An introduction to cost-effectiveness and cost-benefit analysis of pharmacogenomics

A cost-benefit analysis of genetic screening test for breast cancer in Iran

BACKGROUND

This study aimed to evaluate the implementation of the population- and family history (FH) -based screening for BReast CAncer (BRCA) in Iran, a country where less than 10% of breast cancer cases are attributable to a gene mutation.

METHODS

This was an economic evaluation study. The Benefit-Cost Ratio (BCR) for genetic screening test strategies in Iranian women older than 30 was calculated. To this end, the monetary value of the test was estimated using the willingness-to-pay (WTP) approach using the contingent valuation method (CVM) by payment card. From a healthcare perspective, direct medical and non-medical costs were considered and a decision model for the strategies was developed to simulate the costs. A one-way sensitivity analysis assessed the robustness of the analysis. The data were analyzed using Excel 2010.

RESULTS

660 women were included for estimating WTP and 2,176,919 women were considered in the costing model. The cost per genetic screening test for population- and FH-based strategies was $167 and $8, respectively. The monetary value of a genetic screening test was $20 and it was $27 for women with a family history or gene mutation in breast cancer. The BCR for population-based and FH-based screening strategies was 0.12 and 3.37, respectively. Sensitivity analyses confirmed the robustness of the results.

CONCLUSIONS

This study recommends the implementation of a FH-based strategy instead of a population-based genetic screening strategy in Iran, although a cascade genetic screening test strategy should be evaluated in future studies.

Polypharmacy in chronic kidney disease: Health outcomes & pharmacy-based strategies to mitigate inappropriate polypharmacy

The rising prevalence of comorbidities in an increasingly aging population has sparked a reciprocal rise in polypharmacy. Patients with chronic kidney disease (CKD) have a greater burden of polypharmacy due to the comorbidities and complications associated with their disease. Polypharmacy in CKD patients has been linked to myriad direct and indirect costs for patients and the society at large. Pharmacists are uniquely positioned within the healthcare team to streamline polypharmacy management in the setting of CKD. In this article, we review the landscape of polypharmacy and examine its impacts through the lens of the ECHO model of Economic, Clinical, and Humanistic Outcomes. We also present strategies for healthcare teams to improve polypharmacy care through comprehensive medication management process that includes medication reconciliation during transitions of care, medication therapy management, and deprescribing. These pharmacist-led interventions have the potential to mitigate adverse outcomes associated with polypharmacy in CKD.

Population or family history based BRCA gene tests of breast cancer? A systematic review of economic evaluations

BACKGROUND

Nearly 56% of at-risk carriers are not identified and missed as a result of the current family-history (FH) screening for genetic testing. The present study aims to review the economic evaluation studies on BRCA genetic testing strategies for screening and early detection of breast cancer.

METHODS

This systematic literature review is conducted within the Cochrane Library, PubMed, Scopus, Web of Science, ProQuest, and EMBASE databases. In this paper, the relevant published economic evaluation studies are identified by following the standard Cochrane Collaboration methods and adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement reporting some recommendations for articles up to March 2020. Thereafter, the inclusion and exclusion criteria are applied to screen the articles. Disagreements are resolved through a consensus meeting. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist is used in the evaluation of quality. Finally, a narrative synthesis is performed. To compare the different levels of incremental cost-effectiveness ratio (ICER), the net present value is calculated based on a discount rate of 3% in 2019.

RESULTS

Among 788 initially retrieved citations, 12 studies were included. More than 60% of the studies were originated from high-income countries and were published after 2016. It is noteworthy that most of the studies evaluated the payer perspective. Moreover, the robustness of the results were analyzed through one-way and probabilistic sensitivity analyses in nearly 66% of these studies. Nearly, 25% of the studies are focused and defined population-based and family history BRCA tests as comparators; afterwards, the cost-effectiveness of the former was confirmed. The highest and lowest absolute values for the ICERs were $65,661 and $9 per quality adjusted life years, respectively. All studies met over 70% of the CHEERs criteria checklist, which was considered as 93% of high quality on average as well.

