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Evidence requirements for implementation of precision medicine (PM), whether informed by genomic or clinical data, are not well defined. Evidence requirements are driven by uncertainty and its attendant consequences; these aspects can be quantified by a novel technique in health economics: value of information analysis (VOI). We utilized VOI analysis to compare the evidence levels over time for warfarin dosing based on pharmacogenomic vs. amiodarone-warfarin drug-drug interaction information. The primary outcome was the expected value of perfect information (EVPI), which is an estimate of the upper limit of the societal value of conducting future research. Over the past decade, the EVPI for the pharmacogenomic strategy decreased from $1,550 to $140 vs. $1,220 to $280 per patient for the drug-interaction strategy. Evidence levels thus appear to be higher for pharmacogenomic-guided vs. drug-interaction-guided warfarin dosing. Clinical guidelines and reimbursement policies for warfarin PM could be informed by these findings., (© 2017 American Society for Clinical Pharmacology and Therapeutics.)

Although there are several examples in which pharmacogenomic testing seems to provide clinical and economic value, use of pharmacogenomics as a tool to improve drug therapy through routine screening of unselected patients is currently tentative. An informal evaluation of the clinical benefits and economic costs of pharmacogenomic screening suggests that improving the evidence base, addressing uncertainty, and facilitating implementation can lead to practical and cost-effective pharmacogenomic screening programs., (© 2015 ASCPT.)

A key to accelerating the appropriate integration of genomic applications into healthcare in the coming decades will be the ability to assess the tradeoffs between clinical benefits and clinical risks of genetic tests in a timely manner. Several factors limit the ability of stakeholders to achieve this objective, including the lack of direct evidence, the lack of a framework to quantitatively assess risk and benefit, and the lack of a formal analytic approach to assess uncertainty. We propose that a formal, quantitative risk-benefit framework may be particularly useful for assessing genetic tests intended to influence health outcomes, and communicating the potential clinical benefits, harms, and uncertainty to stakeholders. As part of the development process for such a framework, a stakeholder meeting was held in Seattle (Wash., USA) in December of 2008, with the objective of discussing a risk-benefit framework, using warfarin pharmacogenomics as a case study. Participants engaged in focused discussion to elucidate the potential role of genetic test risk-benefit analysis in informing decision-making, categorizing genetic tests and directing research prioritization. This research investigation focuses on qualitative analysis of responses elicited from workshop participants during the proceedings of the workshop session. The major findings of the workshop were: (1) stakeholder support for risk-benefit modeling as a tool to structure discussion of the clinical utility of genetic tests; (2) desire for the modeling process to be iterative, transparent, and parsimonious in its presentation to stakeholders, and (3) some concern with the use of quality-adjusted life-years in the evaluation process. The meeting's findings emphasize the potential utility of risk-benefit analysis in genetic test evaluation, and highlight key areas for future research and stakeholder consensus-building., (Copyright © 2010 S. Karger AG, Basel.)

Purpose: Evaluation of genomic tests is often challenging because of the lack of direct evidence of clinical benefit compared with usual care and unclear evidence requirements. To address these issues, this study presents a risk-benefit framework for assessing the health-related utility of genomic tests., Methods: We incorporated approaches from a variety of established fields including decision science, outcomes research, and health technology assessment to develop the framework. Additionally, we considered genomic test stakeholder perspectives and case studies., Results: We developed a three-tiered framework: first, we use decision-analytic modeling techniques to synthesize data, project incidence of clinical events, and assess uncertainty. Second, we defined the health-related utility of genomic tests as improvement in health outcomes as measured by clinical event rates, life expectancy, and quality-adjusted life-years. Finally, we displayed results using a risk-benefit policy matrix to facilitate the interpretation and implementation of findings from these analyses., Conclusion: A formal risk-benefit framework may accelerate the utilization and practice-based evidence development of genomic tests that pose low risk and offer plausible clinical benefit, while discouraging premature use of tests that provide little benefit or pose significant health risks compared with usual care.

