Estimating the Allocation of the Economic Value Generated by Utilization of All-Oral Direct-Acting Antivirals for Hepatitis C in the United States, 2015 to 2019.

OBJECTIVES: Between 2013 to 2019, several all-oral direct-acting antivirals (DAAs) were launched with the potential to cure patients with hepatitis C virus (HCV). They generated economic value in terms of the health gains for patients and cost-savings for the US healthcare system. We estimated the share of this value allocated to 4 manufacturers vs society. METHODS: For 2015 to 2019, we estimated the incremental impact of DAAs on HCV health outcomes and costs. We used the Center for Disease Analysis Foundation Polaris Observatory database to estimate utilization. Per-patient projections of lifetime quality-adjusted life-years (QALYs) gained and medical costs avoided were based on a standard 9-state HCV disease-progression model for DAA treatment vs alternatives. Annual QALY gains were valued at $114 000 per QALY. Outcomes and costs were discounted at 3%. Estimated revenues were based on reported sales. RESULTS: An estimated 1 080 000 patients received DAAs: 81.5% would not have received the pre-DAA standard of care. On average, these patients were projected to gain 4.4 QALYs and save $104 400 in lifetime healthcare costs, generating $531.8 billion in value. Those who would have received treatment gained 1.7 QALYs and saved $41 500 in lifetime costs, generating $47.4 billion in economic value. As treatment costs fell nearly 75%, the 4 manufacturers reported $37.4 billion from DAA sales-an allocation of 6.5% of the total value. CONCLUSIONS: The significant majority (∼90%) of the economic value of curing HCV with DAAs were health benefits to patients and net cost-savings to society. DAA manufacturers received a minority share (6.5%) of the aggregate economic value generated.

Evolving Evidence-Based Value Assessment of One-Time Therapies: Tisagenlecleucel as a Case Study.

BACKGROUND: Economic evaluation of one-time therapies during reimbursement decision-making is challenging due to uncertain long-term outcomes. The availability of 5-year outcome data from the ELIANA trial and real-world evidence of tisagenlecleucel, the first chimeric antigen receptor T-cell (CAR-T) therapy, presents an opportunity to re-evaluate the predictions of prior cost-effectiveness analyses (CEAs). OBJECTIVE: To conduct a systematic literature review (SLR) of prior CEAs of tisagenlecleucel for pediatric/young adult relapsed or refractory acute lymphoblastic leukemia (r/r ALL) and evaluate the impact of recently available 5-year efficacy data from ELIANA and advances in CAR-T manufacturing in an updated CEA model. METHODS: OVID MEDLINE/Embase and health technology assessment (HTA) databases were searched for full-text economic evaluations in English reporting cost-effectiveness results for tisagenlecleucel for r/r ALL. Evaluations with publicly reported incremental cost-effectiveness ratios (ICERs) were included in the SLR. Study screening and data abstraction were conducted following PRISMA guidelines. Data extracted included the country/currency, perspective, clinical trial evidence, model structures, long-term efficacy extrapolation approaches (i.e., overall survival [OS]), time horizon, discount rates, and outcomes (i.e., life years [LY], quality-adjusted LY [QALY], and ICERs). The CEA model reported in Wakase et al. was updated using 5-year OS data from ELIANA and the CAR-T infusion rate informed by real-world practice. RESULTS: Sixteen records corresponding to 15 unique studies were included in the SLR (11 publications and 5 HTA reports); all were conducted from the health care system perspective of the respective countries. Most studies found tisagenlecleucel to be cost effective, but all studies' projected 3- and 5-year OS rates for tisagenlecleucel were lower than the observed 3- and 5-year rates, respectively, derived from 5-year ELIANA data. When applying updated OS projections from the most recent ELIANA data cut and higher infusion rates of 92.5% (per the real-world infusion rate)-96.0% (per the manufacturer success rate) to the CEA of Wakase et al., the associated QALYs for tisagenlecleucel increased from 11.6 to 14.6-15.0, and LYs increased from 13.3 to 17.0-17.5. Accordingly, the ICERs for tisagenlecleucel decreased from ¥2,035,071 to ¥1,787,988-¥1,789,048 versus blinatumomab and from ¥2,644,702 to ¥2,257,837-¥2,275,181 versus clofarabine combination therapy in the updated CEA model. CONCLUSIONS AND RELEVANCE: Projections at launch of the likely cost effectiveness of tisagenlecleucel appear to have underestimated its ultimate economic value given more recent trial and real-world data. To balance uncertainty in initial valuation with the need to provide access to novel oncology therapies, payers can consider flexible reimbursement policies alongside ongoing assessments as new data emerge.