CONCLUSIONS

The genetic BRCA tests for the general population as well as unselected breast cancer patients were cost-effective in high and upper-middle income countries and those with prevalence of gene mutation while population-based genetic tests for low-middle income countries are depended on the price of the tests.

Prevalence of polypharmacy and associated adverse health outcomes in adult patients with chronic kidney disease: protocol for a systematic review and meta-analysis

BACKGROUND

Polypharmacy, often defined as the concomitant use of ≥ 5 medications, has been identified as a significant global public health threat. Aging and multimorbidity are key drivers of polypharmacy and have been linked to a broad range of adverse health outcomes and mortality. Patients with chronic kidney disease (CKD) are particularly at high risk of polypharmacy and use of potentially inappropriate medications given the numerous risk factors and complications associated with CKD. The aim of this systematic review will be to assess the prevalence of polypharmacy among adult patients with CKD, and the potential association between polypharmacy and adverse health outcomes within this population.

METHODS/DESIGN

We will search empirical databases such as MEDLINE, Embase, Cochrane Library, CINAHL, Web of Science, and PsycINFO and grey literature from inception onwards (with no language restrictions) for observational studies (e.g., cross-sectional or cohort studies) reporting the prevalence of polypharmacy in adult patients with CKD (all stages including dialysis). Two reviewers will independently screen all citations, full-text articles, and extract data. Potential conflicts will be resolved through discussion. The study methodological quality will be appraised using an appropriate tool. The primary outcome will be the prevalence of polypharmacy. Secondary outcomes will include any adverse health outcomes (e.g., worsening kidney function) in association with polypharmacy. If appropriate, we will conduct random effects meta-analysis of observational data to summarize the pooled prevalence of polypharmacy and the associations between polypharmacy and adverse outcomes. Statistical heterogeneity will be estimated using Cochran's Q and I2 index. Additional analyses will be conducted to explore the potential sources of heterogeneity (e.g., sex, kidney replacement therapy, multimorbidity).

DISCUSSION

Given that polypharmacy is a major and a growing public health issue, our findings will highlight the prevalence of polypharmacy, hazards associated with it, and medication thresholds associated with adverse outcomes in patients with CKD. Our study will also draw attention to the prognostic importance of improving medication practices as a key priority area to help minimize the use of inappropriate medications in patients with CKD.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number: [ CRD42020206514 ].

Bridging the Gaps in Personalized Medicine Value Assessment: A Review of the Need for Outcome Metrics across Stakeholders and Scientific Disciplines

Despite monumental advances in genomics, relatively few health care provider organizations in the United States offer personalized or precision medicine as part of the routine clinical workflow. The gaps between research and applied genomic medicine may be a result of a cultural gap across various stakeholders representing scientists, clinicians, patients, policy makers, and third party payers. Scientists are trained to assess the health care value of genomics by either quantifying population-scale effects, or through the narrow lens of clinical trials where the standard of care is compared with the predictive power of a single or handful of genetic variants. While these metrics are an essential first step in assessing and documenting the clinical utility of genomics, they are rarely followed up with other assessments of health care value that are critical to stakeholders who use different measures to define value. The limited value assessment in both the research and implementation science of precision medicine is likely due to necessary logistical constraints of these teams; engaging bioethicists, health care economists, and individual patient belief systems is incredibly daunting for geneticists and informaticians conducting research. In this narrative review, we concisely describe several definitions of value through various stakeholder viewpoints. We highlight the existing gaps that prevent clinical translation of scientific findings generally as well as more specifically using two present-day, extreme scenarios: (1) genetically guided warfarin dosing representing a handful of genetic markers and more than 10 years of basic and translational research, and (2) next-generation sequencing representing genome-dense data lacking substantial evidence for implementation. These contemporary scenarios highlight the need for various stakeholders to broadly adopt frameworks designed to define and collect multiple value measures across different disciplines to ultimately impact more universal acceptance of and reimbursement for genomic medicine.