In pursuing personalized medicine, pharmacogenomic (PGx) knowledge may help guide prescribing drugs based on a person's genotype. Here we evaluate the feasibility of incorporating PGx knowledge, combined with clinical data, to support clinical decision-making by: 1) analyzing clinically relevant knowledge contained in PGx knowledge resources; 2) evaluating the feasibility of a rule-based framework to support formal representation of clinically relevant knowledge contained in PGx knowledge resources; and, 3) evaluating the ability of an electronic medical record/electronic health record (EMR/EHR) to provide computable forms of clinical data needed for PGx clinical decision support. Findings suggest that the PharmGKB is a good source for PGx knowledge to supplement information contained in FDA approved drug labels. Furthermore, we found that with supporting knowledge (e.g. IF age <18 THEN patient is a child), sufficient clinical data exists in University of Washington's EMR systems to support 50% of PGx knowledge contained in drug labels that could be expressed as rules.

In this review, we discuss the potential expectations, validity, predictive ability, and reality of pharmacogenetics in (1) titration of medication dose, (2) prediction of intended (efficacy) drug response, and (3) dose prediction of unintended (adverse) drug response. We expound on what these potential genetic predictors tell us and, more importantly, what they cannot tell us. Although pharmacogenetic markers have been hailed as promising tools, these proclamations are based mainly on associations rather than their evaluation as predictors. To put the expectations of the promise of pharmacogenetics in a realistic perspective, we review three examples. First, warfarin pharmacogenetics, wherein although the validity of the genetic variant dose is established and there is a validity of genetic variant-hemorrhage association, the clinical utility of testing is not clear. Second, the strong and clinically relevant HLA-Stevens-Johnson syndrome/toxic epidermal necrolysis association highlights the role of ethnicity. Third, the influence of CYP2D6 on tamoxifen efficacy, a model candidate with potential clinical utility but unclear validity. These examples highlight both the challenges and opportunities of pharmacogenomics. First, establishing a valid association between a genetic variation and drug response; second, doing so for a clinically meaningful outcome; and third, providing solid evidence or rationale for improvement in patient outcomes compared with current standard of care.

Background: In 2007, the US FDA added information about pharmacogenomics to the warfarin label based on the influence of the CYP2C9 and VKORC1 genes on anticoagulation-related outcomes. Payers will be facing increasing demand for coverage decisions regarding this technology, but the potential clinical and economic impacts of testing are not clear., Objective: To develop a policy model to evaluate the potential outcomes of warfarin pharmacogenomic testing based on the most recently available data., Methods: A decision-analytic Markov model was developed to assess the addition of genetic testing to anticoagulation clinic standard care for a hypothetical cohort of warfarin patients. The model was based on anticoagulation status (international normalized ratio), a common outcome measure in clinical trials that captures both the benefits and risks of warfarin therapy. Initial estimates of testing effects were derived from a recently completed randomized controlled trial (n = 200). Healthcare cost ($US, year 2007 values) and health-state utility data were obtained from the literature. The perspective was that of a US third-party payer. Probabilistic and one-way sensitivity analyses were performed to explore the range of plausible results., Results: The policy model included thromboembolic events (TEs) and bleeding events and was populated by data from the COUMAGEN trial. The rate of bleeding calculated for standard care approximated bleeding rates found in an independent cohort of warfarin patients. According to our model, pharmacogenomic testing provided an absolute reduction in the incidence of bleeds of 0.17%, but an absolute increase in the incidence of TEs of 0.03%. The improvement in QALYs was small, 0.003, with an increase in total cost of $US162 (year 2007 values). The incremental cost-effectiveness ratio (ICER) ranged from testing dominating to standard care dominating, and the ICER was <$US50,000 per QALY in 46% of simulations. Results were most sensitive to the cost of genotyping and the effect of genotyping., Conclusion: Our model, based on initial clinical studies to date, suggests that warfarin pharmacogenomic testing may provide a small clinical benefit with significant uncertainty in economic value. Given the uncertainty in the analysis, further updates will be important as additional clinical data become available.

