Issues surrounding the health economic evaluation of genomic technologies

Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework

INTRODUCTION

Genomic medicine has features that make it preference sensitive and amenable to model-based health economic evaluation. Preferences of patients, caregivers, and clinicians related to the uptake and delivery of genomic medicine technologies and services that are not captured in health state utility weights can affect the intervention's cost-effectiveness and budget impact. However, there is currently no established or agreed-on approach for integrating preference information into economic evaluations. The objective of this study was to explore approaches for incorporating preferences into model-based economic evaluations of genomic medicine and to develop a conceptual framework to consider preferences in health economic models.

METHODS

We conducted a critical interpretive synthesis of published literature guided by the following question: how have preferences been incorporated into model-based economic evaluations of genomic medicine interventions? We integrated findings from the literature and expert opinion to develop a conceptual framework of ways in which preferences influence economic value in the context of genomic medicine.

RESULTS

Our synthesis included 14 articles. Revealed and stated preference data were used to estimate choice probabilities and to value outcomes. Our conceptual framework situates preference data in the context of health system, patient, clinician, and family characteristics. Preference data were sourced from clinicians, patients and families impacted by a condition or intervention, and the general public. Evaluations employed various types of models, including discrete event simulation, microsimulation, Markov, and decision tree models.

CONCLUSION

When evaluating the broad benefits and costs of implementing new interventions, sufficiently accounting for preferences in the form of model inputs and valuation of outcomes in economic evaluations is important to avoid biased implementation decisions. Incorporation of preference data may improve alignment between predicted and real-world uptake and more accurately estimate welfare impacts, and this study provides critical insights to support researchers who seek to incorporate preference information into model-based health economic evaluations.

The Concept of Personal Utility in Genomic Testing: Three Ethical Tensions

Health Technology Assessment (HTA) has traditionally focused on efficacy, safety, and cost-effectiveness. There has long been concern, however, that this is determined by the goals of healthcare providers/payers, not patients. As a result, HTA arguably fails to reflect the overall value of health technologies-including their "non-clinical" or "personal" utility to patients and their families. The use of genomic testing in clinical care is one domain where this problem is evident, as the personal utility of results is often especially significant. As such, there are growing calls for HTA frameworks to adopt personal utility as a distinct element of value when assessing clinical genomic tests. We agree that personal utility is important to HTA in clinical genomics. However, against a trend toward comprehensive conceptions of personal utility within HTA, we advocate for a restrictive approach to assessing the value of personal utility in the case of clinical genomic testing.

Next-generation sequencing in oncology: challenges in economic evaluations

INTRODUCTION

Next-generation sequencing (NGS) identifies genetic variants to inform personalized treatment plans. Insufficient evidence of cost-effectiveness impedes the integration of NGS into routine cancer care. The complexity of personalized treatment challenges conventional economic evaluation. Clearly delineating challenges informs future cost-effectiveness analyses to better value and contextualize health, preference-, and equity-based outcomes.

AREAS COVERED

We conducted a scoping review to characterize the applied methods and outcomes of economic evaluations of NGS in oncology and identify existing challenges. We included 27 articles published since 2016 from a search of PubMed, Embase, and Web of Science. Identified challenges included defining the evaluative scope, managing evidentiary limitations including lack of causal evidence, incorporating preference-based utility, and assessing distributional and equity-based impacts. These challenges reflect the difficulty of generating high-quality clinical effectiveness and real-world evidence (RWE) for NGS-guided interventions.

EXPERT OPINION

Adapting methodological approaches and developing life-cycle health technology assessment (HTA) guidance using RWE is crucial for implementing NGS in oncology. Healthcare systems, decision-makers, and HTA organizations are facing a pivotal opportunity to adapt to an evolving clinical paradigm and create innovative regulatory and reimbursement processes that will enable more sustainable, equitable, and patient-oriented healthcare.

Scenario analysis and multi-criteria decision analysis to explore alternative reimbursement pathways for whole genome sequencing for blood cancer patients

BACKGROUND

Whole genome sequencing (WGS) has transformative potential for blood cancer management, but reimbursement is hindered by uncertain benefits relative to added costs. This study employed scenario planning and multi-criteria decision analysis (MCDA) to evaluate stakeholders' preferences for alternative reimbursement pathways, informing future health technology assessment (HTA) submission of WGS in blood cancer.

METHODS

Key factors influencing WGS reimbursement in blood cancers were identified through a literature search. Hypothetical scenarios describing various evidential characteristics of WGS for HTA were developed using the morphological approach. An online survey, incorporating MCDA weights, was designed to gather stakeholder preferences (consumers/patients, clinicians/health professionals, industry representatives, health economists, and HTA committee members) for these scenarios. The survey assessed participants' approval of WGS reimbursement for each scenario, and scenario preferences were determined using the geometric mean method, applying an algorithm to improve reliability and precision by addressing inconsistent responses.

RESULTS

Nineteen participants provided complete survey responses, primarily clinicians or health professionals (n = 6; 32 %), consumers/patients and industry representatives (both at n = 5; 26 %). "Clinical impact of WGS results on patient care" was the most critical criterion (criteria weight of 0.25), followed by "diagnostic accuracy of WGS" (0.21), "cost-effectiveness of WGS" (0.19), "availability of reimbursed treatment after WGS" (0.16), and "eligibility criteria for reimbursed treatment based on actionable WGS results" and "cost comparison of WGS" (both at 0.09). Participants preferred a scenario with substantial clinical evidence, high access to reimbursed targeted treatment, cost-effectiveness below $50,000 per quality-adjusted life year (QALY) gained, and affordability relative to standard molecular tests. Reimbursement was initially opposed until criteria such as equal cost to standard tests and better treatment accessibility were met.

CONCLUSION

Payers commonly emphasize acceptable cost-effectiveness, but strong clinical evidence for many variants and comparable costs to standard tests are likely to drive positive reimbursement decisions for WGS.

Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders

Genetic diseases are medical conditions caused by sequence or structural changes in an individual's genome. Whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly used for diagnosing suspected genetic conditions in children to reduce the diagnostic delay and accelerating the implementation of appropriate treatments. While more information is becoming available on clinical efficacy and economic sustainability of WES, the broad implementation of WGS is still hindered by higher complexity and economic issues. The aim of this study is to estimate the cost-effectiveness of WGS versus WES and standard testing for pediatric patients with suspected genetic disorders. A Bayesian decision tree model was set up. Model parameters were retrieved both from hospital administrative datasets and scientific literature. The analysis considered a lifetime time frame and adopted the perspective of the Italian National Health Service (NHS). Bayesian inference was performed using the Markov Chain Monte Carlo simulation method. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI). The present analysis showed that implementing first-line WGS would be a cost-effective strategy, against the majority of the other tested alternatives at a threshold of €30,000-50,000, for diagnosing outpatient pediatric patients with suspected genetic disorders. According to the sensitivity analyses, the findings were robust to most assumption and parameter uncertainty. Lessons learnt from this modeling study reinforces the adoption of first-line WGS, as a cost-effective strategy, depending on actual difficulties for the NHS to properly allocate limited resources.

Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders

Importance

The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary.

Objective

To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders.

Design, Setting, and Participants

In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis.

Main Outcomes and Measures

Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS.

Results

The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty.

Conclusions and Relevance

The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

Can knowledgeable experts assess costs and outcomes as if they were ignorant? An experiment within precision medicine evaluation

OBJECTIVES

The purpose of this study is to evaluate the validity of the standard approach in expert judgment for evaluating precision medicines, in which experts are required to estimate outcomes as if they did not have access to diagnostic information, whereas in fact, they do.