New Vaccine Platforms-Novel Dimensions of Economic and Societal Value and Their Measurement.

The COVID-19 pandemic's dramatic impact has been a vivid reminder that vaccines-especially in the context of infectious respiratory viruses-provide enormous societal value, well beyond the healthcare system perspective which anchors most Health Technology Assessment (HTA) and National Immunization Technical Advisory Group (NITAG) evaluation frameworks. Furthermore, the development of modified ribonucleic acid-based (mRNA-based) and nanoparticle vaccine technologies has brought into focus several new value drivers previously absent from the discourse on vaccines as public health interventions such as increased vaccine adaptation capabilities, the improved ability to develop combination vaccines, and more efficient vaccine manufacturing and production processes. We review these novel value dimensions and discuss how they might be measured and incorporated within existing value frameworks using existing methods. To realize the full potential of next-generation vaccine platforms and ensure their widespread availability across populations and health systems, it is important that value frameworks utilized by HTAs and NITAGs properly reflect the full range of benefits for population health and well-being and cost efficiencies that these new vaccines platforms provide.

The evolving value assessment of cancer therapies: Results from a modified Delphi study.

The move toward early detection and treatment of cancer presents challenges for value assessment using traditional endpoints. Current cancer management rarely considers the full economic and societal benefits of therapies. Our study used a modified Delphi process to develop principles for defining and assessing value of cancer therapies that aligns with the current trajectory of oncology research and reflects broader notions of value. 24 experts participated in consensus-building activities across 5 months (16 took part in structured interactions, including a survey, plenary sessions, interviews, and off-line discussions, while 8 participated in interviews). Discussion focused on: 1) which oncology-relevant endpoints should be used for assessing treatments for early-stage cancer and access decisions for early-stage treatments, and 2) the importance of additional value components and how these can be integrated in value assessments. The expert group reached consensus on 4 principles in relation to the first area (consider oncology-relevant endpoints other than overall survival; build evidence for endpoints that provide earlier indication of efficacy; develop evidence for the next generation of predictive measures; use managed entry agreements supported by ongoing evidence collection to address decision-maker evidence needs) and 3 principles in relation to the second (routinely use patient reported outcomes in value assessments; assess broad economic impact of new medicines; consider other value aspects of relevance to patients and society).

Using Patient Preferences in Health Technology Assessment: Evaluating Quality-Adjusted Survival Equivalents (QASE) for the Quantification of Non-health Benefits.

Interest in using patient preference (PP) data alongside traditional economic models in health technology assessment (HTA) is growing, including using PP data to quantify non-health benefits. However, this is limited by a lack of standardised methods. In this article, we describe a method for using discrete choice experiment (DCE) data to estimate the value of non-health benefits in terms of quality-adjusted survival equivalence (QASE), which is consistent with the concept of value prevalent among HTA agencies. We describe how PP data can be used to estimate QASE, assess the ability to test the face-validity of QASE estimates of changes in mode of administration calculated from five published DCE oncology studies and review the methodological and normative considerations associated with using QASE to support HTA. We conclude that QASE may have some methodological advantages over alternative methods, but this requires DCEs to estimate second-order effects between length and quality of life. In addition, empirical work has yet to be undertaken to substantiate this advantage and demonstrate the validity of QASE. Further work is also required to align QASE with normative objectives of HTA agencies. Estimating QASE would also have implications for the conduct of DCEs, including standardising and defining more clear attribute definitions.

