Economic analyses of genetic tests in personalized medicine: clinical utility first, then cost utility

Economic evaluation of genomic/genetic tests: a review and future directions

It has been suggested that health economists need to improve their methods in order to meet the challenges of evaluating genomic/genetic tests. In this article, we set out twelve challenges identified from a rapid review of the literature and suggest solutions to the challenges identified. Two challenges were common to all economic evaluations: choice of perspective and time-horizon. Five challenges were relevant for all diagnostic technologies: complexity of analysis; range of costs; under-developed evidence base; behavioral aspects; and choice of outcome metrics. The final five challenges were pertinent for genomic tests and only these may require methodological development: heterogeneity of tests and platforms, increasing stratification, capturing personal utility; incidental findings; and spillover effects. Current methods of economic evaluation are generally able to cope with genomic/genetic tests, although a renewed focus on specific decision-makers’ needs and a willingness to move away from cost-utility analysis may be required. Certain analysts may be constrained by reference cases developed primarily for the assessment of pharmaceuticals. The combined impact of multiple challenges may require analysts to be particularly careful in setting the scope of their analysis in order to ensure that feasibility is balanced with usefulness to the decision maker. A key issue is the under-developed evidence-base and it may be necessary to rethink translation processes to ensure sufficient, relevant evidence is available to support economic evaluation and adoption of genomic/genetic tests.

Pharmacogenomic testing in paediatrics: clinical implementation strategies

Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited.

As with most paediatric pharmacological studies, there are well‐recognised barriers to obtaining high‐quality PGx evidence, particularly when patient numbers may be small, and off‐label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential.

This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences.

Improving the evidence base demonstrating the clinical utility and cost‐effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.

Projected Cost-Effectiveness for 2 Gene-Drug Pairs Using a Multigene Panel for Patients Undergoing Percutaneous Coronary Intervention

BACKGROUND

For patients undergoing percutaneous coronary intervention, gene-drug associations exist relevant to first-line treatment options-antiplatelet agent, clopidogrel, and pain medication, tramadol. Knowledge of genotype information may allow for avoidance of adverse drug events during critical clinical windows.

OBJECTIVE

This evaluation estimated cost-effectiveness associated with a multi-gene panel pre-emptively testing two genes providing CYP2C19 genotype-guided strategy for antiplatelet therapy, with CYP2D6 genotype-guided pain management, compared to single gene test for CYP2C19 with random assignment for pain treatment, and to no testing (empiric clopidogrel with random assignment for pain treatment).

METHODS

Decision analysis modeling was used to project costs from a payer perspective and patient quality-adjusted life years (QALYs) from the three strategies. The model captured composite risks of major adverse cardiovascular events and pain therapy-related adverse drug events and associated utility estimates. We conducted sensitivity analyses to assess influential input parameters.

RESULTS

Over 15 months, multi-gene testing was least costly and yielded more QALYs compared to both single gene and no testing; total incremental costs were $1646 lower with incremental gains of 0.04 QALYs for multi-gene compared with single gene and $11 368 lower with 0.17 QALY gains compared to no test. Base case analyses revealed multi gene was dominant compared to both single gene and no test, as it demonstrated cost savings with increased QALYs.

CONCLUSIONS

For these patients, a multi-gene-guided strategy yields a favorable incremental cost-effectiveness ratio compared to the other two treatment strategies. Pre-emptively ascertaining additional gene-drug pair information can inform clinical and economic decision-making at the point of care.

The challenges of implementing pharmacogenomic testing in the clinic

INTRODUCTION

Pharmacogenomic testing has the potential to greatly benefit patients by enabling personalization of medication management, ensuring better efficacy and decreasing the risk of side effects. However, to fully realize the potential of pharmacogenomic testing, there are several important issues that must be addressed. Areas covered: In this expert review we discuss current challenges impacting the implementation of pharmacogenomic testing in the clinical practice. We emphasize issues related to testing methods, reporting of the results, test selection, clinical interpretation of the results, cost-effectiveness, and the long-term use of pharmacogenomic results in clinical practice. We identify opportunities and future directions to facilitate clinical implementation. Expert commentary: Several key elements are necessary to optimally integrate pharmacogenomic testing into clinical practice. Collaborative efforts among laboratories are needed to improve standardization of testing and reporting of the results. Clinicians need educational opportunities to improve understanding of which test to order and how to interpret the results. The electronic health records and other clinical systems need to improve their storage of the pharmacogenomics test results and interoperability to facilitate the use of clinically actionable results to improve patient care.