METHODS

Fourteen clinicians participated in an expert judgment task to estimate the cost and medical outcomes of the use of exome sequencing in pediatric patients with intractable epilepsy in Thailand. Experts were randomly assigned to either an "unblind" or "blind" group; the former was provided with the exome sequencing results for each patient case prior to the judgment task, whereas the latter was not provided with the exome sequencing results. Both groups were asked to estimate the outcomes for the counterfactual scenario, in which patients had not been tested by exome sequencing.

RESULTS

Our study did not show significant results, possibly due to the small sample size of both participants and case studies.

CONCLUSIONS

A comparison of the unblind and blind approach did not show conclusive evidence that there is a difference in outcomes. However, until further evidence suggests otherwise, we recommend the blind approach as preferable when using expert judgment to evaluate precision medicines because this approach is more representative of the counterfactual scenario than the unblind approach.

Evaluating the Value for Money of Precision Medicine from Early Cycle to Market Access: A Comprehensive Review of Approaches and Challenges

OBJECTIVES

This study aimed to perform a comprehensive review of modeling approaches and methodological and policy challenges in the economic evaluation (EE) of precision medicine (PM) across clinical stages.

METHODS

First, a systematic review was performed to assess the approaches of EEs in the past 10 years. Next, a targeted review of methodological articles was conducted for methodological and policy challenges in performing EEs of PM. All findings were synthesized into a structured framework that focused on patient population, Intervention, Comparator, Outcome, Time, Equity and ethics, Adaptability and Modeling aspects, named the "PICOTEAM" framework. Finally, a stakeholder consultation was conducted to understand the major determinants of decision making in PM investment.

RESULTS

In 39 methodological articles, we identified major challenges to the EE of PM. These challenges include that PM applications involve complex and evolving clinical decision space, that clinical evidence is sparse because of small subgroups and complex pathways in PM settings, a one-time PM application may have lifetime or intergenerational impacts but long-term evidence is often unavailable, and that equity and ethics concerns are exceptional. In 275 EEs of PM, current approaches did not sufficiently capture the value of PM compared with targeted therapies, nor did they differentiate Early EEs from Conventional EEs. Finally, policy makers perceived the budget impact, cost savings, and cost-effectiveness of PM as the most important determinants in decision making.

CONCLUSIONS

There is an urgent need to modify existing guidelines or develop a new reference case that fits into the new healthcare paradigm of PM to guide decision making in research and development and market access.

Economic evaluations of predictive genetic testing: A scoping review

Predictive genetic testing can provide information about whether or not someone will develop or is likely to develop a specific condition at a later stage in life. Economic evaluation can assess the value of money for such testing. Studies on the economic evaluation of predictive genetic testing have been carried out in a variety of settings, and this research aims to conduct a scoping review of findings from these studies. We searched the PubMed, Web of Science, Embase, and Cochrane databases with combined search terms, from 2019 to 2022. Relevant studies from 2013 to 2019 in a previous systematic review were also included. The study followed the recommended stages for undertaking a scoping review. A total of 53 studies were included, including 33 studies from the previous review and 20 studies from the search of databases. A significant number of studies focused on the US, UK, and Australia (34%, 23%, and 11%). The most frequently included health conditions were cancer and cardiovascular diseases (68% and 19%). Over half of the studies compared predictive genetic testing with no genetic testing, and the majority of them concluded that at least some type of genetic testing was cost-effective compared to no testing (94%). Some studies stated that predictive genetic testing is becoming more cost-effective with the trend of lowering genetic testing costs. Studies on predictive genetic testing covered various health conditions, particularly cancer and cardiovascular diseases. Most studies indicated that predictive genetic testing is cost-effective compared to no testing.

A comparative cost analysis of two screening strategies for colorectal cancer in Lynch Syndrome in a South African tertiary hospital

AIM

Lynch Syndrome (LS) individuals have a 25-75% lifetime risk of developing colorectal cancer. Colonoscopy screening decreases this risk. This study compared the cost of Strategy 1: screening colonoscopy for 1st degree relatives of patients that met the Revised Bethesda Criteria (i.e., probands) to Strategy 2: screening colonoscopy for 1^st degree relatives of probands with genetic mutations for Lynch Syndrome based in a resource-constrained health care system.

METHOD

A comparative, health care provider perspective, cost analysis was conducted at a tertiary hospital, using a micro-costing, ingredient approach. Forty probands that underwent genetic testing between November 01, 2014 and October 30, 2015 and their first-degree relatives were costed according to Strategy 1 and Strategy 2. Unit costs of colonoscopy and genetic testing were estimated and used to calculate and compare the total costs per strategy in South African rand (R) converted to UK pounds (£). Sensitivity analyses were performed on colonoscopy adherence, relatives' positivity, and variable discount rates.

RESULTS

The cost for Strategy 1 amounted to £653 344/R6 161 035 compared to £49 327/R 465 155 for Strategy 2 (Discount rate 3%; Adherence 75%; and Positivity rate of relatives 45%). Base case analysis indicated a difference of 92% less in the total cost for Strategy 2 compared to Strategy 1. Sensitivity analyses showed that the difference in cost between the two strategies was not sensitive to variations in adherence, positivity or discount rates.

CONCLUSION

Colonoscopy screening for LS and at-risk family members was tenfold less costly when combined with genetic analysis. The logistics of rolling out this strategy nationally should be investigated.

Economic evaluation of using polygenic risk score to guide risk screening and interventions for the prevention of type 2 diabetes in individuals with high overall baseline risk

Type 2 diabetes (T2D) with increasing prevalence is a significant global public health challenge. Obesity, unhealthy diet, and low physical activity are one of the major determinants of the rise in T2D prevalence. In addition, family history and genetic risk of diabetes also play a role in the process of developing T2D. Therefore, solutions for the early identification of individuals at high risk for T2D for early targeted detection of T2D, prevention, and intervention are highly preferred. Recently, novel genomic-based polygenic risk scores (PRSs) have been suggested to improve the accuracy of risk prediction supporting the targeting of preventive interventions to those at highest risk for T2D. Therefore, the aim of the present study was to assess the cost-utility of an additional PRS testing information (as a part of overall risk assessment) followed by a lifestyle intervention and an additional medical therapy when estimated 10-year overall risk for T2D exceeded 20% among Finnish individuals screened as at the high-risk category (i.e., 10%–20% 10-year overall risk of T2D) based on traditional risk factors only. For a cost-utility analysis, an individual-level state-transition model with probabilistic sensitivity analysis was constructed. A 1-year cycle length and a lifetime time horizon were applied in the base-case. A 3% discount rate was used for costs and QALYs. Cost-effectiveness acceptability curve (CEAC) and estimates for the expected value of perfect information (EVPI) were calculated to assist decision makers. The use of the targeted PRS strategy reclassified 12.4 percentage points of individuals to be very high-risk individuals who would have been originally classified as high risk using the usual strategy only. Over a lifetime horizon, the targeted PRS was a dominant strategy (i.e., less costly, more effective). One-way and scenario sensitivity analyses showed that results remained dominant in almost all simulations. However, there is uncertainty, since the probability (EVPI) of cost-effectiveness at a WTP of 0€/QALY was 63.0% (243€) indicating the probability that the PRS strategy is a dominant option. In conclusion, the results demonstrated that the PRS provides moderate additional value in Finnish population in risk screening leading to potential cost savings and better quality of life when compared with the current screening methods for T2D risk.