Evidence Synthesis and Linkage for Modelling the Cost-Effectiveness of Diagnostic Tests: Preliminary Good Practice Recommendations.

OBJECTIVES: To develop preliminary good practice recommendations for synthesising and linking evidence of treatment effectiveness when modelling the cost-effectiveness of diagnostic tests. METHODS: We conducted a targeted review of guidance from key Health Technology Assessment (HTA) bodies to summarise current recommendations on synthesis and linkage of treatment effectiveness evidence within economic evaluations of diagnostic tests. We then focused on a specific case study, the cost-effectiveness of troponin for the diagnosis of myocardial infarction, and reviewed the approach taken to synthesise and link treatment effectiveness evidence in different modelling studies. RESULTS: The Australian and UK HTA bodies provided advice for synthesising and linking treatment effectiveness in diagnostic models, acknowledging that linking test results to treatment options and their outcomes is common. Across all reviewed models for the case study, uniform test-directed treatment decision making was assumed, i.e., all those who tested positive were treated. Treatment outcome data from a variety of sources, including expert opinion, were utilised for linked clinical outcomes. Preliminary good practice recommendations for data identification, integration and description are proposed. CONCLUSION: Modelling the cost-effectiveness of diagnostic tests poses unique challenges in linking evidence on test accuracy to treatment effectiveness data to understand how a test impacts patient outcomes and costs. Upfront consideration of how a test and its results will likely be incorporated into patient diagnostic pathways is key to exploring the optimal design of such models. We propose some preliminary good practice recommendations to improve the quality of cost-effectiveness evaluations of diagnostics tests going forward.

Incorporating Real Option Value in Valuing Innovation: A Way Forward.

BACKGROUND: Considerable progress has been made in defining and measuring the real option value (ROV) of medical technologies. However, questions remain on how to estimate (1) ROV outside of life-extending oncology interventions; (2) the impact of ROV on costs and cost effectiveness; and (3) potential interactions between ROV and other elements of value. METHODS: We developed a 'minimal modeling' approach for estimating the size of ROV that does not require constructing a full, formal cost-effectiveness model. We proposed a qualitative approach to assessing the level of uncertainty in the ROV estimate. We examined the potential impact of ROV on the incremental cost-effectiveness ratio as well as on the potential interactions between ROV and other elements of value. Lastly, we developed and presented a 15-item checklist for reporting ROV in value assessment. RESULTS: The minimal modeling approach uses estimates on the efficacy of current treatment and potential future innovation, as well as success rate and length of new treatment development, and can be applied to all types of ROV across disease areas. ROV may interact with the conventional value, value of hope, productivity effects, and insurance value. The impact of ROV on cost effectiveness can be evaluated via threshold analysis. CONCLUSION: The minimal modeling approach and the checklist developed in this paper simplifies and standardizes the estimation and reporting of ROV in value assessment. Systematically including and reporting ROV in value assessment will minimize bias and improve transparency, which will help improve the credibility of ROV research and acceptance by stakeholders.

Is the price right? Paying for value today to get more value tomorrow.