The use of pharmacogenetic testing in clinical practice is limited thus far. A potential barrier to the widespread implementation of pharmacogenetic testing is the lack of evidence on whether testing provides good value for money. The objective of this review was to provide a systematic and critical review of economic evaluations of pharmacogenetic testing. A literature search using publically available databases was performed for articles published up to October 2009. To be included, studies had to meet the definition of being a pharmacogenomic study (defined as use of information on human genetic variation to target drug therapy) and an economic evaluation (defined as an evaluation of both costs and clinical outcomes). Articles that met these criteria were subsequently reviewed and graded using the Quality of Health Economic Studies (QHES) instrument. Lastly, the evidence for biomarker validity and utility were qualitatively assessed using expert opinion. A total of 34 articles were identified using our defined criteria. The most common disease category was thromboembolic-related diseases (26%), while the most common biomarkers were thiopurine methyltransferase and cytochrome P450 2C9 (18% each). Almost all studies were published after 2004 (91%). Two types of studies were identified: cost-effectiveness studies and cost-utility studies, with roughly half of the overall studies being cost-utility studies (53%) and a majority of these published within the last 3 years. The average quality score was 77 (range 29-99). Of the biomarkers reviewed, it was estimated that most had demonstrated clinical validity, but only two had demonstrated clinical utility. Despite a recent increase in the number of economic evaluations of pharmacogenetic applications, further studies examining the clinical validity and utility of these biomarkers are needed to support cost-effectiveness assessments.

Objectives: Pharmacogenomic applications in oncology offer significant promise, but the clinical and economic implications remain unclear. The objective of this study was to evaluate the potential cost-utility of implementing epidermal growth factor receptor (EGFR) testing before initiating second-line therapy for advanced refractory non-small-cell lung cancer (NSCLC)., Methods: We developed a decision analytic model to evaluate the cost-utility of EGFR protein expression or gene copy number testing compared to standard care with erlotinib in refractory advanced NSCLC patients. Costs and utilities were obtained from publicly available sources. We performed sensitivity analyses to evaluate uncertainty in the results., Results: The quality-adjusted life expectancies for erlotinib, EGFR protein expression testing, and gene copy number testing were: 0.44, 0.48, and 0.50 quality-adjusted life years (QALYs); and the costs were: $57,238, $63,512, and $66,447, respectively. The most cost-effective testing option, EGFR gene copy number testing, produced an incremental cost-effectiveness ratio of $162,018/QALY compared to no testing (erlotinib). The results were most sensitive to the survival estimates, health state utilities, and cost of disease progression. In the probabilistic sensitivity analyses, erlotinib without testing was the optimal treatment strategy until the $150,000/QALY willingness-to-pay threshold, after which gene copy testing was optimal. The discounted expected value of perfect information at a $100,000/QALY threshold in the USA over 5 years was $31.4 million., Conclusions: The study results suggest that EGFR pharmacogenomic testing has the potential to improve quality-adjusted life expectancy in the treatment of refractory NSCLC by a clinically meaningful margin at a value commensurate with the approved therapies in this setting. Additional research in this area is warranted.

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.

Initiation of warfarin therapy using trial-and-error dosing is problematic. Our goal was to develop and validate a pharmacogenetic algorithm. In the derivation cohort of 1,015 participants, the independent predictors of therapeutic dose were: VKORC1 polymorphism -1639/3673 G>A (-28% per allele), body surface area (BSA) (+11% per 0.25 m(2)), CYP2C9(*)3 (-33% per allele), CYP2C9(*)2 (-19% per allele), age (-7% per decade), target international normalized ratio (INR) (+11% per 0.5 unit increase), amiodarone use (-22%), smoker status (+10%), race (-9%), and current thrombosis (+7%). This pharmacogenetic equation explained 53-54% of the variability in the warfarin dose in the derivation and validation (N= 292) cohorts. For comparison, a clinical equation explained only 17-22% of the dose variability (P < 0.001). In the validation cohort, we prospectively used the pharmacogenetic-dosing algorithm in patients initiating warfarin therapy, two of whom had a major hemorrhage. To facilitate use of these pharmacogenetic and clinical algorithms, we developed a nonprofit website, http://www.WarfarinDosing.org.

Some pharmacogenetic tests may provide ancillary disease risk information. To evaluate evidence and assess the social and policy implications of ancillary disease risk information associated with candidate pharmacogenetic variants, We conducted a literature search and abstract review of disease susceptibility studies for each of 42 gene variants potentially associated with drug response. Twenty-two variants (53%) had suggested association with disease risk in at least two studies, and sixteen (38%) were for diseases other than the pharmacogenetic indication. Seven variants (16%) were associated with risk for at least two different diseases. Pharmacogenetic tests have the potential to provide ancillary disease risk information, and this potential should be considered as pharmacogenetic tests are brought into clinical use. Implications will vary with each test but tests should be evaluated individually within a framework that outlines the potential implications of ancillary information.