Defining a Core Data Set for the Economic Evaluation of Precision Oncology

OBJECTIVES

Precision oncology is generating vast amounts of multiomic data to improve human health and accelerate research. Existing clinical study designs and attendant data are unable to provide comparative evidence for economic evaluations. This lack of evidence can cause inconsistent and inappropriate reimbursement. Our study defines a core data set to facilitate economic evaluations of precision oncology.

METHODS

We conducted a literature review of economic evaluations of next-generation sequencing technologies, a common application of precision oncology, published between 2005 and 2018 and indexed in PubMed (MEDLINE). Based on this review, we developed a preliminary core data set for informal expert feedback. We then used a modified-Delphi approach with individuals involved in implementation and evaluation of precision medicine, including 2 survey rounds followed by a final voting conference to refine the data set.

RESULTS

Two authors determined that variation in published data elements was reached after abstraction of 20 economic evaluations. Expert consultation refined the data set to 83 unique data elements, and a multidisciplinary sample of 46 experts participated in the modified-Delphi process. A total of 68 elements (81%) were selected as required, spanning demographics and clinical characteristics, genomic data, cancer treatment, health and quality of life outcomes, and resource use.

CONCLUSIONS

Cost-effectiveness analyses will fail to reflect the real-world impacts of precision oncology without data to accurately characterize patient care trajectories and outcomes. Data collection in accordance with the proposed core data set will promote standardization and enable the generation of decision-grade evidence to inform reimbursement.

Evaluating the quality of the economic evidence in colorectal cancer genomics studies

The increase in the use of genome-based screening and diagnostic tests adds to the overall costs of oncologic care for colorectal cancer. This, in turn, has resulted in an increase in published economic analyses. Aim: To perform a systematic literature review of the available economic evidence evaluating the value of genomic testing for colorectal cancer and appraise the quality of the economic studies conducted to date. Methods: A systematic review of the literature for economic studies of colorectal cancer genomics from January 2006 through October 2020, and evaluation of study quality using the Quality of Health Economic Studies (QHES) instrument was conducted. The validated QHES was then applied to a final set of articles that met eligibility criteria. Results: Our search of the literature initially yielded 12,859 records. A final set of 49 articles met our inclusion criteria. The QHES score ranged from 24 to 100, with an average score of 82. Most of the studies (n = 40, 82%) scored above 75 and were considered of good quality. Conclusion: Our analysis revealed that most of the economic analyses of colorectal cancer genomic molecular diagnostics in the literature may be of good quality. There is, however, some variation in methodological rigor between the articles.

Health economic evidence for the use of molecular biomarker tests in hematological malignancies: A systematic review

Objectives

Molecular biomarker tests can inform the clinical management of genomic heterogeneous hematological malignancies, yet their availability in routine care largely depends on the supporting health economic evidence. This study aims to systematically review the economic evidence for recent molecular biomarker tests in hematological malignancies.

Methods

We conducted a systematic search in five electronic databases for studies published between January 2010 and October 2020. Publications were independently screened by two reviewers. Clinical study characteristics, economic methodology, and results were extracted, and reporting quality was assessed.

Results

Fourteen studies were identified, of which half (n = 7; 50%) were full economic evaluations examining both health and economic outcomes. Studies were predominantly conducted in a first‐line treatment setting (n = 7; 50%) and adopted a non‐lifetime time horizon to measure health outcomes and costs (n = 7; 50%). Five studies reported that companion diagnostics for associated therapies were likely cost‐effective for acute myeloid leukemia, chronic myeloid leukemia, diffuse large B‐cell lymphoma, and multiple myeloma. Four studies suggested molecular biomarker tests for treatment monitoring in chronic myeloid leukemia were likely cost‐saving.

Conclusions

Although there is initial confirmation of the promising health economic results, the present research for molecular biomarker tests in hematological malignancies is sparse with many applications of technological advances yet to be evaluated.

What Has the Undiagnosed Diseases Network Taught Us About the Clinical Applications of Genomic Testing?

Genetic testing has undergone a revolution in the last decade, particularly with the advent of next-generation sequencing and its associated reductions in costs and increases in efficiencies. The Undiagnosed Diseases Network (UDN) has been a leader in the application of such genomic testing for rare disease diagnosis. This review discusses the current state of genomic testing performed within the UDN, with a focus on the strengths and limitations of whole-exome and whole-genome sequencing in clinical diagnostics and the importance of ongoing data reanalysis. The role of emerging technologies such as RNA and long-read sequencing to further improve diagnostic rates in the UDN is also described. This review concludes with a discussion of the challenges faced in insurance coverage of comprehensive genomic testing as well as the opportunities for a larger role of testing in clinical medicine.

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.

Stakeholder Perspectives on Navigating Evidentiary and Decision Uncertainty in Precision Oncology

(1) Background: Precision oncology has the potential to improve patient health and wellbeing through targeted prevention and treatment. Owing to uncertain clinical and economic outcomes, reimbursement has been limited. The objective of this pan-Canadian qualitative study was to investigate barriers to precision oncology implementation from the perspectives of health system stakeholders. (2) Methods: We conducted 32 semi-structured interviews with health technology decision makers (n = 14) and clinicians (n = 18) experienced with precision oncology. Participants were recruited using a purposive sampling technique. Interviews were analyzed using thematic analysis. Recruitment continued until two qualitative analysts reached agreement that thematic saturation was reached. (3) Results: While cautiously optimistic about the potential for enhanced therapeutic alignment, participants identified multiple decisional challenges under conditions of evidentiary uncertainty. Decision makers voiced concern over resource requirements alongside small benefitting patient populations and limited evidence supporting patient and health system impacts. Clinicians were comparatively tolerant of evidentiary uncertainty guiding clinical decision-making practices. Clinicians applied a broader definition of patient benefit, focusing on the ability to assist patients making informed clinical decisions. (4) Conclusions: Sustainable precision oncology must balance demand with evidence demonstrating benefit. We show that clinicians and decision makers vary in their tolerance for evolving knowledge, suggesting a need to establish evidentiary standards supporting precision oncology reimbursement decisions.

Evaluation of Pharmacogenomics Testing of Cytochrome P450 Enzymes in the Military Health System From 2015 to 2020

Pharmacogenomics (PGx) plays a fundamental role in personalized medicine, providing an evidence-based treatment approach centered on the relationship between genomic variations and their effect on drug metabolism. Cytochrome P450 (CYP450) enzymes are responsible for the metabolism of most clinically prescribed drugs and a major source of variability in drug pharmacokinetics and pharmacodynamics. To assess the prevalence of PGx testing within the Military Health System (MHS), testing of specific CYP450 enzymes was evaluated. Data were retrospectively obtained from the Military Health System Management Analysis and Reporting Tool (M2) database. Patient demographics were identified for each test, along with TRICARE status, military treatment facility, clinic, and National Provider Identifier. A total of 929 patients received 1,833 PGx tests, predominantly composed of active duty/guard service members (N = 460; 49.5%), with highest testing rates in the army (51.5%). An even distribution in testing was observed among gender, with the highest rates in Caucasians (41.7%). Of the CYP enzymes assessed, CYP2C19 and CYP2D6 accounted for 87.8% of all PGx CYP testing. The majority of patients were tested in psychiatry clinics (N = 496; 53.4%) and primary care clinics (N = 233; 25.1%), accounting for 56.4% and 24.8% of all tests, respectively. Testing was found to be provider driven, suggesting a lack of a standardized approach to PGx and its application in patient care within the MHS. We initially recommend targeted education and revising testing labels to be more uniform and informative. Long-term recommendations include establishing pharmacy-driven protocols and point-of-care PGx testing to optimize patient outcomes.