BACKGROUND: Contemporary debates about drug pricing feature several widely held misconceptions, including the relationship between incentives and innovation, the proportion of total healthcare spending on pharmaceuticals, and whether the economic evaluation of a medicine can be influenced by things other than clinical efficacy. MAIN BODY: All citizens should have access to timely, equitable, and cost-effective care covered by public funds, private insurance, or a combination of both. Better managing the collective burden of diseases borne by today's and future generations depends in part on developing better technologies, including better medicines. As in any innovative industry, the expectation of adequate financial returns incentivizes innovators and their investors to develop new medicines. Estimating expected returns requires that they forecast revenues, based on the future price trajectory and volume of use over time. How market participants decide what price to set or accept can be complicated, and some observers and stakeholders want to confirm whether the net prices society pays for novel medicines, whether as a reward for past innovation or an incentive for future innovation, are commensurate with those medicines' incremental value. But we must also ask "value to whom?"; medicines not only bring immediate clinical benefits to patients treated today, but also can provide a broad spectrum of short- and long-term benefits to patients, their families, and society. Spending across all facets of healthcare has grown over the last 25 years, but both inpatient and outpatient spending has outpaced drug spending growth even as our drug armamentarium is constantly improving with safer and more effective medicines. In large part, this is because, unlike hospitals, drugs typically go generic, thus making room in our budgets for new and better ones, even as they often keep patients out of hospitals, driving further savings. CONCLUSION: A thorough evaluation of drug spending and value can help to promote a better allocation of healthcare resources for both the healthy and the sick, both of whom must pay for healthcare. Taking a holistic approach to assessing drug value makes it clear that a branded drug's value to a patient is often only a small fraction of the drug's total value to society. Societal value merits consideration when determining whether and how to make a medicine affordable and accessible to patients: a drug that is worth its price to society should not be rendered inaccessible to ill patients by imposing high out-of-pocket costs or restricting coverage based on narrow health technology assessments (HTAs). Furthermore, recognizing the total societal cost of un- or undertreated conditions is crucial to gaining a thorough understanding of what guides the biomedical innovation ecosystem to create value for society. It would be unwise to discourage the development of new solutions without first appreciating the cost of leaving the problems unsolved.

Evaluating Policies of Expanding Versus Restricting First-Line Treatment Choices: A Cost-Effectiveness Analysis Framework.

OBJECTIVES: Healthcare payers often implement coverage policies that restrict the utilization of costly new first-line treatments. Cost-effectiveness analysis can be conducted to inform these decisions by comparing the new treatment with an existing one. However, this approach may overlook important factors such as treatment effect heterogeneity and endogenous treatment selection, policy implementation costs, and diverse patient preferences across multiple treatment options. We aimed to develop a cost-effectiveness analysis framework that considers these real-world factors, facilitating the evaluation of alternative policies related to expanding or restricting first-line treatment choices. METHODS: We introduced a metric of incremental cost-effectiveness ratio (ICER) that compares an expanded choice set (CS) including the new first-line treatment with a restricted CS excluding the new treatment. ICER(CS) accounts for treatment selection influenced by heterogeneous treatment effects and policy implementation costs. We examined a basic scenario with 2 standard first-line treatment choices and a more realistic scenario involving diverse preferences toward multiple choices. To illustrate the framework, we conducted a retrospective evaluation of including versus excluding abiraterone acetate plus prednisone (AAP) (androgen deprivation therapy [ADT] + AAP) as a first-line treatment for metastatic hormone-sensitive prostate cancer. RESULTS: The traditional ICERs for ADT + AAP versus ADT alone and ADT+ docetaxel were $104 269 and $206 324/quality-adjusted life-year, respectively. The ICER(CS) for comparing an expanded CS with ADT + AAP with a restricted CS without ADT + AAP was $123 179/quality-adjusted life-year. CONCLUSIONS: The proposed framework provides decision makers with policy-relevant tools, enabling them to assess the cost-effectiveness of alternative policies of expanding versus restricting patients' and physicians' first-line treatment choices.

The value of the accelerated approval pathway: real-world outcomes associated with reducing the time between innovations.

Aim: We investigated the effect of shortening time between innovations with the accelerated approval (AA) pathway on patient outcomes for three solid tumors. Methods: This real-world analysis evaluated patients receiving sequential AA pathway-approved innovations after initial treatment with existing therapies in three solid tumor case studies. Outcomes attributable to AA were estimated and assumed approval occurred at the time of conversion to approval and extrapolated to the US population. Results: Survival gains from accessing innovative therapies were 2.3-3.8-times higher when using the AA pathway. At the US population level, AA was associated with ∼8000 life-years gained across all three tumor case studies. Conclusion: In areas of rapid clinical development, the value of existing therapies can be enhanced by earlier access to AA pathway innovations and should be considered when evaluating the AA program.