A proposed approach to accelerate evidence generation for genomic-based technologies in the context of a learning health system

Genomic technologies should demonstrate analytical and clinical validity and clinical utility prior to wider adoption in clinical practice. However, the question of clinical utility remains unanswered for many genomic technologies. In this paper, we propose three building blocks for rapid generation of evidence on clinical utility of promising genomic technologies that underpin clinical and policy decisions. We define promising genomic tests as those that have proven analytical and clinical validity. First, risk-sharing agreements could be implemented between payers and manufacturers to enable temporary coverage that would help incorporate promising technologies into routine clinical care. Second, existing data networks, such as the Sentinel Initiative and the National Patient-Centered Clinical Research Network (PCORnet) could be leveraged, augmented with genomic information to track the use of genomic technologies and monitor clinical outcomes in millions of people. Third, endorsement and engagement from key stakeholders will be needed to establish this collaborative model for rapid evidence generation; all stakeholders will benefit from better information regarding the clinical utility of these technologies. This collaborative model can create a multipurpose and reusable national resource that generates knowledge from data gathered as part of routine care to drive evidence-based clinical practice and health system changes.

The Impact of Whole-Genome Sequencing on the Primary Care and Outcomes of Healthy Adult Patients: A Pilot Randomized Trial

Background

Whole-genome sequencing (WGS) in asymptomatic adults might prevent disease but increase health care use without clinical value.

Objective

To describe the effect on clinical care and outcomes of adding WGS to standardized family history assessment in primary care.

Design

Pilot randomized trial. (ClinicalTrials.gov: NCT01736566).

Setting

Academic primary care practices.

Participants

9 primary care physicians (PCPs) and 100 generally healthy patients recruited at ages 40 to 65 years.

Intervention

Patients were randomly assigned to receive a family history report alone (FH group) or in combination with an interpreted WGS report (FH + WGS group), which included monogenic disease risk (MDR) results (associated with Mendelian disorders), carrier variants, pharmacogenomic associations, and polygenic risk estimates for cardiometabolic traits. Each patient met with his or her PCP to discuss the report.

Measurements

Clinical outcomes and health care use through 6 months were obtained from medical records and audio-recorded discussions between PCPs and patients. Patients' health behavior changes were surveyed 6 months after receiving results. A panel of clinician-geneticists rated the appropriateness of how PCPs managed MDR results.

Results

Mean age was 55 years; 58% of patients were female. Eleven FH + WGS patients (22% [95% CI, 12% to 36%]) had new MDR results. Only 2 (4% [CI, 0.01% to 15%]) had evidence of the phenotypes predicted by an MDR result (fundus albipunctatus due to RDH5 and variegate porphyria due to PPOX). Primary care physicians recommended new clinical actions for 16% (CI, 8% to 30%) of FH patients and 34% (CI, 22% to 49%) of FH + WGS patients. Thirty percent (CI, 17% to 45%) and 41% (CI, 27% to 56%) of FH and FH + WGS patients, respectively, reported making a health behavior change after 6 months. Geneticists rated PCP management of 8 MDR results (73% [CI, 39% to 99%]) as appropriate and 2 results (18% [CI, 3% to 52%]) as inappropriate.

Limitation

Limited sample size and ancestral and socioeconomic diversity.

Conclusion

Adding WGS to primary care reveals new molecular findings of uncertain clinical utility. Nongeneticist providers may be able to manage WGS results appropriately, but WGS may prompt additional clinical actions of unclear value.