Conceptualising 'Benefits Beyond Health' in the Context of the Quality-Adjusted Life-Year: A Critical Interpretive Synthesis

There is growing interest in extending the evaluative space of the quality-adjusted life-year framework beyond health. Using a critical interpretive synthesis approach, the objective was to review peer-reviewed literature that has discussed non-health outcomes within the context of quality-adjusted life-years and synthesise information into a thematic framework. Papers were identified through searches conducted in Web of Science, using forward citation searching. A critical interpretive synthesis allows for the development of interpretations (synthetic constructs) that go beyond those offered in the original sources. The final output of a critical interpretive synthesis is the synthesising argument, which integrates evidence from across studies into a coherent thematic framework. A concept map was developed to show the relationships between different types of non-health benefits. The critical interpretive synthesis was based on 99 papers. The thematic framework was constructed around four themes: (1) benefits affecting well-being (subjective well-being, psychological well-being, capability and empowerment); (2) benefits derived from the process of healthcare delivery; (3) benefits beyond the recipient of care (spillover effects, externalities, option value and distributional benefits); and (4) benefits beyond the healthcare sector. There is a wealth of research concerning non-health benefits and the evaluative space of the quality-adjusted life-year. Further dialogue and debate are necessary to address conceptual and normative challenges, to explore the societal willingness to sacrifice health for benefits beyond health and to consider the equity implications of different courses of action.

Cost-Effectiveness of Targeted Exome Analysis as a Diagnostic Test in Glomerular Diseases

BACKGROUND

Despite the emergence of diagnostic and clinical utility evidence in nephrology, publicly funded access to genomic testing is restricted in most health care systems. To establish genomic sequencing as a clinical test, an evaluation of cost-effectiveness is urgently required.

METHODS

An economic evaluation, informed by a primary clinical study and available clinical evidence and guidelines in nephrology, was performed to evaluate the cost-effectiveness and optimal timing of exome sequencing (ES) in adults and children with suspected monogenic glomerular diseases compared with nongenomic investigations (NGIs). Six diagnostic strategies reflecting current practice and recommended models of care in Australia were modeled: (i) NGIs, (ii) late gene panel followed by ES, (iii) late ES, (iv) early gene panel, (v) early gene panel followed by ES, and (vi) early ES.

RESULTS

ES with targeted analysis achieved a diagnosis in 23 of 63 (36.5%) adults and 10 of 24 (41.6%) children. NGIs were estimated to diagnose 4.0% of children, with an average estimated cost of AU$6120 per child. Integrating ES as a first-line test in children was cost saving, with an incremental cost saving of AU$3230 per additional diagnosis compared with NGIs. In adults, NGIs was estimated to diagnose 8% of patients, with an average estimated cost of AU$1830 per person. In adults, integrating ES early resulted in an incremental cost per additional diagnosis of AU$5460 relative to NGIs.

CONCLUSIONS

Early ES with targeted analysis was effective for diagnosing monogenic kidney disease, with substantial cost savings in children.

Economic evaluations of exome and genome sequencing in pediatric genetics: considerations towards a consensus strategy

OBJECTIVE

Next Generation Sequencing (NGS) is increasingly used for the diagnosis of rare genetic disorders. The aim of this study is to review the different approaches for economic evaluations of Next Generation Sequencing (NGS) in pediatric care used to date, to identify all costs, effects, and time horizons taken into account.

METHODS

A systematic literature review was conducted to identify published economic evaluations of NGS applications in pediatric diagnostics, i.e. exome sequencing (ES) and/or genome sequencing (GS). Information regarding methodological approach, costs, effects, and time horizon was abstracted from these publications.

RESULTS

Twenty-eight economic evaluations of ES/GS within pediatrics were identified. Costs included were mainly restricted to direct in-hospital healthcare costs and varied widely in inclusion of sort of costs and time-horizon. Nineteen studies included diagnostic yield and eight studies included cost-effectiveness as outcome measures. Studies varied greatly in terms of included sort of costs data, effects, and time horizon.

CONCLUSION

Large differences in inclusion of cost and effect parameters were identified between studies. Validity of outcomes can therefore be questioned, which hinders valid comparison and widespread generalization of conclusions. In addition to current health economic guidance, specific guidance for evaluations in pediatric care is therefore necessary to improve the validity of outcomes and furthermore facilitate comparable decision-making for implementing novel NGS-based diagnostic modalities in pediatric genetics and beyond.

Should We Consider Value Frameworks for Cancer Drugs as Oncology's Landscape Evolves?; from an Oncologist Perspective in Korea

BACKGROUND

As the role of immunotherapies and personalized medicine grow, cancer patients have faced many choices in treatments and have suffered financial toxicity. These challenges brought the need for the value framework (VF) to guide treatment decision making.

METHODS

A survey was taken to 102 oncologists about perception for VF. They were asked about priorities among several considerations when they prescribe cancer drugs. Their views on the need for development and potential implications of VF in Korea were assessed, also.

RESULTS

The survey shows that 90% of the respondents choose clinical efficacy as the most important value in cancer drugs selection, and the cost of drug was more weighted value in immune checkpoint inhibitors (13.7%). Approximately half (53.9%) answered that they were aware of the existing VFs. Over 90% of respondents agreed with the need for development of a VF for cancer drugs based on Korean healthcare system and further usefulness for decisions about reimbursement issues. Seventy-one percent answered that two representative VFs (American Society Clinical Oncology-VF and European Society for Medical Oncology-Magnitude of Clinical Benefit Scale) should be reflected in value measurement of cancer drugs in Korea.

CONCLUSION

The Korean oncologists recognized the necessity for the clinical application of VF. Further discussion between the stakeholders should be followed to alleviate the financial burden through the value-based decision making of cancer drugs.

Guidance for the Harmonisation and Improvement of Economic Evaluations of Personalised Medicine

OBJECTIVE

The objective of this study was to develop guidance contributing to improved consistency and quality in economic evaluations of personalised medicine (PM), given current ambiguity about how to measure the value of PM as well as considerable variation in the methodology and reporting in economic evaluations of PM.

METHODS

A targeted literature review of methodological papers was performed for an overview of modelling challenges in PM. Expert interviews were held to discuss best modelling practice. A systematic literature review of economic evaluations of PM was conducted to gain insight into current modelling practice. The findings were synthesised and used to develop a set of draft recommendations. The draft recommendations were discussed at a stakeholder workshop and subsequently finalised.

RESULTS

Twenty-two methodological papers were identified. Some argued that the challenges in modelling PM can be addressed within existing methodological frameworks, others disagreed. Eighteen experts were interviewed. They believed large uncertainty to be a key concern. Out of 195 economic evaluations of PM identified, 56% addressed none of the identified modelling challenges. A set of 23 recommendations was developed. Eight recommendations focus on the modelling of test-treatment pathways. The use of non-randomised controlled trial data is discouraged but several recommendations are provided in case randomised controlled trial data are unavailable. The parameterisation of structural uncertainty is recommended. Other recommendations consider perspective and discounting; premature survival data; additional value elements; patient and clinician compliance; and managed entry agreements.

CONCLUSIONS

This study provides a comprehensive list of recommendations to modellers of PM and to evaluators and reviewers of PM models.

The Interface of Therapeutics and Genomics in Cardiovascular Medicine

Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.