Using Cost-Effectiveness Analysis to Quantify the Value of Genomic-Based Diagnostic Tests: Recommendations for Practice and Research

AIMS

New sequencing technologies allow increased opportunities to use genomic-based diagnostic tests (genomic tests) in routine clinical practice, which will impact healthcare budgets and patients' outcomes. This article aims to generate a list of recommendations on how the principles and methods of cost-effectiveness analysis (CEA) can be used to quantify the costs and benefits of genomic tests.

METHODS

A systematic literature search identified publications describing the use of CEA to evaluate genomic tests. Data were extracted as key concepts to produce a thematic list of previously described challenges and solutions to using CEA to evaluate genomic tests. Defining features of evaluating genomic tests were categorized into a list of key recommendations for applying methods in practice and for research needs.

RESULTS

Features producing challenges in the implementation of CEA to evaluate genomic tests were as follows: the ability of the tests to diagnose multiple disorders; potential consequences for future generations suggesting an infinite time horizon; and the potential need to consider nonhealth benefits.

CONCLUSIONS

CEA was identified as an appropriate evaluative framework for genomic tests, although standard methods may need modification and important method research questions remain. Key recommendations suggest a need for research to reflect: sharing genomic information across generations; genomic tests for multiple disorders; and health and nonhealth benefits.

A model to assess the cost–effectiveness of pharmacogenomics tests in chronic heart failure: the case of ivabradine

Pharmacogenomics (PGx) tests have the potential of improving the effectiveness of expensive new drugs by predicting the likelihood, for a particular patient, to respond to a treatment. The objective of this study was to develop a pharmacoeconomic model to determine the characteristics and the cost–effectiveness of a hypothetical PGx test, which would identify patients who are most likely to respond to an expensive treatment for chronic heart failure. For this purpose, we chose the example of ivabradine. Our results suggest that the use of a PGx test that could select a subgroup of patients to be treated with an expensive drug has the potential to provide more efficient drug utilization.

Welfarism versus extra-welfarism: can the choice of economic evaluation approach impact on the adoption decisions recommended by economic evaluation studies?

A long-running debate surrounds the equivalence of the welfarist and extra-welfarist approaches to economic evaluation. There is a growing belief that the extra-welfarist approach may not necessarily provide all the information that decisionmakers require in certain contexts, e.g. evaluation of complex interventions. As the number of these interventions being evaluated increases, it is crucial that the most appropriate economic evaluation approach is used to enable decisionmakers to be confident in their adoption decisions. We conducted a literature review to evaluate the potential for the choice of economic evaluation approach to impact on the adoption decisions recommended by economic evaluation studies. We found that for every five studies applying both approaches, one shows limited or no concordance in economic evaluation results: the different approaches suggest conflicting adoption decisions, and there is no pattern to which approach provides the most convincing adoption evidence. Only one study in ten indicates which results will best inform adoption decisions. We conclude that the choice of approach can significantly impact on the adoption decisions recommended by economic evaluation studies, with conflicting results creating confusion over whether or not interventions provide good value for money. Health economists rarely provide sufficient guidance to decisionmakers to alleviate this confusion.

Economic Perspectives on Personalized Health Care and Prevention

The objective of this paper is to provide an overview of economic evaluation of personalized medicine, focusing particularly on the use of cost-effectiveness analysis and other methods of valuation. We draw on insights from the literature and our work at the University of California, San Francisco Center for Translational and Policy Research on Personalized Medicine (TRANSPERS). We begin with a discussion of why personalized medicine is of interest and challenges to adoption, whether personalized medicine is different enough to require different evaluation approaches, and what is known about the economics of personalized medicine. We then discuss insights from TRANSPERS research and six areas for future research: Develop and Apply Multiple Methods of Assessing Value Identify Key Factors in Determining the Value of Personalized Medicine Use Real World Perspectives in Economic Analyses Consider Patient Heterogeneity and Diverse Populations in Economic Analyses Prepare for Upcoming Challenges of Assessing Value of Emerging Technologies Incorporate Behavioral Economics into Value Assessments.