This article reviews the regulatory, social, policy, and other issues that will shape the development of pharmacogenomics applications. We identify and analyze 19 key public policy issues, ranging from the economic incentives for linked diagnostic-drug development, to the regulation of tests and drugs, and to privacy and informed consent. Challenging technical, business, and policy-related issues might either hinder progress in the field of pharmacogenomics or potentially accelerate it, depending on how they are addressed and resolved. How well the numerous important stakeholders - both private and public - address these issues will be critical for pharmacogenomics to deliver on its promise.

Background: Aminoglycosides are commonly used in cystic fibrosis patients to treat Pseudomonas aeruginosa respiratory infections. Aminoglycoside-induced hearing loss may occur in 1%-15% of patients with cystic fibrosis, ranging from mild to severe. Recently, a genetic test to identify patients with a mitochondrial mutation (A1555G) that may predispose patients to this adverse event has become available. Although the A1555G variant is very rare, it seems to confer a high risk of severe hearing loss in patients exposed to aminoglycosides., Objective: The objective was to evaluate the potential clinical, patient, and economic outcomes associated with the use of A1555G testing in a cystic fibrosis population, and explore data gaps and uncertainty in its clinical implementation., Methods: We developed a decision-analytic model to evaluate a hypothetical cohort of patients with cystic fibrosis from a societal perspective. Clinical and economic data were derived primarily from a critical literature review. The incidence of aminoglycoside-induced severe hearing loss, quality-adjusted life-years, and total health care costs were evaluated. Sensitivity analyses were conducted to evaluate uncertainty in our results., Results: In the base-case analysis, A1555G testing decreased the risk of severe aminoglycoside-induced hearing loss by 0.12% in the cystic fibrosis population. The discounted incremental cost per quality-adjusted life-years gained was $79,300, but varied widely from $33,000 to testing being dominated by the no testing strategy (higher costs and lower quality-adjusted life-years with testing) in sensitivity analyses. If avoidance of aminoglycosides in patients testing positive leads to an absolute increase in the lifetime risk of death from Pseudomonas infection of 0.8% or greater, A1555G testing would lead to a decrease in quality-adjusted life-years., Conclusions: The results of our analysis suggest that there are significant data gaps and uncertainty in the outcomes with A1555G testing, but it is not likely cost-effective, and could lead to worse patient outcomes due to avoidance of first-line therapy in the >95% of patients who are false-positives. Additional research is needed before pharmacogenetic testing for the A1555G mitochondrial mutation can be recommended, even in a population with a high likelihood of exposure to aminoglycosides.

Background: Studies have shown that approximately 80% of hypertensive patients do not take diuretics despite their recommendation as a first-line therapy. A recent study reported that hypertensive patients with the Gly460Trp variant in the alpha-adducin gene are more likely to benefit from diuretic therapy. The objective of this study was to evaluate the potential cost effectiveness of screening for the alpha-adducin Gly460Trp variant among hypertensive patients., Methods: A decision analytic Markov model was developed to estimate the clinical and economic outcomes comparing screening for the Gly460Trp variant to identify patients for addition of a diuretic compared to no screening and no addition of diuretic (usual care) in a hypothetical cohort of treated hypertensive patients not receiving diuretic therapy. We used a lifetime horizon and payer perspective. Cost, utility and epidemiological data were obtained from the literature. One-way, probabilistic, and scenario sensitivity analyses were conducted to evaluate the uncertainty in the results., Results: The screening strategy increased quality adjusted life years (QALYs) by 0.14 (95% confidence range [CR]: 0.05, 0.36) and saved dollar 1834 (dollar 505, dollar 5174) compared to usual care. The most influential input was the strength of the interaction between the alpha-adducin gene variant and diuretic effect., Conclusions: Our results suggest that screening for the alpha-adducin gene variant may be a useful mechanism to identify patients most likely to benefit from diuretic therapy and improve compliance with current treatment guidelines.

