Prospective alpha allocation in the Clarification of Optimal Anticoagulation through Genetics (COAG) trial

Effect of Genotype-Guided Warfarin Dosing on Clinical Events and Anticoagulation Control Among Patients Undergoing Hip or Knee Arthroplasty: The GIFT Randomized Clinical Trial

IMPORTANCE

Warfarin use accounts for more medication-related emergency department visits among older patients than any other drug. Whether genotype-guided warfarin dosing can prevent these adverse events is unknown.

OBJECTIVE

To determine whether genotype-guided dosing improves the safety of warfarin initiation.

DESIGN, SETTING, AND PATIENTS

The randomized clinical Genetic Informatics Trial (GIFT) of Warfarin to Prevent Deep Vein Thrombosis included patients aged 65 years or older initiating warfarin for elective hip or knee arthroplasty and was conducted at 6 US medical centers. Enrollment began in April 2011 and follow-up concluded in October 2016.

INTERVENTIONS

Patients were genotyped for the following polymorphisms: VKORC1-1639G>A, CYP2C9*2, CYP2C9*3, and CYP4F2 V433M. In a 2 × 2 factorial design, patients were randomized to genotype-guided (n = 831) or clinically guided (n = 819) warfarin dosing on days 1 through 11 of therapy and to a target international normalized ratio (INR) of either 1.8 or 2.5. The recommended doses of warfarin were open label, but the patients and clinicians were blinded to study group assignment.

MAIN OUTCOMES AND MEASURES

The primary end point was the composite of major bleeding, INR of 4 or greater, venous thromboembolism, or death. Patients underwent a screening lower-extremity duplex ultrasound approximately 1 month after arthroplasty.

RESULTS

Among 1650 randomized patients (mean age, 72.1 years [SD, 5.4 years]; 63.6% women; 91.0% white), 1597 (96.8%) received at least 1 dose of warfarin therapy and completed the trial (n = 808 in genotype-guided group vs n = 789 in clinically guided group). A total of 87 patients (10.8%) in the genotype-guided group vs 116 patients (14.7%) in the clinically guided warfarin dosing group met at least 1 of the end points (absolute difference, 3.9% [95% CI, 0.7%-7.2%], P = .02; relative rate [RR], 0.73 [95% CI, 0.56-0.95]). The numbers of individual events in the genotype-guided group vs the clinically guided group were 2 vs 8 for major bleeding (RR, 0.24; 95% CI, 0.05-1.15), 56 vs 77 for INR of 4 or greater (RR, 0.71; 95% CI, 0.51-0.99), 33 vs 38 for venous thromboembolism (RR, 0.85; 95% CI, 0.54-1.34), and there were no deaths.

CONCLUSIONS AND RELEVANCE

Among patients undergoing elective hip or knee arthroplasty and treated with perioperative warfarin, genotype-guided warfarin dosing, compared with clinically guided dosing, reduced the combined risk of major bleeding, INR of 4 or greater, venous thromboembolism, or death. Further research is needed to determine the cost-effectiveness of personalized warfarin dosing.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01006733.

A systematic analysis and comparison of warfarin initiation strategies

OBJECTIVE

Randomized trials have reported inconsistent evidence on the effectiveness of algorithms that use genotypes to initiate warfarin therapy. The Clarification of Optimal Anticoagulation through Genetics (COAG) trial initiated therapy on the basis of predicted maintenance doses, with a pharmacogenetic-guided algorithm in one study group and a clinically guided algorithm in the other. The European Pharmacogenetics of Anticoagulant Therapy (EU-PACT) consortium initiated therapy on the basis of loading doses, with an algorithm-based prediction in one study group and a fixed-dose regimen in the other. To understand the differences between these trials, we compared the initial doses between alternative dosing algorithms (the pharmacogenetic-guided and clinically guided algorithms developed by Gage and colleagues and those developed by the International Warfarin Pharmacogenetics Consortium) and between the COAG and EU-PACT dose-initiation strategies.