Primary Funding Source

National Institutes of Health.

The Use of Economic Evaluation to Inform Newborn Screening Policy Decisions: The Washington State Experience

POLICY POINTS

Newborn screening not only saves lives but can also yield net societal economic benefit, in addition to benefits such as improved quality of life to affected individuals and families. Calculations of net economic benefit from newborn screening include the monetary equivalent of avoided deaths and reductions in costs of care for complications associated with late-diagnosed individuals minus the additional costs of screening, diagnosis, and treatment associated with prompt diagnosis. Since 2001 the Washington State Department of Health has successfully implemented an approach to conducting evidence-based economic evaluations of disorders proposed for addition to the state-mandated newborn screening panel.

CONTEXT

Economic evaluations can inform policy decisions on the expansion of newborn screening panels. This article documents the use of cost-benefit models in Washington State as part of the rule-making process that resulted in the implementation of screening for medium-chain acyl-CoA dehydrogenase (MCAD) deficiency and 4 other metabolic disorders in 2004, cystic fibrosis (CF) in 2006, 15 other metabolic disorders in 2008, and severe combined immune deficiency (SCID) in 2014.

METHODS

We reviewed Washington State Department of Health internal reports and spreadsheet models of expected net societal benefit of adding disorders to the state newborn screening panel. We summarize the assumptions and findings for 2 models (MCAD and CF) and discuss them in relation to findings in the peer-reviewed literature.

FINDINGS

The MCAD model projected a benefit-cost ratio of 3.4 to 1 based on assumptions of a 20.0 percentage point reduction in infant mortality and a 13.9 percentage point reduction in serious developmental disability. The CF model projected a benefit-cost ratio of 4.0-5.4 to 1 for a discount rate of 3%-4% and a plausible range of 1-2 percentage point reductions in deaths up to age 10 years.

CONCLUSIONS

The Washington State cost-benefit models of newborn screening were broadly consistent with peer-reviewed literature, and their findings of net benefit appear to be robust to uncertainty in parameters. Public health newborn screening programs can develop their own capacity to project expected costs and benefits of expansion of newborn screening panels, although it would be most efficient if this capacity were shared among programs.

Which BRCA genetic testing programs are ready for implementation in health care? A systematic review of economic evaluations

PURPOSE

There is considerable evidence regarding the efficacy and effectiveness of BRCA genetic testing programs, but whether they represent good use of financial resources is not clear. Therefore, we aimed to identify the main health-care programs for BRCA testing and to evaluate their cost-effectiveness.

METHODS

We performed a systematic review of full economic evaluations of health-care programs involving BRCA testing.

RESULTS

Nine economic evaluations were included, and four main categories of BRCA testing programs were identified: (i) population-based genetic screening of individuals without cancer, either comprehensive or targeted based on ancestry; (ii) family history (FH)-based genetic screening, i.e., testing individuals without cancer but with FH suggestive of BRCA mutation; (iii) familial mutation (FM)-based genetic screening, i.e., testing individuals without cancer but with known familial BRCA mutation; and (iv) cancer-based genetic screening, i.e., testing individuals with BRCA-related cancers.

CONCLUSIONS

Currently BRCA1/2 population-based screening represents good value for the money among Ashkenazi Jews only. FH-based screening is potentially very cost-effective, although further studies that include costs of identifying high-risk women are needed. There is no evidence of cost-effectiveness for BRCA screening of all newly diagnosed cases of breast/ovarian cancers followed by cascade testing of relatives, but programs that include tools for identifying affected women at higher risk for inherited forms are promising. Cost-effectiveness is highly sensitive to the cost of BRCA1/2 testing.Genet Med 18 12, 1171-1180.