Objectives: To determine the potential impact of genetic testing and pharmacogenomics on healthcare delivery and costs., Study Design: Literature review., Methods: We examined 3 examples: (1) BRCA1/2 testing for breast cancer risk, (2) HER2/neu overexpression testing to guide drug treatment in women with breast cancer, and (3) CYP2C9 testing before the use of the anticoagulant warfarin. We discussed each genetic testing example from the perspective of the patient, provider, insurer, industry, government, and society., Results: The expanded use of genetic information offers many potential clinical benefits, but also many economic challenges. One of those challenges will be managing the impact of genetic testing on healthcare delivery and costs., Conclusions: Systematic, evidence-based technology assessments and economic evaluations will have to be used to guide the incorporation of genomics into clinical practice. More research also will be needed to assess patient preferences and willingness to pay for genomic technologies; how providers can assess and use genomic technologies; and how the industry, insurers, and government can best balance the relevant costs and benefits.

Context: Adverse drug reactions are a significant cause of morbidity and mortality. Although many adverse drug reactions are considered nonpreventable, recent developments suggest these reactions may be avoided through individualization of drug therapies based on genetic information, an application known as pharmacogenomics., Objective: To evaluate the potential role of pharmacogenomics in reducing the incidence of adverse drug reactions., Data Sources: MEDLINE English-language only searches for adverse drug reaction studies published between January 1995 and June 2000 and review articles of variant alleles of drug-metabolizing enzymes published between January 1997 and August 2000. We also used online resources, texts, and expert opinion., Study Selection: Detailed inclusion criteria were used to select studies. We included 18 of 333 adverse drug reaction studies and 22 of 61 variant allele review articles., Data Extraction: All the investigators reviewed and coded articles using standardized abstracting forms., Data Synthesis: We identified 27 drugs frequently cited in adverse drug reaction studies. Among these drugs, 59% are metabolized by at least 1 enzyme with a variant allele known to cause poor metabolism. Conversely, only 7% to 22% of randomly selected drugs are known to be metabolized by enzymes with this genetic variability (range, P =.006-P<.001)., Conclusions: Our results suggest that drug therapy based on individuals' genetic makeups may result in a clinically important reduction in adverse outcomes. Our findings serve as a foundation for further research on how pharmacogenomics can reduce the incidence of adverse reactions and on the resulting clinical, societal, and economic implications.

Objective: To review the societal and economic implications of the use of genetic information to individualize drug therapies. Although studies have begun to address the ethical issues raised by the use of genetic information , few have examined the implications of pharmacogenomics f rom the perspective of health services research., Principal Findings: We propose a research agenda for health services research in three areas: (1) to evaluate the effectiveness and cost-effectiveness of pharmacogenomics; (2) to evaluate the effect of pharmacogenomics from the perspective of patients, providers, insurers, industry, and government ; and (3) to evaluate the ethical and societal implications of pharmacogenomics. Throughout the article we use the example of HIV genotyping as an illustration of how genetic technology is disseminated and used., Conclusion: More research is needed on the societal and economic implications of pharmacogenomics to inform the clinical and policy decisions about its use that will be increasingly urgent in the future.

The use of pharmacogenomics to individualize drug therapy offers the potential to improve drug effectiveness, reduce adverse side effects, and provide cost-effective pharmaceutical care. However, the combinations of disease, drug, and genetic test characteristics that will provide clinically useful and economically feasible therapeutic interventions have not been clearly elucidated. The purpose of this paper was to develop a framework for evaluating the potential cost-effectiveness of pharmacogenomic strategies that will help scientists better understand the strategic implications of their research, assist in the design of clinical trials, and provide a guide for health care providers making reimbursement decisions. We reviewed concepts of cost-effectiveness analysis and pharmacogenomics and identified 5 primary characteristics that will enhance the cost-effectiveness of pharmacogenomics: 1) there are severe clinical or economic consequence that are avoided through the use of pharmacogenomics, 2) monitoring drug response using current methods is difficult, 3) a well-established association between genotype and clinical phenotype exists, 4) there is a rapid and relatively inexpensive genetic test, and 5) the variant gene is relatively common. We used this framework to evaluate several examples of pharmacogenomics. We found that pharmacogenomics offers great potential to improve patients' health in a cost-effective manner. However, pharmacogenomics will not be applied to all currently marketed drugs, and careful evaluations are needed on a case-by-case basis before investing resources in research and development of pharmacogenomic-based therapeutics and making reimbursement decisions.