METHODS

This was a secondary analysis of the COAG trial - a double-blind, randomized-controlled trial (2009-2013) - conducted at 18 clinical centers in the USA, which included 1010 adults initiating warfarin therapy, of whom 719 achieved maintenance dose.

RESULTS

Among COAG participants, the distribution of initial doses differed between algorithms, but showed similar prediction accuracy for maintenance dose. However, had the COAG trial implemented the EU-PACT strategy, the 3-day initial dose would have been 4.8 mg greater among participants randomized to pharmacogenetic-guided dosing, but only 2.5 mg greater among participants randomized to clinically guided dosing (P<0.001).

CONCLUSION

Compared with the COAG trial, the EU-PACT trial used systematically larger loading doses in the pharmacogenetic-guided group and might have inadequately adjusted for clinical variability in warfarin dose requirements in the fixed-dose group.

Adjusting for misclassification in a stratified biomarker clinical trial

Clinical trials utilizing predictive biomarkers have become a research focus in personalized medicine. We investigate the effects of biomarker misclassification on the design and analysis of stratified biomarker clinical trials. For a variety of inference problems including marker-treatment interaction in particular, we show that marker misclassification may have profound adverse effects on the coverage of confidence intervals, power of the tests, and required sample sizes. For each inferential problem, we propose methods to adjust for the classification errors.

Genotype-guided use of oral antithrombotic therapy: a pharmacoeconomic perspective

Pharmacogenomics focuses on tailoring therapy to the individual as opposed to the historical model of fitting the individual to the therapy, and it offers the potential to maximize medication efficacy while reducing adverse events. By its very nature, personalized medicine is conducive to a patient-centered care model. Oral antithrombotics as a class could benefit immensely from this type of approach because an imbalance of safety and efficacy in either direction can yield deadly consequences. Since the current healthcare climate in the USA requires thoughtful allocation of resources, pharmacoeconomic analysis has become critical for all stakeholders, and the adoption of new technologies hinges upon economic impact. This article summarizes the current state of genetics in oral antithrombotic therapy, including clinical relevance as well as cost-effectiveness from a US healthcare system perspective, and provides insight into the future of pharmacogenomics in treating and preventing thromboembolic disorders.

A pharmacogenetic versus a clinical algorithm for warfarin dosing

BACKGROUND

The clinical utility of genotype-guided (pharmacogenetically based) dosing of warfarin has been tested only in small clinical trials or observational studies, with equivocal results.

METHODS

We randomly assigned 1015 patients to receive doses of warfarin during the first 5 days of therapy that were determined according to a dosing algorithm that included both clinical variables and genotype data or to one that included clinical variables only. All patients and clinicians were unaware of the dose of warfarin during the first 4 weeks of therapy. The primary outcome was the percentage of time that the international normalized ratio (INR) was in the therapeutic range from day 4 or 5 through day 28 of therapy.

RESULTS

At 4 weeks, the mean percentage of time in the therapeutic range was 45.2% in the genotype-guided group and 45.4% in the clinically guided group (adjusted mean difference, [genotype-guided group minus clinically guided group], -0.2; 95% confidence interval, -3.4 to 3.1; P=0.91). There also was no significant between-group difference among patients with a predicted dose difference between the two algorithms of 1 mg per day or more. There was, however, a significant interaction between dosing strategy and race (P=0.003). Among black patients, the mean percentage of time in the therapeutic range was less in the genotype-guided group than in the clinically guided group. The rates of the combined outcome of any INR of 4 or more, major bleeding, or thromboembolism did not differ significantly according to dosing strategy.

CONCLUSIONS

Genotype-guided dosing of warfarin did not improve anticoagulation control during the first 4 weeks of therapy. (Funded by the National Heart, Lung, and Blood Institute and others; COAG ClinicalTrials.gov number, NCT00839657.).

