A review of economic issues for gene-targeted therapies: Value, affordability, and access.

The National Center for Advancing Translational Sciences' virtual 2021 conference on gene-targeted therapies (GTTs) encouraged multidisciplinary dialogue on a wide range of GTT topic areas. Each of three parallel working groups included social scientists and clinical scientists, and the three major sessions included a presentation on economic issues related to their focus area. These experts also coordinated their efforts across the three groups. The economics-related presentations covered three areas with some overlap: (1) value assessment, uncertainty, and dynamic efficiency; (2) affordability, pricing, and financing; and (3) evidence generation, coverage, and access. This article provides a synopsis of three presentations, some of their key recommendations, and an update on related developments in the past year. The key high-level findings are that GTTs present unique data and policy challenges, and that existing regulatory, health technology assessment, as well as payment and financing systems will need to adapt. But these adjustments can build on our existing foundation of regulatory and incentive systems for innovation, and much can be done to accelerate progress in GTTs. Given the substantial unmet medical need that exists for these oft-neglected patients suffering from rare diseases, it would be a tragedy to not leverage these exciting scientific advances in GTTs.

Opportunities, resources, and techniques for implementing genomics in clinical care.

Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.

Use of Real-World Evidence in US Payer Coverage Decision-Making for Next-Generation Sequencing-Based Tests: Challenges, Opportunities, and Potential Solutions.

OBJECTIVES: Given the potential of real-world evidence (RWE) to inform understanding of the risk-benefit profile of next-generation sequencing (NGS)-based testing, we undertook a study to describe the current landscape of whether and how payers use RWE as part of their coverage decision making and potential solutions for overcoming barriers. METHODS: We performed a scoping literature review of existing RWE evidentiary frameworks for evaluating new technologies and identified barriers to clinical integration and evidence gaps for NGS. We synthesized findings as potential solutions for improving the relevance and utility of RWE for payer decision-making. RESULTS: Payers require evidence of clinical utility to inform coverage decisions, yet we found a relatively small number of published RWE studies, and these are predominately focused on oncology, pharmacogenomics, and perinatal/pediatric testing. We identified 3 categories of innovation that may help address the current undersupply of RWE studies for NGS: (1) increasing use of RWE to inform outcomes-based contracting for new technologies, (2) precision medicine initiatives that integrate clinical and genomic data and enable data sharing, and (3) Food and Drug Administration reforms to encourage the use of RWE. Potential solutions include development of data and evidence review standards, payer engagement in RWE study design, use of incentives and partnerships to lower the barriers to RWE generation, education of payers and providers concerning the use of RWE and NGS, and frameworks for conducting outcomes-based contracting for NGS. CONCLUSIONS: We provide numerous suggestions to overcome the data, methodologic, infrastructure, and policy challenges constraining greater integration of RWE in assessments of NGS.

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.

Payer decision making for next-generation sequencing-based genetic tests: insights from cell-free DNA prenatal screening.

PURPOSE: Cell-free DNA (cfDNA) prenatal screening tests have been rapidly adopted into clinical practice, due in part to positive insurance coverage. We evaluated the framework payers used in making coverage decisions to describe a process that should be informative for other sequencing tests. METHODS: We analyzed coverage policies from the 19 largest US private payers with publicly available policies through February 2016, building from the University of California San Francisco TRANSPERS Payer Coverage Policy Registry. RESULTS: All payers studied cover cfDNA screening for detection of trisomies 21, 18, and 13 in high-risk, singleton pregnancies, based on robust clinical validity (CV) studies and modeled evidence of clinical utility (CU). Payers typically evaluated the evidence for each chromosomal abnormality separately, although results are offered as part of a panel. Starting in August 2015, 8 of the 19 payers also began covering cfDNA screening in average-risk pregnancies, citing recent CV studies and updated professional guidelines. Most payers attempted, but were unable, to independently assess analytic validity (AV). CONCLUSION: Payers utilized the standard evidentiary framework (AV/CV/CU) when evaluating cfDNA screening but varied in their interpretation of the sufficiency of the evidence. Professional guidelines, large CV studies, and decision analytic models regarding health outcomes appeared highly influential in coverage decisions.Genet Med advance online publication 22 September 2016.

Making genomic medicine evidence-based and patient-centered: a structured review and landscape analysis of comparative effectiveness research.

Comparative effectiveness research (CER) in genomic medicine (GM) measures the clinical utility of using genomic information to guide clinical care in comparison to appropriate alternatives. We summarized findings of high-quality systematic reviews that compared the analytic and clinical validity and clinical utility of GM tests. We focused on clinical utility findings to summarize CER-derived evidence about GM and identify evidence gaps and future research needs. We abstracted key elements of study design, GM interventions, results, and study quality ratings from 21 systematic reviews published in 2010 through 2015. More than half (N = 13) of the reviews were of cancer-related tests. All reviews identified potentially important clinical applications of the GM interventions, but most had significant methodological weaknesses that largely precluded any conclusions about clinical utility. Twelve reviews discussed the importance of patient-centered outcomes, although few described evidence about the impact of genomic medicine on these outcomes. In summary, we found a very limited body of evidence about the effect of using genomic tests on health outcomes and many evidence gaps for CER to address.Genet Med advance online publication 13 April 2017.