Higher frequency of genetic variants conferring increased risk for ADRs for commonly used drugs treating cancer, AIDS and tuberculosis in persons of African descent

There is established clinical evidence for differences in drug response, cure rates and survival outcomes between different ethnic populations, but the causes are poorly understood. Differences in frequencies of functional genetic variants in key drug response and metabolism genes may significantly influence drug response differences in different populations. To assess this, we genotyped 1330 individuals of African (n=372) and European (n=958) descent for 4535 single-nucleotide polymorphisms in 350 key drug absorption, distribution, metabolism, elimination and toxicity genes. Important and remarkable differences in the distribution of genetic variants were observed between Africans and Europeans and among the African populations. These could translate into significant differences in drug efficacy and safety profiles, and also in the required dose to achieve the desired therapeutic effect in different populations. Our data points to the need for population-specific genetic variation in personalizing medicine and care.

Pharmacogenomics and public health: implementing 'populationalized' medicine

Pharmacogenomics are frequently considered in personalized medicine to maximize therapeutic benefits and minimize adverse drug reactions. However, there is a movement towards applying this technology to populations, which may produce the same benefits, while saving already scarce health resources. We conducted a narrative literature review to examine how pharmacogenomics and public health can constructively intersect, particularly in resource-poor settings. We identified 27 articles addressing the research question. Real and theoretical connections between public health and pharmacogenomics were presented in the areas of disease, drugs and public policy. Suggested points for consideration, such as educational efforts and cultural acceptability, were also provided. Including pharmacogenomics in public health can result in both health-related and economic benefits. Including pharmacogenomics in public health holds promise but deserves extensive consideration. To fully realize the benefits of this technology, support is needed from private, public and governmental sectors in order to ensure the appropriateness within a society.

Pharmacogenomics and active surveillance for serious adverse drug reactions in children

Juxtaposing clinical pharmacology with human genetics, pharmacogenomics utilizes a patient’s genetic information to identify genetic variants that have the potential to provide clinically relevant predictions of toxicity and efficacy. The goal is to develop personalized and genetic-based predictions of an individual’s drug response and likelihood of experiencing an adverse drug reaction. The Canadian Pharmacogenomics Network for Drug Safety (CPNDS) has implemented active adverse drug reaction surveillance to monitor and discover genetic markers related to serious adverse drug reactions in the pediatric population. Evidence-based pharmacogenomics research will inform public policy and influence drug benefit–risk decision-making. Regulatory processes and future challenges in pharmacogenomics research will be discussed.

Economic opportunities and challenges for pharmacogenomics

Economic evaluation provides health care decision makers with a powerful tool for resource allocation decisions because it offers a framework for comparing the costs and benefits of competing interventions or options. This paper reviews how economic analyses have been applied to the field of pharmacogenomics, both by the pharmaceutical industry to inform investment decisions and by payers to make coverage decisions. There is much anticipation that pharmacogenomic testing is likely to be cost-effective because it uses genomic information to improve drug effectiveness and reduce toxicity both in the drug development process and at the bedside. However, the demonstration of economic benefits first requires that pharmacogenomic testing show evidence of clinical effectiveness. This will only be achieved by greater participation of pharmacogenomics experts in comparative effectiveness research and additional emphasis on including costs in the determination of the relative value of pharmacogenomic testing to the health care system.

A health services research agenda for cellular, molecular and genomic technologies in cancer care

BACKGROUND

In recent decades, extensive resources have been invested to develop cellular, molecular and genomic technologies with clinical applications that span the continuum of cancer care.

METHODS

In December 2006, the National Cancer Institute sponsored the first workshop to uniquely examine the state of health services research on cancer-related cellular, molecular and genomic technologies and identify challenges and priorities for expanding the evidence base on their effectiveness in routine care.