What is this study about? The US Food and Drug Administration's accelerated approval pathway provides patients with access to innovative drugs sooner than standard regulatory pathways. Using three case studies in solid tumors, this study measured how many patients on current cancer drugs received future cancer drugs because of the accelerated approval pathway and asked whether quicker access to new drugs resulted in them living longer. What were the results? In three cancer case studies, the accelerated approval pathway led to more patients receiving future cancer drugs. Patients who received future drugs through the AA pathway lived longer than patients who did not have access to them. What do the results of the study mean? The accelerated approval pathway is important because it can improve outcomes of current cancer drugs by giving patients additional treatments to choose from in the future and therefore a chance to live longer. Policymakers should consider this when thinking about making changes to the accelerated approval pathway.

Distributional Cost-Effectiveness Analysis of Treatments for Non-Small Cell Lung Cancer: An Illustration of an Aggregate Analysis and its Key Drivers.

BACKGROUND AND OBJECTIVE: Distributional cost-effectiveness analysis (DCEA) facilitates quantitative assessments of how health effects and costs are distributed among population subgroups, and of potential trade-offs between health maximisation and equity. Implementation of DCEA is currently explored by the National Institute for Health and Care Excellence (NICE) in England. Recent research conducted an aggregate DCEA on a selection of NICE appraisals; however, significant questions remain regarding the impact of the characteristics of the patient population (size, distribution by the equity measure of interest) and methodologic choices on DCEA outcomes. Cancer is the indication most appraised by NICE, and the relationship between lung cancer incidence and socioeconomic status is well established. We aimed to conduct an aggregate DCEA of two non-small cell lung cancer (NSCLC) treatments recommended by NICE, and identify key drivers of the analysis. METHODS: Subgroups were defined according to socioeconomic deprivation. Data on health benefits, costs, and target populations were extracted from two NICE appraisals (atezolizumab versus docetaxel [second-line treatment following chemotherapy to represent a broad NSCLC population] and alectinib versus crizotinib [targeted first-line treatment to represent a rarer mutation-positive NSCLC population]). Data on disease incidence were derived from national statistics. Distributions of population health and health opportunity costs were taken from the literature. A societal welfare analysis was conducted to assess potential trade-offs between health maximisation and equity. Sensitivity analyses were conducted, varying a range of parameters. RESULTS: At an opportunity cost threshold of £30,000 per quality-adjusted life-year (QALY), alectinib improved both health and equity, thereby increasing societal welfare. Second-line atezolizumab involved a trade-off between improving health equity and maximising health; it improved societal welfare at an opportunity cost threshold of £50,000/QALY. Increasing the value of the opportunity cost threshold improved the equity impact. The equity impact and societal welfare impact were small, driven by the size of the patient population and per-patient net health benefit. Other key drivers were the inequality aversion parameters and the distribution of patients by socioeconomic group; skewing the distribution to the most (least) deprived quintile improved (reduced) equity gains. CONCLUSION: Using two illustrative examples and varying model parameters to simulate alternative decision problems, this study suggests that key drivers of an aggregate DCEA are the opportunity cost threshold, the characteristics of the patient population, and the level of inequality aversion. These drivers raise important questions in terms of the implications for decision making. Further research is warranted to examine the value of the opportunity cost threshold, capture the public's views on unfair differences in health, and estimate robust distributional weights incorporating the public's preferences. Finally, guidance from health technology assessment organisations, such as NICE, is needed regarding methods for DCEA construction and how they would interpret and incorporate those results in their decision making.

Estimating the Lifetime Medical Cost Burden of an Allogeneic Hematopoietic Cell Transplantation Patient.