Payer Coverage for Hereditary Cancer Panels: Barriers, Opportunities, and Implications for the Precision Medicine Initiative.

Background: Hereditary cancer panels (HCPs), testing for multiple genes and syndromes, are rapidly transforming cancer risk assessment but are controversial and lack formal insurance coverage. We aimed to identify payers' perspectives on barriers to HCP coverage and opportunities to address them. Comprehensive cancer risk assessment is highly relevant to the Precision Medicine Initiative (PMI), and payers' considerations could inform PMI's efforts. We describe our findings and discuss them in the context of PMI priorities. Methods: We conducted semi-structured interviews with 11 major US payers, covering >160 million lives. We used the framework approach of qualitative research to design, conduct, and analyze interviews, and used simple frequencies to further describe findings. Results: Barriers to HCP coverage included poor fit with coverage frameworks (100%); insufficient evidence (100%); departure from pedigree/family history-based testing toward genetic screening (91%); lacking rigor in the HCP hybrid research/clinical setting (82%); and patient transparency and involvement concerns (82%). Addressing barriers requires refining HCP-indicated populations (82%); developing evidence of actionability (82%) and pathogenicity/penetrance (64%); creating infrastructure and standards for informing and recontacting patients (45%); separating research from clinical use in the hybrid clinical-research setting (44%); and adjusting coverage frameworks (18%). Conclusions: Leveraging opportunities suggested by payers to address HCP coverage barriers is essential to ensure patients' access to evolving HCPs. Our findings inform 3 areas of the PMI: addressing insurance coverage to secure access to future PMI discoveries; incorporating payers' evidentiary requirements into PMI's research agenda; and leveraging payers' recommendations and experience to keep patients informed and involved.

Decision Making on Medical Innovations in a Changing Health Care Environment: Insights from Accountable Care Organizations and Payers on Personalized Medicine and Other Technologies.

BACKGROUND: New payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs. OBJECTIVES: To understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations. METHODS: We interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis. RESULTS: We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs' decision making in terms of achieving a balance between the components of the Triple Aim-improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs' decisions and ACOs' insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients' interest in personalized medicine. CONCLUSIONS: As new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations.

EXAMINING EVIDENCE IN U.S. PAYER COVERAGE POLICIES FOR MULTI-GENE PANELS AND SEQUENCING TESTS.

OBJECTIVES: The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions. METHODS: We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study. RESULTS: Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73-100 percent), clinical studies in 69 percent (50-87 percent), technology assessments 47 percent (33-86 percent), systematic reviews or meta-analyses 31 percent (7-71 percent), and CEAs 5 percent (0-7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types. CONCLUSIONS: Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.

Generating and evaluating evidence of the clinical utility of molecular diagnostic tests in oncology.

PURPOSE: Enthusiasm for molecular diagnostic (MDx) testing in oncology is constrained by the gaps in required evidence regarding its impact on patient outcomes (clinical utility (CU)). This effectiveness guidance document proposes recommendations for the design and evaluation of studies intended to reflect the evidence expectations of payers, while also reflecting information needs of patients and clinicians. METHODS: Our process included literature reviews and key informant interviews followed by iterative virtual and in-person consultation with an expert technical working group and an advisory group comprising life-sciences industry experts, public and private payers, patients, clinicians, regulators, researchers, and other stakeholders. RESULTS: Treatment decisions in oncology represent high-risk clinical decision making, and therefore the recommendations give preference to randomized controlled trials (RCTs) for demonstrating CU. The guidance also describes circumstances under which alternatives to RCTs could be considered, specifying conditions under which test developers could use prospective-retrospective studies with banked biospecimens, single-arm studies, prospective observational studies, or decision-analytic modeling techniques that make a reasonable case for CU. CONCLUSION: Using a process driven by multiple stakeholders, we developed a common framework for designing and evaluating studies of the clinical validity and CU of MDx tests, achieving a balance between internal validity of the studies and the relevance, feasibility, and timeliness of generating the desired evidence.Genet Med 18 8, 780-787.

Economic opportunities and challenges for pharmacogenomics.

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

Getting our priorities straight: a novel framework for stakeholder-informed prioritization of cancer genomics research.