RESULTS

This article summarizes the workshop outcomes, which included development of a comprehensive research agenda that incorporates health and safety endpoints, utilization patterns, patient and provider preferences, quality of care and access, disparities, economics and decision modeling, trends in cancer outcomes, and health-related quality of life among target populations.

CONCLUSIONS

Ultimately, the successful adoption of useful technologies will depend on understanding and influencing the patient, provider, health care system and societal factors that contribute to their uptake and effectiveness in 'real-world' settings.

Genotypic Approaches to Therapy in Children: A National Active Surveillance Network (GATC) to Study the Pharmacogenomics of Severe Adverse Drug Reactions in Children

A striking failure of modern medicine is the debilitating and lethal consequences of adverse drug reactions (ADRs), which rank as one of the top 10 leading causes of death and illness in the developed world with direct medical costs of 137-177 billion annually US dollars in the USA. Although many factors influence the effect of medications (e.g., age, organ function, drug interactions), genetic factors account for 20% to 95% of drug response variability and play a significant role in the incidence and severity of ADRs. The field of pharmacogenomics seeks to identify genetic factors responsible for individual differences in drug efficacy and ADRs. Pharmacogenomics has led to several genetic tests that provide clinical dosing recommendations. The Genetic Approaches to Therapy in Children (GATC) project is a national project established in Canada to identify novel predictive genomic markers for severe ADRs in children. An ADR surveillance network has been established in eight of Canada's major children's hospitals, serving up to 75% of all Canadian children. The goal of the project is to identify patients experiencing specific ADRs and matched controls, collect DNA samples, and apply genomics-based technologies to identify ADR-associated genetic markers with the goal of preventing serious ADRs in susceptible children.

Valuing personalized medicine: willingness to pay for genetic testing for colorectal cancer risk

Objectives: Personalized medicine using genetic information is increasing in cancer screening and treatment; however, little is known about perceived value of genetic testing for cancer risk in a general population. The objectives of this report are: to identify a general population’s willingness to pay for genetic testing that provids colorectal cancer risk information; examine whether screening intentions (likelihood of testing and test choice) change based on risk; and identify providers’ beliefs about patients’ perceived value. Methods: A survey of US general (n = 1087) and physician (n = 100) populations using the willingness-to-pay method was carried out. Physicians responded from the perspective of a typical patient. χ2 tests, t-tests and ordered logistic regression were used to examine factors associated with willingness to pay and intentions to be screened. Results: General population respondents’ average willingness to pay for a genetic test for colorectal cancer risk was US$150. Higher willingness to pay was significantly associated with being male, having higher income and education, having private health insurance and reporting a greater likelihood of getting colorectal cancer screening when due. Physicians’ beliefs about patients were different than general population responses: physicians believed patients would be willing to pay more (US$212; p < 0.001), fewer believed patients would not pay (1 vs 17%; p<0.001), and if a genetic test indicated higher than average risk, physicians believed patients would be more likely to get screened (65 vs 46%; p < 0.001) and would choose alternative screening tests (62 vs 22%; p < 0.001). Conclusion: Respondents valued genetic tests to inform screening decisions and indicated that tests may influence screening choices. Additional studies are needed to examine the implications of physicians’ beliefs about patients’ choices for screening.

Pharmacogenomics and its implications for autoimmune disease

A striking failure of modern medicine is the debilitating and lethal consequences of adverse drug reactions (ADRs) which rank as one of the top ten leading causes of death and illness in the developed world with direct medical costs of 137-177 billion US dollars annually in the USA. Although many factors influence the effect of medications (i.e. age, organ function, drug interactions), genetic factors account for 20-95% of drug response variability and play a significant role in the incidence and severity of ADRs. The field of pharmacogenomics seeks to identify genetic factors responsible for individual differences in drug efficacy and adverse drug reactions. Pharmacogenomics has led to several genetic tests that provide clinical dosing recommendations. For autoimmune disease, pharmacogenomics has led to several DNA-based tests to improve drug selection, optimize dosing, and minimize the risk of toxicity. The 'GATC' project is a nation-wide project established in Canada to identify novel predictive genomic markers of severe ADRs in children. An ADR surveillance network has been established in all of Canada's major children's hospitals, serving up to 75% of all Canadian children. The goal of the project is to identify patients experiencing specific ADRs, collect DNA samples, and apply genomics-based technologies to identify ADR-associated genetic markers.