Allogeneic hematopoietic cell transplantation (allo-HCT) has the potential for curative outcomes for a variety of hematologic malignancies. Current allo-HCT studies often describe the outcomes and costs in the near term; however, research on the lifetime economic burden post-allo-HCT remains limited. This study was conducted to estimate the average total lifetime direct medical costs of an allo-HCT patient and the potential net monetary savings from an alternative treatment associated with improved graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS). A disease-state model was constructed using a short-term decision tree and a long-term semi-Markov partitioned survival model to estimate the average per-patient lifetime cost and expected quality-adjusted life years (QALYs) for an allo-HCT patient from a US healthcare system perspective. Key clinical inputs included overall survival, GRFS, incidence of both acute and chronic GVHD, relapse of the primary disease, and infections. Cost results were reported as ranges based on varying the percentage of chronic GVHD patients that remained on treatment after 2 years (15% or 39%). Over a lifetime, the average per-patient medical cost of allo-HCT was estimated to range from $942,373 to $1,247,917. The majority of the costs were for chronic GVHD treatment (37% to 53%), followed by the allo-HCT procedure (15% to 19%). The expected lifetime QALYs of an allo-HCT patient were estimated as 4.7. Lifetime per-patient treatment costs often exceed $1,000,000 for allo-HCT patients. Innovative research efforts focused on the reduction or elimination of late complications, particularly chronic GVHD, may provide the greatest value to improved patient outcomes.

Assessing the potential cost-effectiveness of centralised versus point-of-care testing for hepatitis C virus in Pakistan: a model-based comparison.

OBJECTIVES: Pakistan has a hepatitis C virus (HCV) infection prevalence of 6%-9% and aims to achieve World Health Organisation (WHO) targets for elimination of HCV by the year 2030. We aim to evaluate the potential cost-effectiveness of a reference laboratory-based (centralised laboratory testing; CEN) confirmatory testing approach versus a molecular near-patient point-of-care (POC) confirmatory approach to screen the general population for HCV in Pakistan. STUDY DESIGN: We used a decision tree-analytic model from a governmental (formal healthcare sector) perspective. STUDY SETTING: Individuals were assumed to be initially screened with an anti-HCV test at home, followed by POC nucleic acid test (NAT) at nearby district hospitals or followed by NAT at centralised laboratories. PARTICIPANTS: We included the general testing population for chronic HCV in Pakistan. INTERVENTION: Screening with an anti-HCV antibody test (Anti-HCV) followed by either POC NAT (Anti-HCV-POC), or reference laboratory NAT (Anti-HCV-CEN), was compared, using data from published literature and the Pakistan Ministry of Health. MEASURES: Outcome measures included: number of HCV infections identified per year, percentage of individuals correctly classified, total costs, average costs per individual tested, and cost-effectiveness (assessed as cost per additional HCV infection identified). Sensitivity analysis was also performed. RESULTS: At a national level (25 million annual screening tests), the Anti-HCV-CEN strategy would identify 142 406 more HCV infections in 1 year and increase correct classification of individuals by 0.57% compared with the Anti-HCV-POC strategy. The total annual cost of HCV testing was reduced using the Anti-HCV-CEN strategy by US$7.68 million (US$0.31/person). Thus, incrementally, the Anti-HCV-CEN strategy costs less and identifies more HCV infections than Anti-HCV-POC. The incremental difference in HCV infections identified was most sensitive to the probability of loss to follow-up (for POC confirmatory NAT). CONCLUSIONS: Anti-HCV-CEN would provide the best value for money when scaling up HCV testing in Pakistan.

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.

Estimating the Potential Economic Impact of Tissue Valve Replacement for Heart Valve Disease in China: Patient-Level and Population-Level Cost-Benefit Simulation Analyses.