Cost-effectiveness of pharmacogenetics-guided warfarin therapy vs. alternative anticoagulation in atrial fibrillation

Pharmacogenetics-guided warfarin dosing is an alternative to standard clinical algorithms and new oral anticoagulants for patients with nonvalvular atrial fibrillation. However, clinical evidence for pharmacogenetics-guided warfarin dosing is limited to intermediary outcomes, and consequently, there is a lack of information on the cost-effectiveness of anticoagulation treatment options. A clinical trial simulation of S-warfarin was used to predict times within therapeutic range for different dosing algorithms. Relative risks of clinical events, obtained from a meta-analysis of trials linking times within therapeutic range with outcomes, served as inputs to an economic analysis. Neither dabigatran nor rivaroxaban were cost-effective options. Along the cost-effectiveness frontier, in relation to clinically dosed warfarin, pharmacogenetics-guided warfarin and apixaban had incremental cost-effectiveness ratios of £13,226 and £20,671 per quality-adjusted life year gained, respectively. On the basis of our simulations, apixaban appears to be the most cost-effective treatment.

Warfarin pharmacogenetics: A controlled dose–response study in healthy subjects

The aim of this study was to determine how genetic variants contribute to warfarin dosing variability when non-genetic factors are controlled. Thirty healthy subjects were subjected to a warfarin dosing algorithm with daily international normalized ratio (INR) measurements to INR ≥ 2.0, then off warfarin to INR ≤ 1.2. The primary outcome was the cumulative dose required to achieve INR ≥ 2.0 for 2 consecutive days. CYP2C9 ( p=0.004) and VKORC1 ( p=0.02) variant carriers required lower cumulative doses, and CYP4F2 carriers required higher doses ( p=0.04). Subjects with variants in both CYP2C9 and VKORC1 required fewer days to reach INR ≥ 2.0 than wild-type subjects or those with variants in CYP2C9 or VKORC1 ( p=0.01). Genetic contribution to dose variability (~62%) was greater than previously reported, suggesting that uncontrolled clinical variables influence the effect of these variants. In conclusion, genotype-guided warfarin-dosing algorithms may rely more on genetic variables in healthier individuals than in patients with clinical confounders. ClinicalTrials.gov Identifier: NCT01520402

Rationale and design of the Clarification of Optimal Anticoagulation through Genetics trial

BACKGROUND

Current dosing practices for warfarin are empiric and result in the need for frequent dose changes as the international normalized ratio gets too high or too low. As a result, patients are put at increased risk for thromboembolism, bleeding, and premature discontinuation of anticoagulation therapy. Prior research has identified clinical and genetic factors that can alter warfarin dose requirements, but few randomized clinical trials have examined the utility of using clinical and genetic information to improve anticoagulation control or clinical outcomes among a large, diverse group of patients initiating warfarin.

METHODS

The COAG trial is a multicenter, double-blind, randomized trial comparing 2 approaches to guiding warfarin therapy initiation: initiation of warfarin therapy based on algorithms using clinical information plus an individual's genotype using genes known to influence warfarin response ("genotype-guided dosing") versus only clinical information ("clinical-guided dosing") (www.clinicaltrials.gov Identifier: NCT00839657).

RESULTS

The COAG trial design is described. The study hypothesis is that, among 1,022 enrolled patients, genotype-guided dosing relative to clinical-guided dosing during the initial dosing period will increase the percentage of time that patients spend in the therapeutic international normalized ratio range in the first 4 weeks of therapy.

CONCLUSION

The COAG will determine if genetic information provides added benefit above and beyond clinical information alone.

Personalized medicine: is it a pharmacogenetic mirage?