Economic evaluation of whole genome sequencing for pathogen identification and surveillance - results of case studies in Europe and the Americas 2016 to 2019

Background

Whole genome sequencing (WGS) is increasingly used for pathogen identification and surveillance.

Aim

We evaluated costs and benefits of routine WGS through case studies at eight reference laboratories in Europe and the Americas which conduct pathogen surveillance for avian influenza (two laboratories), human influenza (one laboratory) and food-borne pathogens (five laboratories).

Methods

The evaluation focused on the institutional perspective, i.e. the ‘investment case’ for implementing WGS compared with conventional methods, based on costs and benefits during a defined reference period, mostly covering at least part of 2017. A break-even analysis estimated the number of cases of illness (for the example of Salmonella surveillance) that would need to be avoided through WGS in order to ‘break even’ on costs.

Results

On a per-sample basis, WGS was between 1.2 and 4.3 times more expensive than routine conventional methods. However, WGS brought major benefits for pathogen identification and surveillance, substantially changing laboratory workflows, analytical processes and outbreaks detection and control. Between 0.2% and 1.1% (on average 0.7%) of reported salmonellosis cases would need to be prevented to break even with respect to the additional costs of WGS.

Conclusions

Even at cost levels documented here, WGS provides a level of additional information that more than balances the additional costs if used effectively. The substantial cost differences for WGS between reference laboratories were due to economies of scale, degree of automation, sequencing technology used and institutional discounts for equipment and consumables, as well as the extent to which sequencers are used at full capacity.

Pharmacogenomics Implementation and Hurdles to Overcome; In the Context of a Developing Country

Having multiple dimensions, uncertainties and several stakeholders, the costly pharmacogenomics (PGx) is associated with dynamic implementation complexities. Identification of these challenges is critical to harness its full potential, especially in developing countries with fragile healthcare systems and scarce resources. This is the first study aimed to identify most salient challenges related to PGx implementation, with respect to the experiences of early-adopters and local experts' prospects, in the context of a developing country in the Middle East. To perform a comprehensive reconnaissance on PGx adoption challenges a scoping literature review was conducted based on national drug policy components: efficacy/safety, access, affordability and rational use of medicine (RUM). Strategic option development and analysis workshop method with cognitive mapping as the technique was used to evaluate challenges in the context of Iran. The cognitive maps were face-validated and analyzed via Decision Explorer XML. The findings indicated a complex network of issues relative to PGx adoption, categorized in national drug policy indicators. In the rational use of medicine category, ethics, education, bench -to- bedside strategies, guidelines, compliance, and health system issues were found. Clinical trial issues, test's utility, and biomarker validation were identified in the efficacy group. Affordability included pricing, reimbursement, and value assessment issues. Finally, access category included regulation, availability, and stakeholder management challenges. The current study identified the most significant challenges ahead of clinical implementation of PGx in a developing country. This could be the basis of a policy-note development in future work, which may consolidate vital communication among stakeholders and accelerate the efficient implementation in developing new-comer countries.

Exome Sequencing for Isolated Congenital Hearing Loss: A Cost-Effectiveness Analysis

OBJECTIVES/HYPOTHESIS

To assess the relative cost-effectiveness of exome sequencing for isolated congenital deafness compared with standard care.

STUDY DESIGN

Incremental cost-effectiveness and cost-benefit analyses were undertaken from the perspective of the Australian healthcare system using an 18-year time horizon.

METHODS

A decision tree was used to model the costs and outcomes associated with exome sequencing and standard care for infants presenting with isolated congenital deafness.

RESULTS

Exome sequencing resulted in an incremental cost of AU$1,000 per child and an additional 30 diagnoses per 100 children tested. The incremental cost-effectiveness ratio was AU$3,333 per additional diagnosis. The mean societal willingness to pay for exome sequencing was estimated at AU$4,600 per child tested relative to standard care, resulting in a positive net benefit of AU$3,600. Deterministic and probabilistic sensitivity analyses confirmed the cost-effectiveness of exome sequencing.

CONCLUSIONS

Our findings demonstrate the cost-effectiveness of exome sequencing in congenital hearing loss, through increased diagnostic rate and consequent improved process of care by reducing or ceasing diagnostic investigation or facilitating targeted further investigation. We recommend equitable funding for exome sequencing in infants presenting with isolated congenital hearing loss.

LEVEL OF EVIDENCE

N/A. Laryngoscope, 131:E2371-E2377, 2021.

Clinical utility of genomic sequencing: a measurement toolkit

Whole-genome sequencing (WGS) is positioned to become one of the most robust strategies for achieving timely diagnosis of rare genomic diseases. Despite its favorable diagnostic performance compared to conventional testing strategies, routine use and reimbursement of WGS are hampered by inconsistencies in the definition and measurement of clinical utility. For example, what constitutes clinical utility for WGS varies by stakeholder's perspective (physicians, patients, families, insurance companies, health-care organizations, and society), clinical context (prenatal, pediatric, critical care, adult medicine), and test purpose (diagnosis, screening, treatment selection). A rapidly evolving technology landscape and challenges associated with robust comparative study design in the context of rare disease further impede progress in this area of empiric research. To address this challenge, an expert working group of the Medical Genome Initiative was formed. Following a consensus-based process, we align with a broad definition of clinical utility and propose a conceptually-grounded and empirically-guided measurement toolkit focused on four domains of utility: diagnostic thinking efficacy, therapeutic efficacy, patient outcome efficacy, and societal efficacy. For each domain of utility, we offer specific indicators and measurement strategies. While we focus on diagnostic applications of WGS for rare germline diseases, this toolkit offers a flexible framework for best practices around measuring clinical utility for a range of WGS applications. While we expect this toolkit to evolve over time, it provides a resource for laboratories, clinicians, and researchers looking to characterize the value of WGS beyond the laboratory.

Genomic Testing for Relapsed and Refractory Lymphoid Cancers: Understanding Patient Values

BACKGROUND

New clinical genomic assays for lymphoid cancers allow for improved disease stratification and prognostication. At present, clinical implementation has been appropriately limited, owing to a paucity of evidence to support clinical and cost effectiveness. Understanding patients' values for precision oncology under conditions of uncertainty can be used to inform priority-setting decisions.

OBJECTIVES

Our objective was to ascertain patients' qualitative preferences and attitudes for prognostic-based genomic testing.

METHODS

Individuals who were diagnosed with lymphoid cancer between 2000 and 2018 in British Columbia, Canada, were recruited to participate in one of three focus groups. A maximum variation sampling technique was used to capture a diversity of perspectives. A patient partner was involved in the development of the focus group topic guide and presentation materials. All sessions were audio recorded and analyzed using NVivo qualitative analysis software, version 12.

RESULTS

In total, 26 participants took part in focus groups held between November 2018 and February 2019. Results illustrate qualitative preference heterogeneity for situations under which individuals would be willing to undergo genomic testing for relapsed lymphoid cancers. Preferences were highly contextualized within personal experiences with disease and treatment protocols. Hypothetical willingness to pay for testing was contingent on invasiveness, the potential for treatment de-escalation, and personal health benefit.

CONCLUSIONS

Patients are supportive and accepting of evidentiary uncertainty up until the point at which they are required to trade-off the potential for improved quality and length of life. Demand for precision medicine is contingent on expectations for benefit alongside an acknowledgment of the opportunity cost required for implementation. The clinical implementation of precision medicine will be required to address evidentiary uncertainty surrounding personal benefit while ensuring equitable access to emerging innovations.