PURPOSE: Prioritization of translational research on genomic tests is critically important given the rapid pace of innovation in genomics. The goal of this study was to evaluate a stakeholder-informed priority-setting framework in cancer genomics. METHODS: An external stakeholder advisory group including patients/consumers, payers, clinicians, and test developers used a modified Delphi approach to prioritize six candidate cancer genomic technologies during a 1-day meeting. Nine qualitative priority-setting criteria were considered. We used a directed, qualitative content-analysis approach to investigate the themes of the meeting discussion. RESULTS: Stakeholders primarily discussed six of the original nine criteria: clinical benefits, population health impacts, economic impacts, analytical and clinical validity, clinical trial implementation and feasibility, and market factors. Several new priority-setting criteria were identified from the workshop transcript, including "patient-reported outcomes," "clinical trial ethics," and "trial recruitment." The new criteria were incorporated with prespecified criteria to develop a novel priority-setting framework. CONCLUSION: This study highlights key criteria that stakeholders can consider when prioritizing comparative effectiveness research for cancer genomic applications. Applying an explicit priority-setting framework to inform investment in comparative effectiveness research can help to ensure that critical factors are weighed when deciding between many potential research questions and trial designs.

Payer reimbursement practices and incentives for improving interpretation of germline genetic testing.

Germline genetic testing for inherited cancer risk has shifted to multi-gene panel tests (MGPTs). While MGPTs detect more pathogenic variants, they also detect more variants of uncertain significance (VUSs) that increase the possibility of harms such as unnecessary surgery. Data sharing by laboratories is critical to addressing the VUS problem. However, barriers to sharing and an absence of incentives have limited laboratory contributions to the ClinVar database. Payers can play a crucial role in the expansion of knowledge and effectiveness of genetic testing. Current policies affecting MGPT reimbursement are complex and create perverse incentives. Trends in utilization and coverage for private payers and Medicare illustrate opportunities and challenges for data sharing to close knowledge gaps and improve clinical utility. Policy options include making data sharing (i) a condition of payment, and (ii) a metric of laboratory quality in payment contracts, yielding preferred coverage or enhanced reimbursement. Mandating data sharing sufficient to verify interpretations and resolve discordance among labs under Medicare and federal health programs is an option for the US Congress. Such policies can reduce the current waste of valuable data needed for precision oncology and improved patient outcomes, enabling a learning health system.

Stakeholder assessment of the evidence for cancer genomic tests: insights from three case studies.

PURPOSE: Insufficient evidence on the net benefits and harms of genomic tests in real-world settings is a translational barrier for genomic medicine. Understanding stakeholders' assessment of the current evidence base for clinical practice and coverage decisions should be a critical step in influencing research, policy, and practice. METHODS: Twenty-two stakeholders participated in a workshop exploring the evidence of genomic tests for clinical and coverage decision making. Stakeholders completed a survey prior to and during the meeting. They also discussed if they would recommend for or against current clinical use of each test. RESULTS: At baseline, the level of confidence in the clinical validity and clinical utility of each test varied, although the group expressed greater confidence for epidermal growth factor receptor mutation and Lynch syndrome testing than for Oncotype DX. Following the discussion, survey results reflected even less confidence for Oncotype DX, intermediate levels of confidence for [corrected] epidermal growth factor receptor mutation testing and stable levels of confidence [corrected] for Lynch syndrome testing. The majority of stakeholders would consider clinical use for all three tests, but under the conditions of additional research or a shared clinical decision-making approach. CONCLUSION: Stakeholder engagement in unbiased settings is necessary to understand various perspectives about evidentiary thresholds in genomic medicine. Participants recommended the use of various methods for evidence generation and synthesis.

Prioritization in comparative effectiveness research: the CANCERGEN Experience.

BACKGROUND: Systematic approaches to stakeholder-informed research prioritization are a central focus of comparative effectiveness research. Genomic testing in cancer is an ideal area to refine such approaches given rapid innovation and potentially significant impacts on patient outcomes. OBJECTIVE: To develop and pilot test a stakeholder-informed approach to prioritizing genomic tests for future study in collaboration with the cancer clinical trials consortium SWOG. METHODS: We conducted a landscape analysis to identify genomic tests in oncology using a systematic search of published and unpublished studies, and expert consultation. Clinically valid tests suitable for evaluation in a comparative study were presented to an external stakeholder group. Domains to guide the prioritization process were identified with stakeholder input, and stakeholders ranked tests using multiple voting rounds. RESULTS: A stakeholder group was created including representatives from patient-advocacy groups, payers, test developers, regulators, policy makers, and community-based oncologists. We identified 9 domains for research prioritization with stakeholder feedback: population impact; current standard of care, strength of association; potential clinical benefits, potential clinical harms, economic impacts, evidence of need, trial feasibility, and market factors. The landscape analysis identified 635 studies; of 9 tests deemed to have sufficient clinical validity, 6 were presented to stakeholders. Two tests in lung cancer (ERCC1 and EGFR) and 1 test in breast cancer (CEA/CA15-3/CA27.29) were identified as top research priorities. CONCLUSIONS: Use of a diverse stakeholder group to inform research prioritization is feasible in a pragmatic and timely manner. Additional research is needed to optimize search strategies, stakeholder group composition, and integration with existing prioritization mechanisms.