Assessing the Costs and Cost-Effectiveness of Genomic Sequencing

Despite dramatic drops in DNA sequencing costs, concerns are great that the integration of genomic sequencing into clinical settings will drastically increase health care expenditures. This commentary presents an overview of what is known about the costs and cost-effectiveness of genomic sequencing. We discuss the cost of germline genomic sequencing, addressing factors that have facilitated the decrease in sequencing costs to date and anticipating the factors that will drive sequencing costs in the future. We then address the cost-effectiveness of diagnostic and pharmacogenomic applications of genomic sequencing, with an emphasis on the implications for secondary findings disclosure and the integration of genomic sequencing into general patient care. Throughout, we ground the discussion by describing efforts in the MedSeq Project, an ongoing randomized controlled clinical trial, to understand the costs and cost-effectiveness of integrating whole genome sequencing into cardiology and primary care settings.

When is Genomic Testing Cost-Effective? Testing for Lynch Syndrome in Patients with Newly-Diagnosed Colorectal Cancer and Their Relatives

Varying estimates of the cost-effectiveness of genomic testing applications can reflect differences in study questions, settings, methods and assumptions. This review compares recently published cost-effectiveness analyses of testing strategies for Lynch Syndrome (LS) in tumors from patients newly diagnosed with colorectal cancer (CRC) for either all adult patients or patients up to age 70 along with cascade testing of relatives of probands. Seven studies published from 2010 through 2015 were identified and summarized. Five studies analyzed the universal offer of testing to adult patients with CRC and two others analyzed testing patients up to age 70; all except one reported incremental cost-effectiveness ratios (ICERs) < $ 100,000 per life-year or quality-adjusted life-year gained. Three studies found lower ICERs for selective testing strategies using family history-based predictive models compared with universal testing. However, those calculations were based on estimates of sensitivity of predictive models derived from research studies, and it is unclear how sensitive such models are in routine clinical practice. Key model parameters that are influential in ICER estimates included 1) the number of first-degree relatives tested per proband identified with LS and 2) the cost of gene sequencing. Others include the frequency of intensive colonoscopic surveillance, the cost of colonoscopy, and the inclusion of extracolonic surveillance and prevention options.

'Someday it will be the norm': physician perspectives on the utility of genome sequencing for patient care in the MedSeq Project

AIM

To describe practicing physicians' perceived clinical utility of genome sequencing.

MATERIALS & METHODS

We conducted a mixed-methods analysis of data from 18 primary care physicians and cardiologists in a study of the clinical integration of whole-genome sequencing. Physicians underwent brief genomics continuing medical education before completing surveys and semi-structured interviews.

RESULTS

Physicians described sequencing as currently lacking clinical utility because of its uncertain interpretation and limited impact on clinical decision-making, but they expressed the idea that its clinical integration was inevitable. Potential clinical uses for sequencing included complementing other clinical information, risk stratification, motivating patient behavior change and pharmacogenetics.

CONCLUSION

Physicians given genomics continuing medical education use the language of both evidence-based and personalized medicine in describing the utility of genome-wide testing in patient care.

Personalized Medicine's Bottleneck: Diagnostic Test Evidence and Reimbursement

Background: Personalized medicine is gradually emerging as a transformative field. Thus far, seven co-developed drug-diagnostic combinations have been approved and several dozen post-hoc drug-diagnostic combinations (diagnostic approved after the drug). However, barriers remain, particularly with respect to reimbursement. Purpose, methods: This study analyzes barriers facing uptake of drug-diagnostic combinations. We examine Medicare reimbursement in the U.S. of 10 drug-diagnostic combinations on the basis of a formulary review and a survey. Findings: We found that payers reimburse all 10 drugs, but with variable and relatively high patient co-insurance, as well as imposition of formulary restrictions. Payer reimbursement of companion diagnostics is limited and highly variable. In addition, we found that the body of evidence on the clinical- and cost-effectiveness of therapeutics is thin and even less robust for diagnostics. Conclusions, discussion: The high cost of personalized therapeutics and dearth of evidence concerning the comparative clinical effectiveness of drug-diagnostic combinations appear to contribute to high patient cost sharing, imposition of formulary restrictions, and limited and variable reimbursement of companion diagnostics. Our findings point to the need to increase the evidence base supportive of establishing linkage between diagnostic testing and positive health outcomes.