The personal utility and uptake of genomic sequencing in pediatric and adult conditions: eliciting societal preferences with three discrete choice experiments

Purpose

To estimate the personal utility and uptake of genomic sequencing (GS) across pediatric and adult-onset genetic conditions.

Methods

Three discrete choice experiment (DCE) surveys were designed and administered to separate representative samples of the Australian public. Bayesian D-efficient explicit partial profile designs were used. Choice data were analyzed using a panel error component random parameter logit model.

Results

Overall, 1913 participants completed the pediatric (n = 533), symptomatic adult (n = 700) and at-risk adult (n = 680) surveys. The willingness-to-pay for GS information in pediatric conditions was estimated at $5470–$15,250 (US$3830–$10,675) depending on the benefits of genomic information. Uptake ranged between 60% and 81%. For symptomatic adults, the value of GS was estimated at $1573–$8102 (US$1100–$5671) and uptake at 34–82%. For at-risk adults, GS was valued at $2036–$5004 (US$1425–$3503) and uptake was predicted at 35–61%.

Conclusion

There is substantial personal utility in GS, particularly for pediatric conditions. Personal utility increased as the perceived benefits of genomic information increased. The clinical and regulatory context, and individuals’ sociodemographic and attitudinal characteristics influenced the value and uptake of GS. Society values highly the diagnostic, clinical, and nonclinical benefits of GS. The personal utility of GS should be considered in health-care decision-making.

Quantifying Downstream Healthcare Utilization in Studies of Genomic Testing

OBJECTIVES

The challenges of understanding how interventions influence follow-up medical care are magnified during genomic testing because few patients have received it to date and because the scope of information it provides is complex and often unexpected. We tested a novel strategy for quantifying downstream healthcare utilization after genomic testing to more comprehensively and efficiently identify related services. We also evaluated the effectiveness of different methods for collecting these data.

METHODS

We developed a risk-based approach for a trial of newborn genomic sequencing in which we defined primary conditions based on existing diagnoses and family histories of disease and defined secondary conditions based on unexpected findings. We then created patient-specific lists of services associated with managing primary and secondary conditions. Services were quantified based on medical record reviews, surveys, and telephone check-ins with parents.

RESULTS

By focusing on services that genomic testing would most likely influence in the short-term, we reduced the number of services in our analyses by more than 90% compared with analyses of all observed services. We also identified the same services that were ordered in response to unexpected findings as were identified during expert review and by confirming whether recommendations were completed. Data also showed that quantifying healthcare utilization with surveys and telephone check-ins alone would have missed the majority of attributable services.

CONCLUSIONS

Our risk-based strategy provides an improved approach for assessing the short-term impact of genomic testing and other interventions on healthcare utilization while conforming as much as possible to existing best-practice recommendations.

Genome-Wide Sequencing for Unexplained Developmental Disabilities or Multiple Congenital Anomalies: A Health Technology Assessment

BACKGROUND

People with unexplained developmental disabilities or multiple congenital anomalies might have had many biochemical, metabolic, and genetic tests for a period of years without receiving a diagnosis. A genetic diagnosis can help these people and their families better understand their condition and may help them to connect with others who have the same condition. Ontario Health (Quality), in collaboration with the Canadian Agency for Drugs and Technologies in Health (CADTH) conducted a health technology assessment about the use of genome-wide sequencing for patients with unexplained developmental disabilities or multiple congenital anomalies. Ontario Health (Quality) evaluated the effectiveness, cost-effectiveness, and budget impact of publicly funding genome-wide sequencing. We also conducted interviews with patients and examined the quantitative evidence of preferences and values literature to better understand the patient preferences and values for these tests.

METHODS

Ontario Health (Quality) performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS) and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also performed a search of the quantitative evidence and undertook direct patient engagement to ascertain patient preferences for genetic testing for unexplained developmental disabilities or multiple congenital anomalies. CADTH performed a review of qualitative literature about patient perspectives and experiences, and a review of ethical issues.Ontario Health (Quality) performed an economic literature review of genome-wide sequencing in people with unexplained developmental disabilities or multiple congenital anomalies. Although we found eight published cost-effectiveness studies, none completely addressed our research question. Therefore, we conducted a primary economic evaluation using a discrete event simulation model. Owing to its high cost and early stage of clinical implementation, whole exome sequencing is primarily used for people who do not have a diagnosis from standard testing (referred to here as whole exome sequencing after standard testing; standard testing includes chromosomal microarray and targeted single-gene tests or gene panels). Therefore, in our first analysis, we evaluated the cost-effectiveness of whole exome sequencing after standard testing versus standard testing alone. In our second analysis, we explored the cost-effectiveness of whole exome and whole genome sequencing used at various times in the diagnostic pathway (e.g., first tier, second tier, after standard testing) versus standard testing. We also estimated the budget impact of publicly funding genome-wide sequencing in Ontario for the next 5 years.

RESULTS

Forty-four studies were included in the clinical evidence review. The overall diagnostic yield of genome-wide sequencing for people with unexplained development disability and multiple congenital anomalies was 37%, but we are very uncertain about this estimate (GRADE: Very Low). Compared with standard genetic testing of chromosomal microarray and targeted single-gene tests or gene panels, genome-wide sequencing could have a higher diagnostic yield (GRADE: Low). As well, for some who are tested, genome-wide sequencing prompts some changes to medications, treatments, and referrals to specialists (GRADE: Very Low).Whole exome sequencing after standard testing cost an additional $3,261 per patient but was more effective than standard testing alone. For every 1,000 persons tested, using whole exome sequencing after standard testing would lead to an additional 240 persons with a molecular diagnosis, 272 persons with any positive finding, and 46 persons with active treatment change (modifications to medications, procedures, or treatment). The resulting incremental cost-effectiveness ratios (ICERs) were $13,591 per additional molecular diagnosis. The use of genome-wide sequencing early in the diagnostic pathway (e.g., as a first- or second-tier test) can save on costs and improve diagnostic yields over those of standard testing. Results remained robust when parameters and assumptions were varied.Our budget impact analysis showed that, if whole exome sequencing after standard testing continues to be funded through Ontario's Out-of-Country Prior Approval Program, its budget impact would range from $4 to $5 million in years 1 to 5. If whole exome sequencing becomes publicly funded in Ontario (not through the Out-of-Country Prior Approval Program), the budget impact would be about $9 million yearly. We also found that using whole exome sequencing as a second-tier test would lead to cost savings ($3.4 million per 1,000 persons tested yearly).Participants demonstrated consistent motivations for and expectations of obtaining a diagnosis for unexplained developmental delay or congenital anomalies through genome-wide sequencing. Patients and families greatly value the support and information they receive through genetic counselling when considering genome-wide sequencing and learning of a diagnosis.

CONCLUSIONS

Genome-wide sequencing could have a higher diagnostic yield than standard testing for people with unexplained developmental disabilities or multiple congenital anomalies. Genome-wide sequencing can also prompt some changes to medications, treatments, and referrals to specialists for some people tested; however, we are very uncertain about this. Genome-wide sequencing could be a cost-effective strategy when used after standard testing to diagnose people with unexplained developmental disabilities or multiple congenital anomalies. It could also lead to cost savings when used earlier in the diagnostic pathway. Patients and families consistently noted a benefit from seeking a diagnosis through genetic testing.