A framework to evaluate the economic impact of pharmacogenomics

INTRODUCTION

Pharmacogenomics and personalized medicine promise to improve healthcare by increasing drug efficacy and minimizing side effects. There may also be substantial savings realized by eliminating costs associated with failed treatment. This paper describes a framework using health claims data for analyzing the potential value of pharmacogenomic testing in clinical practice.

METHODS

We evaluated a model of alternate clinical strategies using asthma patients' data from a retrospective health claims database to determine a potential cost offset. We estimated the likely cost impact of using a hypothetical pharmacogenomic test to determine a preferred initial therapy. We compared the annualized per patient costs distributions under two clinical strategies: testing all patients for a nonresponse genotype prior to treating and testing none.

RESULTS

In the Test All strategy, more patients fall into lower cost ranges of the distribution. In our base case (15% phenotype prevalence, 200 US dollars test, 74% overall first-line treatment efficacy and 60% second-line therapy efficacy) the cost savings per patient for a typical run of the testing strategy simulation ranged from 200 US dollars to 767 US dollars (5th and 95th percentile). Genetic variant prevalence, test cost and the cost of choosing the wrong treatment are key parameters in the economic viability of pharmacogenomics in clinical practice.

CONCLUSIONS

A general tool for predicting the impact of pharmacogenomic-based diagnostic tests on healthcare costs in asthma patients suggests that upfront testing costs are likely offset by avoided nonresponse costs. We suggest that similar analyses for decision making could be undertaken using claims data in which a population can be stratified by response to a drug.

Cost-effectiveness of pharmacogenomics in clinical practice: a case study of thiopurine methyltransferase genotyping in acute lymphoblastic leukemia in Europe

Only a few studies have addressed the cost-effectiveness of pharmacogenetics interventions in healthcare. Lack of health economics data on aspects of pharmacogenetics is perceived as one of the barriers hindering its implementation for improving drug safety. Thus, a recent Institute for Prospective Technological Studies (IPTS) study, entitled 'Pharmacogenetics and pharmacogenomics: state-of-the-art and potential socio-economic impact in the EU' included an explorative cost-effectiveness review for a pharmacogenetic treatment strategy compared with traditional medical practice. The selected case study examined the cost-effectiveness of thiopurine methyltransferase (TMPT) genotyping prior to thiopurine treatment in children with acute lymphoblastic leukemia (ALL). Information for the cost-effectiveness model parameters was collected from literature surveys and interviews with experts from four European countries (Germany, Ireland, the Netherlands and the UK). The model has established that TPMT testing in ALL patients has a favorable cost-effectiveness ratio. This conclusion was based on parameters collected for TPMT genotyping costs, estimates for frequency of TMPT deficiency, rates of thiopurine-mediated myelosuppression in TPMT-deficient individuals, and myelosuppression-related hospitalization costs in each of the four countries studied. The mean calculated cost per life-year gained by TPMT genotyping in ALL patients in the four study countries was euro 2100 (or euro 4800 after 3% discount) based on genotyping costs of euro 150 per patient. Cost per life-year gained is expected to further improve following the introduction of the wider use of TMPT genotyping and the availability of lower cost genotyping methods. Our analysis indicates that TPMT genotyping should be seriously considered as an integral part of healthcare prior to the initiation of therapy with thiopurine drugs.