OBJECTIVES: This study seeks to estimate the potential societal economic impact of treating patients with heart valve disease (HVD) in China with surgical tissue valve replacement versus mechanical valves. METHODS: This societal economic cost-benefit evaluation is based on an individual simulation model for subgroups of patients with HVD that is also aggregated to a macrosocietal model. The individual simulation model was developed to estimate the likely economic impact of surgical aortic valve replacement (SAVR) with tissue versus mechanical valves for different subgroups among all eligible patients with HVD over their remaining lifetimes. Clinical inputs were informed by health claims database analysis, expert clinical opinion, and published literature. Epidemiological inputs and demographic inputs were sourced from the published literature and the China Statistical Yearbook 2020. Health gains were valued at 3 times the average national income. RESULTS: Projected total lifetime economic gains were greater for patients receiving tissue valves. Costs were reported in 2021 US dollars. The average lifetime net economic gain for tissue valve patients was $51 736 (20.0% more than for mechanical valve patients). Increasing the use of tissue valves to 50% among all eligible patients with HVD would provide aggregate long-term economic gains of $167 billion during their remaining lifetimes. The economic gains from greater tissue valve use were due to avoiding anticoagulation monitoring costs, improved quality of life, and greater post-SAVR labor force participation. CONCLUSION: Increased use of tissue valves versus mechanical values in SAVR procedures in China would be likely to generate a substantial societal economic gain.

Value-Based Pricing for Patent-Protected Medicines Over the Product Life Cycle: Pricing Anomalies in the "Age of Cures" and Their Implications for Dynamic Efficiency.

OBJECTIVES: Conventional cost-effectiveness analysis (CEA) for the value-based pricing of new medicines largely ignores the implications of limited market exclusivity (ie, patent-protection periods plus any exclusivity granted by regulators). This paper explores the implications of this methodological shortcoming, which produces several pricing anomalies with potentially unintended effects on research and development (R&D) incentives. METHODS: We illustrate these implications by comparing 4 stylized examples of increasing complexity, from short-term cures for acute conditions to long-term cures for rare, health-catastrophic conditions. RESULTS: (1) Conventional-CEA will project a different result than an adjusted CEA that considers generic or biosimilar entry; (2) free and flexible pricing of long-term treatments (eg, statins for hypercholesterolemia) or repeated-dose cures (eg, insulin for type 1 diabetes) for chronic conditions will likely result in predictable price increases at the end of the exclusivity period that may be perceived as unjustified or unsupported; and (3) one-time administration "cures" (eg, gene therapy for spinal muscular atrophy) have the potential to allocate a large share of the social surplus to the manufacturer over the product lifetime, which may or may not be dynamically efficient per se, but may also inadvertently disadvantage the development of valuable long-term treatments or repeated-dose cures for chronic conditions. CONCLUSIONS: We highlight the need for additional research on long-term solutions to these issues that would aim to promote dynamically efficient global R&D. More work is needed on the following: (1) relationships between social surplus allocation and the amount and composition of global R&D, as we may be as likely to be encouraging excessive R&D in some areas as to be undersupplying it in others; and (2) relating the size of the surplus reward to R&D cost and, thus, the return on investment.

Value Insider Season 1 Episode 5: What Other Aspects of Value May Be Relevant? (Societal Impact) [Podcast].

What other aspects of value may be relevant? In this episode of the Value Insider podcast, host Mike Chambers speaks with Prof. Lou Garrison about the societal perspective on value of healthcare interventions. Prof. Garrison is Professor Emeritus in The Comparative Health Outcomes, Policy, and Economics institute (CHOICE) in the School of Pharmacy at the University of Washington. Lou is past president of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and he is currently co-chair of its Policy Outlook Committee. Going beyond the "conventional" elements of value assessment, Prof. Garrison highlights which additional impacts may be at play. He shares his concept of the "Value Flower", explaining elements such as insurance value and scientific spill-over.

Does Clinical Evidence of Heterogeneity Impact Treatment Selection? A Case Study of Abiraterone for Metastatic Prostate Cancer.