Conducting Value for Money Analyses for Non-randomised Interventional Studies Including Service Evaluations: An Educational Review with Recommendations

This article provides an educational review covering the consideration of conducting ‘value for money’ analyses as part of non-randomised study designs including service evaluations. These evaluations represent a vehicle for producing evidence such as value for money of a care intervention or service delivery model. Decision makers including charities and local and national governing bodies often rely on evidence from non-randomised data and service evaluations to inform their resource allocation decision-making. However, as randomised data obtained from randomised controlled trials are considered the ‘gold standard’ for assessing causation, the use of this alternative vehicle for producing an evidence base requires careful consideration. We refer to value for money analyses, but reflect on methods associated with economic evaluations as a form of analysis used to inform resource allocation decision-making alongside a finite budget. Not all forms of value for money analysis are considered a full economic evaluation with implications for the information provided to decision makers. The type of value for money analysis to be conducted requires considerations such as the outcome(s) of interest, study design, statistical methods to control for confounding and bias, and how to quantify and describe uncertainty and opportunity costs to decision makers in any resulting value for money estimates. Service evaluations as vehicles for producing evidence present different challenges to analysts than what is commonly associated with research, randomised controlled trials and health technology appraisals, requiring specific study design and analytic considerations. This educational review describes and discusses these considerations, as overlooking them could affect the information provided to decision makers who may make an ‘ill-informed’ decision based on ‘poor’ or ‘inaccurate’ information with long-term implications. We make direct comparisons between randomised controlled trials relative to non-randomised data as vehicles for assessing causation; given ‘gold standard’ randomised controlled trials have limitations. Although we use UK-based decision makers as examples, we reflect on the needs of decision makers internationally for evidence-based decision-making specific to resource allocation. We make recommendations based on the experiences of the authors in the UK, reflecting on the wide variety of methods available, used as documented in the empirical literature. These methods may not have been fully considered relevant to non-randomised study designs and/or service evaluations, but could improve and aid the analysis conducted to inform the relevant value for money decision problem.

Determining accurate costs for genomic sequencing technologies-a necessary prerequisite

Genome sequencing (GS) is increasingly being translated into clinical practice and is a technology characterized by a complex multi-step workflow. Funding decisions for GS would be aided by formal economic evaluation of GS platforms, but these analyses require detailed costing. This article addresses the importance of and challenges associated with costing GS using a GS microcosting project in autism spectrum disorder as an illustrative example.

Application of Economic Evaluation to Assess Feasibility for Reimbursement of Genomic Testing as Part of Personalized Medicine Interventions

Background: The incorporation of genomic testing into clinical practice constitutes an opportunity to improve patients' lives, as it makes possible the implementation of innovative, individualized clinical interventions that maximize efficacy and/or minimize the risk of adverse drug reactions. In order to ensure equal access to genomic testing for all patients, the costs associated with these tests should be reimbursed by their respective national healthcare systems. Given that funding for the public health sector is decreasing in real terms, it is of paramount importance that the emerging interventions are thoroughly evaluated both in terms of their clinical effectiveness and their full economic cost. Objective: The aim of this study was to identify those genome-guided interventions that could be adopted and reimbursed by national healthcare systems. Further, we recorded the underlying factors determining the broad adoption of genome-guided interventions in clinical practice, in order to identify potential reimbursement criteria. Methods: We performed a systematic review of published (PubMed-listed) scientific articles on the economic evaluation of those individualized clinical interventions that include genomic tests. Information on genomic tests reimbursed by the US Medicare program was also included. Subsequently, we correlated the regulatory guidance given for the interventions collated in our systematic review with the corresponding economic evaluation results and policies of the Medicare program. Regulatory guidance information was collected from the PharmGKB online knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC). Results: Most of the included studies constitute cost-utility analyses, in which the outcome of the interventions has been measured in quality-adjusted life years (QALYs) whereas an estimate of the total cost has been based upon direct medical cost data. Favorable economic evaluation results, as well as concrete evidence demonstrating the clinical utility of pre-emptive genotyping, are considered as prerequisites for the broad adoption and reimbursement of the costs incurred during genomic testing. Indicatively, pre-emptive HLA-B*5701 and TPMT testing before administration of abacavir and azathioprine, respectively, is reimbursed by Medicare based on both economic and efficacy evidence. Likewise, the medical necessary screening for MMR and BRCA1/2 genes are reimbursed for high-risk populations. Conclusions: Our findings further underline the need for further cost-utility analyses within different national healthcare systems, in order to promote the reimbursement of the cost of innovative genome-guided therapeutic interventions.

The complete costs of genome sequencing: a microcosting study in cancer and rare diseases from a single center in the United Kingdom

Purpose

The translation of genome sequencing into routine health care has been slow, partly because of concerns about affordability. The aspirational cost of sequencing a genome is $1000, but there is little evidence to support this estimate. We estimate the cost of using genome sequencing in routine clinical care in patients with cancer or rare diseases.

Methods

We performed a microcosting study of Illumina-based genome sequencing in a UK National Health Service laboratory processing 399 samples/year. Cost data were collected for all steps in the sequencing pathway, including bioinformatics analysis and reporting of results. Sensitivity analysis identified key cost drivers.

Results

Genome sequencing costs £6841 per cancer case (comprising matched tumor and germline samples) and £7050 per rare disease case (three samples). The consumables used during sequencing are the most expensive component of testing (68–72% of the total cost). Equipment costs are higher for rare disease cases, whereas consumable and staff costs are slightly higher for cancer cases.

Conclusion

The cost of genome sequencing is underestimated if only sequencing costs are considered, and likely surpasses $1000/genome in a single laboratory. This aspirational sequencing cost will likely only be achieved if consumable costs are considerably reduced and sequencing is performed at scale.

Allocating healthcare resources to genomic testing in Canada: latest evidence and current challenges

Precision medicine (PM) informed by next-generation sequencing (NGS) poses challenges for health technology assessment (HTA). To date, there has been limited reimbursement of genomic testing with NGS in Canada, particularly for whole-genome and whole-exome sequencing (WGS/WES). Through a structured literature review, we examine Canadian economic evidence and evidentiary challenges for the adoption of genomic testing. We searched Medline (PubMed) for published Canadian studies generating economic evidence for PM informed by NGS. Our search focused on studies examining the costs and/or value of NGS. We reviewed included studies and summarized results according to evaluation type, clinical context, NGS technology, and test strategy. We then grouped HTA challenges encountered by authors when evaluating NGS. Our review included twenty-five studies. To determine the economic impacts of NGS-informed PM in Canada, studies applied cost-effectiveness analysis (52%, n = 13), stated preference analysis (20%, n = 5), cost-consequence analysis (16%, n = 4), and healthcare resource utilization or costing analysis (12%, n = 3). NGS panels were the most common technology evaluated (n = 13), followed by WGS and/or WES (n = 8). The included studies highlighted multiple challenges when generating economic evidence, many of which remain unaddressed. Challenges were broadly related to (1) accounting for all NGS outcomes; (2) addressing uncertainty; and (3) improving consistency of economic approaches. Canadian studies are beginning to produce estimates of the economic impacts of NGS-informed PM, yet challenges for HTA remain. While solutions and real-world evidence are generated, lifecycle health technology management methods can be designed to better support resource allocation decisions for genomic testing in Canada.

Generic Cost-Effectiveness Models: A Proof of Concept of a Tool for Informed Decision-Making for Public Health Precision Medicine

BACKGROUND/AIMS

Economic evaluation is integral to informed public health decision-making in the rapidly growing field of precision and personalized medicine (PM); however, this research requires specialized expertise and significant resources. Generic models are a novel innovation to efficiently address a critical PM evidence shortage and implementation barrier by enabling use of population-specific input values. This is a generic PM economic evaluation model proof-of-concept study for a pharmacogenomic use case.