Regulatory perspectives on pharmacogenomics: a review of the literature on key issues faced by the United States Food and Drug Administration

Pharmacogenomics (PGx), the use of genetic information to individualize drug therapy, is an immediate and important application of the Human Genome Project. The advent of PGx presents challenges to the U.S. Food and Drug Administration (FDA) in pursuing its mandate of protecting public health and safety. The authors conducted a review of academic, industry, and government literature using a technology diffusion framework to identify issues faced by the FDA relevant to the application of PGx. Two hundred and ten articles were reviewed. Key issues were categorized as rationale and structure for PGx regulation, regulation of PGx-based testing technologies, regulation of applications in clinical settings, regulation of data, and regulation of product life cycles. This review identifies issues faced by the FDA with respect to PGx, which the FDA is addressing through several initiatives. It also illustrates the complex issues involved in developing, implementing, and adopting new technologies.

Diagnostics and biomarker development: priming the pipeline

The decrease in the rate at which novel medical products are reaching the market, despite major scientific achievements and investment that might have predicted otherwise, is causing much concern. Although this 'pipeline problem' has often been discussed in the context of drug development, it is also crucial to examine the unique characteristics of the pipeline for biomarkers and diagnostics. Here, we characterize the pipeline problem for biomarkers and diagnostics, and consider what steps could be taken to solve it.

Cost-effectiveness analysis of genetic testing for familial long QT syndrome in symptomatic index cases

BACKGROUND

Genetic testing for long QT syndrome (LQTS) has been available in a research setting for the past decade, and a commercial test has recently become available. However, the costs and effectiveness of genetic testing have not been estimated.

OBJECTIVES

The purpose of this study was to conduct a cost-effectiveness analysis of genetic testing in the management of patients who have or are suspected to have familial LQTS.

METHODS

We examined the incremental cost-effectiveness of genetic testing compared with no genetic testing for symptomatic index cases and how this varied according to changes in assumptions and data inputs. Data were obtained from the published literature and a clinical cohort.

RESULTS

We found that genetic testing is more cost-effective than not testing for symptomatic index cases at an estimated cost of 2,500 US dollar per year of life saved. These results were generally robust, although they were sensitive to some data inputs such as the cost of testing and the mortality rate among untreated individuals with LQTS.

CONCLUSION

A genetic test for familial LQTS is cost-effective relative to no testing, given our assumptions about the population to be tested and the relevant probabilities and costs. The primary benefit of testing is to more accurately diagnose and treat individuals based on a combination of clinical scores and test results. Future economic analyses of testing for familial LQTS should consider the potential benefits of genetic testing of broader populations, including family members.

HLA-B genotyping to detect carbamazepine-induced Stevens-Johnson syndrome: implications for personalizing medicine

Preventing severe adverse drug reactions by identifying people at risk with a simple genetic test is the goal of many pharmacogenomic studies. Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are related, life-threatening cutaneous adverse reactions, most often caused by medication. The overall incidence and the commonly offending drugs vary among different ethnic populations. Susceptibility to such idiosyncratic reactions is thought to be genetically determined and immune mediated. Finding a strong genetic association between a particular human leukocyte antigen (HLA)-B allele and the reaction to a specific drug provides evidence that the pathogenesis of the severe cutaneous adverse drug reactions involves major histocompatibility complex-restricted presentation of a drug or its metabolites for T-cell activation. In the case of carbamazepine-induced SJS/TEN, the tight association of the HLA-B*1502 allele (sensitivity 100%, specificity 97% and odds ratio 2504) provides a plausible basis for further development of such a test to identify individuals at risk of developing this life-threatening condition.

Measuring the value of pharmacogenomics

Pharmacogenetics and pharmacogenomics offer the potential of developing DNA-based tests to help maximize drug efficacy and enhance drug safety. Major scientific advances in this field have brought us to the point where such tests are poised to enter more widespread clinical use. However, many questions have been raised about whether such tests will be of significant value, and how to assess this. Here, we review the application of economics-based resource-allocation frameworks to assess the value of pharmacogenomics, and the findings so far. We then develop a resource-allocation framework for assessing the potential value of pharmacogenomic testing from a population perspective, and apply this framework to the example of testing for variant alleles of CYP2D6, an important drug-metabolizing enzyme. This review provides a framework for analysing the value of pharmacogenomic interventions, and suggests where further research and development could be most beneficial.