BACKGROUND: Two pivotal randomized controlled trials (RCTs) demonstrate that abiraterone acetate + prednisone (AAP) combined with androgen deprivation therapy (ADT) significantly extends the survival of men with metastatic hormone-sensitive prostate cancer (mHSPC) compared with ADT alone. Their subgroup analyses indicate that the survival benefit is significant for younger men but not older men. We aimed to assess whether publication of the RCTs was associated with differential real-world AAP utilization by age groups. METHODS: Using TriNetX electronic medical records data collected from 43 healthcare organizations across the United States, we performed a difference-in-differences event study among men with newly diagnosed mHSPC observed from June 2014 to June 2019. Eligible subjects were identified based on a comprehensive published algorithm. We analyzed the change in utilization rate of AAP before versus after publication of the RCTs among men aged <70 years versus ≥70 years, adjusting for demographic factors and clinical conditions. RESULTS: Our study included 6,888 men with newly diagnosed mHSPC with 12,738 observations, of whom 46% were aged <70 years. The prepublication trends of AAP utilization were similar between the age groups, whereas publication of the RCTs was associated with a 3.5% higher adjusted uptake rate of AAP among younger men (95% CI, 1.2%-5.8%) relative to older men. This estimate reflects an uptake rate nearly 3 times higher than would have been expected had younger men followed the same utilization trends as older men. The estimates remained consistent throughout the postpublication period. CONCLUSIONS: Our study suggests that publication of the RCTs was associated with faster uptake of AAP among younger versus older men with newly diagnosed mHSPC, despite the absence of clinical guidance for differential treatment selection. This finding highlights the importance of confirmatory studies among older men, considering the uncertainties of subgroup analyses in RCTs.

Assessing the Cost-effectiveness of a Hypothetical Disease-modifying Therapy With Limited Duration for the Treatment of Early Symptomatic Alzheimer Disease.

PURPOSE: Clinical trials have produced promising results for disease-modifying therapies (DMTs) for Alzheimer's disease (AD); however, the evidence on their potential cost-effectiveness is limited. This study assesses the cost-effectiveness of a hypothetical DMT with a limited treatment duration in AD. METHODS: We developed a Markov state-transition model to estimate the cost-effectiveness of a hypothetical DMT plus best supportive care (BSC) versus BSC alone among Americans living with mild cognitive impairment (MCI) due to AD or mild AD. AD states included MCI due to AD, mild AD, moderate AD, severe AD, and death. A hypothetical DMT was assumed to confer a 30% reduction in progression from MCI and mild AD. The base case annual drug acquisition cost was assumed to be $56,000. Other medical and indirect costs were obtained from published literature or list prices. Utilities for patients and caregivers were obtained from the published literature and varied by AD state and care setting (community care or long-term care). We considered 3 DMT treatment strategies: (1) treatment administered until patients reached severe AD (continuous strategy), (2) treatment administered for a maximum duration of 18 months or when patients reached severe AD (fixed-duration strategy), and (3) 40% of patients discontinuing treatment at 6 months because of amyloid plaque clearance and the remaining patients continuing treatment until 18 months or until they reached severe AD (test-and-discontinue strategy). Incremental cost-effectiveness ratios (ICERs) were calculated as the incremental cost per quality-adjusted life-year (QALY) gained. FINDINGS: From the health care sector perspective, continuous treatment with a hypothetical DMT versus BSC resulted in an ICER of $612,354 per QALY gained. The ICER decreased to $157,288 per QALY gained in the fixed-duration strategy, driven by large reductions in treatment costs. With 40% of patients discontinuing treatment at 6 months (test-and-discontinue strategy), the ICER was $125,631 per QALY gained. In sensitivity and scenario analyses, the ICER was the most sensitive to changes in treatment efficacy, treatment cost, and the initial population AD state distribution. From the modified societal perspective, ICERs were 6.3%, 20.4%, and 25.1% lower than those from the health care sector perspective for the continuous, fixed-duration, and test-and-discontinue strategies, respectively. IMPLICATIONS: Under a set of assumptions for annual treatment costs and the magnitude and duration of treatment efficacy, DMTs used for a limited duration may deliver value consistent with accepted US cost-effectiveness thresholds.