METHODS

An 8-step generic economic model development process was applied to the use case of human leukocyte antigen (HLA)-B*15:02genotyping for prediction of carbamazepine-induced cutaneous reactions, with a user-friendly decision-making tool relying on user-provided input values. This generic model was transparently documented and validated, including cross-validation comparing cost-effectiveness results with 3 country-specific models.

RESULTS

A generic pharmacogenomic use case cost-effectiveness model with decision-making tool was successfully developed and cross-validated using input values for 6 populations which produced consistent results for HLA-B*15:02 screening at country-specific cost-effectiveness threshold values. Differences between the generic and country-specific model results were largely due to differences in model structure and assumptions.

CONCLUSION

This proof on concept demonstrates the feasibility of generic models to provide useful PM economic evidence, supporting their use as a pragmatic and timely approach to address a growing need.

Clinical Application of Genome and Exome Sequencing as a Diagnostic Tool for Pediatric Patients: a Scoping Review of the Literature

PURPOSE

Availability of clinical genomic sequencing (CGS) has generated questions about the value of genome and exome sequencing as a diagnostic tool. Analysis of reported CGS application can inform uptake and direct further research. This scoping literature review aims to synthesize evidence on the clinical and economic impact of CGS.

METHODS

PubMed, Embase, and Cochrane were searched for peer-reviewed articles published between 2009 and 2017 on diagnostic CGS for infant and pediatric patients. Articles were classified according to sample size and whether economic evaluation was a primary research objective. Data on patient characteristics, clinical setting, and outcomes were extracted and narratively synthesized.

RESULTS

Of 171 included articles, 131 were case reports, 40 were aggregate analyses, and 4 had a primary economic evaluation aim. Diagnostic yield was the only consistently reported outcome. Median diagnostic yield in aggregate analyses was 33.2% but varied by broad clinical categories and test type.

CONCLUSION

Reported CGS use has rapidly increased and spans diverse clinical settings and patient phenotypes. Economic evaluations support the cost-saving potential of diagnostic CGS. Multidisciplinary implementation research, including more robust outcome measurement and economic evaluation, is needed to demonstrate clinical utility and cost-effectiveness of CGS.

The Future of Precision Medicine: Potential Impacts for Health Technology Assessment

OBJECTIVE

Precision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies.

METHODS

We performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research.

RESULTS

We identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects.

DISCUSSION

Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.

A Practical First Step Using Needs Assessment and a Survey Approach to Implementing a Clinical Pharmacogenomics Consult Service

Introduction

Genetic-guided selection of non-oncologic medications is not commonly practiced in general, and at University of California, San Francisco (UCSF) Health, specifically. Understanding the unique position of clinicians with respect to clinical pharmacogenetics (PG) at a specific institution or practice is fundamental for implementing a successful PG consult service.

Objectives

To assess clinicians' current practices, needs, and interests with respect to clinical PG at UCSF Health, a large tertiary academic medical center.

Methods

A list of 42 target medications with clinical PG recommendations was complied. Clinical specialties that routinely used the target medications were identified. A 12-question survey focused on practice of PG for target medications was developed. Pharmacists and physicians were surveyed anonymously in several clinical specialties. Survey results were analyzed using descriptive statistics.

Results

Of the 396 clinicians surveyed, 76 physicians and 59 pharmacists participated, resulting in 27% and 50% average response rates, respectively. The current use of PG in clinical practice for physicians and pharmacists was 29% and 32%, respectively, however this number varied across clinical specialties from 0% to 80%. Of clinicians whom reported they do not currently apply PG, 63% of physicians and 54% of pharmacists expressed interest in integrating PG. However, the level of interest varied from 20% to 100% across specialties. Of the respondents, 64% of physicians and 56% of pharmacists elected to provide contact information to investigators to further discuss their interest related to clinical PG.

Conclusions

While PG is not uniformly practiced at UCSF Health, there is considerable interest in utilizing PG by the respondents. Our approach was successful at identifying clinicians and services interested in PG for specific drug-gene pairs. This work has set a foundation for next steps to advance PG integration at UCSF Health. Clinicians can adopt our approach as preliminary work to build a clinical PG program at their institutions.

Methodological Issues in Assessing the Economic Value of Next-Generation Sequencing Tests: Many Challenges and Not Enough Solutions

BACKGROUND

Clinical use of next-generation sequencing (NGS) tests has been increasing, but few studies have examined their economic value. Several studies have noted that there are methodological challenges to conducting economic evaluations of NGS tests.

OBJECTIVE

Our objective was to examine key methodological challenges for conducting economic evaluations of NGS tests, prioritize these challenges for future research, and identify how studies have attempted solutions to address these challenges.

METHODS

We identified challenges for economic evaluations of NGS tests using prior literature and expert judgment of the co-authors. We used a modified Delphi assessment to prioritize challenges, based on importance and probability of resolution. Using a structured literature review and article extraction we then assessed whether published economic evaluations had addressed these challenges.

RESULTS

We identified 11 challenges for conducting economic evaluations of NGS tests. The experts identified three challenges as the top priorities for future research: complex model structure, timeframe, and type of analysis and comparators used. Of the 15 published studies included in our literature review, four studies described specific solutions relevant to five of the 11 identified challenges.

CONCLUSIONS

Major methodological challenges to economic evaluations of NGS tests remain to be addressed. Our results can be used to guide future research and inform decision-makers on how to prioritize research on the economic assessment of NGS tests.

EVIDENCE REQUIRED BY HEALTH TECHNOLGY ASSESSMENT AND REIMBURSEMENT BODIES EVALUATING DIAGNOSTIC OR PROGNOSTIC ALGORITHMS THAT INCLUDE OMICS DATA

OBJECTIVES

Multi-analyte assays with algorithmic analyses (MAAAs) use combinations of circulating and clinical markers including omics-based sources for diagnostic and/or prognostic purposes. Assessing MAAAs is challenging under existing health technology assessment (HTA) methods or practices. We undertook a scoping review to explore the HTA methods used for MAAAs to identify the criteria used for clinical research and reimbursement purposes.

METHODS

This review included only non-companion (stand-alone) tests that are actionable and that have been evaluated by leading HTA or insurer/reimbursement bodies up to September 2017.

RESULTS

Twenty-five reports and articles evaluating seventeen MAAAs were examined, most of which have been developed in oncology. The two main models used were the EUnetHTA Core model and the Evaluation of Genomic Applications in Practice and Prevention ACCE framework. Clinical validity and utility criteria were used, as were economic, ethical, legal, and social aspects. Economic evidence on MAAAs was scarce, and there is no consensus on whether the perspectives used are sufficiently broad to include all relevant stakeholders.

CONCLUSIONS

Clinical utility and efficiency were the most used criteria, with stronger evidence needed linking the use of the algorithm with the clinical outcomes in real-life practice. HTA bodies must as well consider questions related to the analytical validity of MAAAs or with organizational aspects. The two main models, the EUnetHTA Core model and the ACCE framework, could be adapted to the assessment of MAAAs.

Cost-effectiveness analyses of genetic and genomic diagnostic tests

Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests compete with traditional approaches to diagnosis, including the genetic testing of single genes and other clinical strategies, for finite health-care budgets. In this context, decision analytic model-based cost-effectiveness analysis is a useful method to help evaluate the costs versus consequences of introducing new health-care interventions. This Perspective presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of health-care resources to obtain robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.