The notion of personalized medicine has developed from the application of the discipline of pharmacogenetics to clinical medicine. Although the clinical relevance of genetically-determined inter-individual differences in pharmacokinetics is poorly understood, and the genotype-phenotype association data on clinical outcomes often inconsistent, officially approved drug labels frequently include pharmacogenetic information concerning the safety and/or efficacy of a number of drugs and refer to the availability of the pharmacogenetic test concerned. Regulatory authorities differ in their approach to these issues. Evidence emerging subsequently has generally revealed the pharmacogenetic information included in the label to be premature. Revised drugs labels, together with a flurry of other collateral activities, have raised public expectations of personalized medicine, promoted as 'the right drug at the right dose the first time.' These expectations place the prescribing physician in a dilemma and at risk of litigation, especially when evidence-based information on genotype-related dosing schedules is to all intent and purposes non-existent and guidelines, intended to improve the clinical utility of available pharmacogenetic information or tests, distance themselves from any responsibility. Lack of efficacy or an adverse drug reaction is frequently related to non-genetic factors. Phenoconversion, arising from drug interactions, poses another often neglected challenge to any potential success of personalized medicine by mimicking genetically-determined enzyme deficiency. A more realistic promotion of personalized medicine should acknowledge current limitations and emphasize that pharmacogenetic testing can only improve the likelihood of diminishing a specific toxic effect or increasing the likelihood of a beneficial effect and that application of pharmacogenetics to clinical medicine cannot adequately predict drug response in individual patients.

Genetics informatics trial (GIFT) of warfarin to prevent deep vein thrombosis (DVT): rationale and study design

The risk of venous thromboembolism (VTE) is higher after the total hip or knee replacement surgery than after almost any other surgical procedure; warfarin sodium is commonly prescribed to reduce this peri-operative risk. Warfarin has a narrow therapeutic window with high inter-individual dose variability and can cause hemorrhage. The genetics-informatics trial (GIFT) of warfarin to prevent deep vein thrombosis (DVT) is a 2 × 2 factorial-design, randomized controlled trial designed to compare the safety and effectiveness of warfarin-dosing strategies. GIFT will answer two questions: (1) does pharmacogenetic (PGx) dosing reduce the rate of adverse events in orthopedic patients; and (2) is a lower target international normalized ratio (INR) non-inferior to a higher target INR in orthopedic participants? The composite primary endpoint of the trial is symptomatic and asymptomatic VTE (identified on screening ultrasonography), major hemorrhage, INR ≥ 4, and death.

Challenges and opportunities in implementing pharmacogenomics testing in the clinics

The field of pharmacogenomics aims to incorporate individual patient genomic information into treatment selection. This is a rapidly evolving field with significant clinical promise. Implementation into clinical practice has several challenges that must be overcome. Genomics-based information encompasses large databases and requires expert knowledge for interpretation. Existing research suggests there are already several areas where pharmacogenomics-based decision-making is ripe for adoption into clinical practice. Impediments exist that must be overcome prior to large-scale implementation of existing pharmacogenomics-based therapies. There are several institutions and corporations at the forefront of implementation that are leading the development; however, larger systems-based approaches will be necessary. This article will discuss some of the present successes and future challenges that are necessary to overcome in order to implement a more patient-centered healthcare system.

Clinically relevant genetic variations in drug metabolizing enzymes

In the field of pharmacogenetics, we currently have a few markers to guide physicians as to the best course of therapy for patients. For the most part, these genetic variants are within a drug metabolizing enzyme that has a large effect on the degree or rate at which a drug is converted to its metabolites. For many drugs, response and toxicity are multi-genic traits and understanding relationships between a patient's genetic variation in drug metabolizing enzymes and the efficacy and/or toxicity of a medication offers the potential to optimize therapies. This review will focus on variants in drug metabolizing enzymes with predictable and relatively large impacts on drug efficacy and/or toxicity; some of these drug/gene variant pairs have impacted drug labels by the United States Food and Drug Administration. The challenges in identifying genetic markers and implementing clinical changes based on known markers will be discussed. In addition, the impact of next generation sequencing in identifying rare variants will be addressed.

Statistical design of personalized medicine interventions: the Clarification of Optimal Anticoagulation through Genetics (COAG) trial

Background

There is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants.

Methods

The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in CYP2C9 and VKORC1; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.

Results

We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either CYP2C9 or VKORC1 and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.

Conclusions

In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.

Trial Registration

clinicaltrials.gov: NCT00839657