Personalized medicine: how much can we afford? A bioethics perspective

This article examines some major challenges to the clinical implementation of personalized medicine from a bioethics point of view. Challenges arise from the need to choose between competing scenarios in the allocation of healthcare resources. If a choice between competing scenarios must be made, the key question is what sort of medicine a society wants to have and how much its citizens are willing to pay for it. Cost-effectiveness is crucial, but not the only criterium. Pharmacogenomics-based personalized medicine is also challenged by competing concepts of 'good' medicine. However, a real dilemma for health policy arises when a trade-off between implementing public health practices and personalized medicine must be made. This paper tries to show that from a bioethics perspective these concepts are not mutually exclusive. In future, a scenario that seeks to integrate both concepts in a complementary fashion may maximize the benefit for both individuals and the community.

Cost-effectiveness analysis of HLA B*5701 genotyping in preventing abacavir hypersensitivity

OBJECTIVE

Abacavir, a human immunodeficiency virus-1 (HIV-1) nucleoside-analogue reverse transcriptase inhibitor, causes severe hypersensitivity in 4-8% of patients. HLA B*5701 is a known genetic risk factor for abacavir hypersensitivity in Caucasians. Our aim was to confirm the presence of this genetic factor in our patients, and to determine whether genotyping for HLA B*5701 would be a cost-effective use of healthcare resources.

METHODS

Patients with and without abacavir hypersensitivity were identified from a UK HIV clinic. Patients were genotyped for HLA B*5701, and pooled data used for calculation of test characteristics. The cost-effectiveness analysis incorporated the cost of testing, cost of treating abacavir hypersensitivity, and the cost and selection of alternative antiretroviral regimens. A probabilistic decision analytic model (comparing testing versus no testing) was formulated and Monte Carlo simulations performed.

RESULTS

Of the abacavir hypersensitive patients, six (46%) were HLA B*5701 positive, compared to five (10%) of the non-hypersensitive patients (odds ratio 7.9 [95% confidence intervals 1.5-41.4], P = 0.006). Pooling of our data on HLA B*5701 with published data resulted in a pooled odds ratio of 29 (95% CI 6.4-132.3; P < 0.0001). The cost-effectiveness model demonstrated that depending on the choice of comparator, routine testing for HLA B*5701 ranged from being a dominant strategy (less expensive and more beneficial than not testing) to an incremental cost-effectiveness ratio (versus no testing) of Euro 22,811 per hypersensitivity reaction avoided.

CONCLUSIONS

Abacavir hypersensitivity is associated with HLA B*5701, and pre-prescription pharmacogenetic testing for this appears to be a cost-effective use of healthcare resources.

A systematic review of cost-effectiveness analyses of pharmacogenomic interventions

Cost-effectiveness analysis is a widely used tool to assess the value of healthcare interventions. Our objective was to conduct a systematic review of the literature on the cost effectiveness of pharmacogenomic interventions. We found 11 studies that met our inclusion criteria. The most commonly examined disease was deep vein thrombosis (n = 4), followed by cancer (n = 3) and viral infections (n = 3); the most frequently examined mutation was factor V Leiden (n = 5); and the majority of the mutations examined were inherited mutations (n = 7), although several studies looked at acquired (tumor or viral) mutations (n = 4). The majority of the studies reported a favorable cost-effectiveness ratio for the pharmacogenomic-based strategy (n = 7), while two studies reported that the pharmacogenomic-based strategy was not cost effective and two were equivocal. We conclude that there have been few evaluations of the economic costs and benefits of pharmacogenomic interventions and they have covered a limited number of conditions. Further analyses that can be used to guide the use of pharmacogenomics in clinical practice and in developing health policies are urgently needed.

Criteria influencing the clinical uptake of pharmacogenomic strategies

Pharmacogenomics and related genomic technologies may hold the potential to improve efficacy and safety in prescription, but complex factors affect their clinical success