictive of dose across 3 racial groups. Blood 2010; 115(18):3827-34.
  49. Cavallari LH, Momary KM, Patel SR et al. Pharmacogenomics of warfarin dose requirements in Hispanics. Blood Cells Mol Dis 2011; 46(2):147-50.
  50. Gan GG, Phipps ME, Lee MM et al. Contribution of VKORC1 and CYP2C9 polymorphisms in the interethnic variability of warfarin dose in Malaysian populations. Ann Hematol 2011; 90(6):635-41.
  51. Perera MA, Gamazon E, Cavallari LH et al. The missing association: sequencing-based discovery of novel SNPs in VKORC1 and CYP2C9 that affect warfarin dose in African Americans. Clin Pharmacol Ther 2011; 89(3):408-15.
  52. Ramirez AH, Shi Y, Schildcrout JS et al. Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record. Pharmacogenomics 2012; 13(4):407-18.
  53. Sangviroon A, Panomvana D, Tassaneeyakul W et al. Pharmacokinetic and pharmacodynamic variation associated with VKORC1 and CYP2C9 polymorphisms in Thai patients taking warfarin. Drug Metab Pharmacokinet 2010; 25(6):531-8.
  54. Shahin MH, Khalifa SI, Gong Y et al. Genetic and nongenetic factors associated with warfarin dose requirements in Egyptian patients. Pharmacogenet Genomics 2011; 21(3):130-5.
  55. You JH, Wong RS, Waye MM et al. Warfarin dosing algorithm using clinical, demographic and pharmacogenetic data from Chinese patients. J Thromb Thrombolysis 2011; 31(1):113-8.
  56. Aomori T, Obayashi K, Fujita Y et al. Influence of CYP2C9 and vitamin k oxide reductase complex (VKORC)1 polymorphisms on time to determine the warfarin maintenance dose. Pharmazie 2011; 66(3):222-5.
  57. Valentin, II, Vazquez J, Rivera-Miranda G et al. Prediction of warfarin dose reductions in Puerto Rican patients, based on combinatorial CYP2C9 and VKORC1 genotypes. Ann Pharmacother 2012; 46(2):208-18.
  58. Anderson JL, Horne BD, Stevens SM et al. Randomized trial of genotype-guided versus standard warfarin dosing in patients initiating oral anticoagulation. Circulation 2007; 116(22):2563-70.
  59. McMillin GA, Melis R, Wilson A et al. Gene-based warfarin dosing compared with standard of care practices in an orthopedic surgery population: a prospective, parallel cohort study. Ther Drug Monit 2010; 32(3):338-45.
  60. Burmester JK, Berg RL, Yale SH et al. A randomized controlled trial of genotype-based Coumadin initiation. Genet Med 2011; 13(6):509-18.
  61. Epstein RS, Moyer TP, Aubert RE et al. Warfarin genotyping reduces hospitalization rates results from the MM-WES (Medco-Mayo Warfarin Effectiveness study). J Am Coll Cardiol 2010; 55(25):2804-12.
  62. Anderson JL, Horne BD, Stevens SM et al. A randomized and clinical effectiveness trial comparing two pharmacogenetic algorithms and standard care for individualizing warfarin dosing (CoumaGen-II). Circulation 2012; 125(16):1997-2005.
  63. Kangelaris KN, Bent S, Nussbaum RL et al. Genetic testing before anticoagulation? A systematic review of pharmacogenetic dosing of warfarin. J Gen Intern Med 2009; 24(5):656-64.
  64. French B, Joo J, Geller NL et al. Statistical design of personalized medicine interventions: the Clarification of Optimal Anticoagulation through Genetics (COAG) trial. Trials 2010; 11:108.
  65. van Schie RM, Wadelius MI, Kamali F et al. Genotype-guided dosing of coumarin derivatives: the European pharmacogenetics of anticoagulant therapy (EU-PACT) trial design. Pharmacogenomics 2009; 10(10):1687-95.
  66. Flockhart DA, O'Kane D, Williams MS et al. Pharmacogenetic testing of CYP2C9 and VKORC1 alleles for warfarin. Genet Med 2008; 10(2):139-50.
  67. Hirsh J, Guyatt G, Albers GW et al. Antithrombotic and thrombolytic therapy: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest 2008; 133(6 Suppl):110S-12S.
  68. Becquemont L, Alfirevic A, Amstutz U et al. Practical recommendations for pharmacogenomics-based prescription: 2010 ESF-UB Conference on Pharmacogenetics and Pharmacogenomics. Pharmacogenomics 2011; 12(1):113-24.
  69. Genetic Testing for Warfarin Dose. Chicago, Illinois: Blue Cross Blue Shield Association Medical Policy Reference Manual (2012 December) Medicine 2.04.48.
March 2012  Policy updated with literature review; no changes to policy statements. References 33, 38, 44-46, 53, 58, 60 added.
October 2013 Policy formatting and language revised.  Policy statement unchanged.
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Genetic Testing for Warfarin Dose