Does Real Option Value Influence Oncologists' Treatment Recommendations? A Survey of US Oncologists.

OBJECTIVES: Survival benefit from anticancer treatments, even if modest, improves a patient's chances of accessing future innovations, thereby creating real option value. There is no empirical evidence on the impact of potential future innovations on oncologists' treatment recommendations. METHODS: We conducted a national online survey of practicing medical and hematological oncologists. We presented a hypothetical metastatic cancer patient with median survival of 6 months under 4 decision-making scenarios with varying expected efficacy and time to arrival of future innovations. We assessed the likelihood of discussing future innovations with their patients and the likelihood that future innovations would influence their current treatment recommendation, as well as factors associated with these 2 outcomes using multivariate logistic regressions. RESULTS: A total of 201 oncologists completed the survey. When future innovations were expected to improve survival by 6 months and be available in 6 months, 76% of oncologists were likely or very likely to discuss the innovations with their patients, and 68% reported they would influence their current treatment recommendations. A 1-month increase in the expected survival improvement of future innovation was associated with a 1.17 greater odds (95% CI 1.1-1.25) of reporting likely or very likely to discuss future innovations with their patients, whereas a 1-month increase in the expected time to arrival was associated with a 0.91 lower odds (95% CI 0.88-0.94). CONCLUSIONS: Given that potential future innovations seem to influence oncologists' treatments recommendations, evidence to inform clinical guidelines and value assessments should consider data on real option value impacts to support informed treatment decision making.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

Modeling the Ex Ante Clinical Real Option Value in an Innovative Therapeutic Area: ALK-Positive Non-Small-Cell Lung Cancer.

OBJECTIVES: A drug that improves survival and/or disease progression can create real option value (ROV)-the additional health gain from future innovations enabled by a longer survival. ROV can be a relevant consideration for both clinical and payer decision-makers. We aimed to estimate the ex ante ROV for first-line (1L) alectinib in anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC). METHODS: We developed a Markov model to estimate life-years (LYs) and quality-adjusted life-years (QALYs) gained with 1L alectinib versus 1L crizotinib due to potential future second-line (2L) drugs. Transition probabilities were derived from the phase 3 trial of 1L alectinib and phase 2 trial of 2L brigatinib. We identified drugs being studied in phase 2 and 3 trials in ALK-positive NSCLC at the time of alectinib's 1L approval and projected the likelihood and timing of their arrival and their potential efficacy based on publicly available data. RESULTS: The discounted incremental LYs and QALYs for alectinib increased by 12.9% (95% CR - 2.96%, 34.82%; 1.25 vs. 1.11) and 11.2% (95% CR - 2.14%, 29.29%; 1.03 vs. 0.92), respectively, after accounting for ROV. The incremental ROV of alectinib was sensitive to the projected efficacy of future drugs, uptake level, and the hazard ratio of progression-free survival of alectinib (vs. crizotinib). CONCLUSIONS: Ex ante ROV can be a significant value consideration in therapeutic areas with high levels of expected innovation. The potential efficacy of future drugs and incremental survival with alectinib at the projected time of arrival are important considerations in assessing ROV.

Modeling the Ex Post Real Option Value in Metastatic Melanoma Using Real-World Data.

OBJECTIVES: Real option value (ROV) is created when a drug enables a patient to live long enough to benefit from a future innovation. Few studies have quantified ROV in the real world. We aimed to estimate the ex post ROV for ipilimumab in metastatic melanoma using real-world data (RWD). METHODS: We developed a framework for calculating ROV using RWD, accounting for the health gain in the standard therapy arm and the uptake of future innovations. A Markov model was developed to estimate the quality-adjusted life-years (QALYs) gained with ipilimumab compared with chemotherapy for patients with or without subsequent cancer immunotherapy (CIT). A nationwide electronic health record-derived, deidentified database was used to estimate survival and uptake of CIT. RESULTS: The incremental QALYs gained for ipilimumab compared with chemotherapy without subsequent CIT were 1.74. With subsequent CIT, the incremental QALYs compared with chemotherapy increased by 0.92, 0.60, 0.33, 0.18, 0.10, and 0.02 when CIT became available 0, 3, 6, 9, 12, and 24 months after the initiation of first-line treatment, respectively. The results were most sensitive to the survival benefit of ipilimumab, the survival benefit of subsequent CIT, and the uptake of CIT. CONCLUSIONS: This is the first study to estimate ex post ROV using RWD. The ex post ROV was between 1% and 54% of conventional value for patients who received a diagnosis within 2 years before CIT availability. Further studies are needed to understand ROV in other disease areas, particularly those with longer survival times.

Antimicrobial Resistance: Is Health Technology Assessment Part of the Solution or Part of the Problem?

Antimicrobial resistance is a serious challenge to the success and sustainability of our healthcare systems. There has been increasing policy attention given to antimicrobial resistance in the last few years, and increased amounts of funding have been channeled into funding for research and development of antimicrobial agents. Nevertheless, manufacturers doubt whether there will be a market for new antimicrobial technologies sufficient to enable them to recoup their investment. Health technology assessment (HTA) has a critical role in creating confidence that if valuable technologies can be developed they will be reimbursed at a level that captures their true value. We identify 3 deficiencies of current HTA processes for appraising antimicrobial agents: a methods-centric approach rather than problem-centric approach for dealing with new challenges, a lack of tools for thinking about changing patterns of infection, and the absence of an approach to epidemiological risks. We argue that, to play their role more effectively, HTA agencies need to broaden their methodological tool kit, design and communicate their analysis to a wider set of users, and incorporate long-term policy goals, such as containing resistance, as part of their evaluation criteria alongside immediate health gains.

Real-world evidence for option value in metastatic melanoma.

BACKGROUND: The concept of real option value (ROV) suggests there is added value in treatments that extend life because they enable a patient to live long enough to benefit from future innovative treatments. Real-world evidence of this novel value element is scant, limiting its consideration in formal value assessments. OBJECTIVE: To calculate the ROV in clinical practice of ipilimumab for treatment of advanced melanoma, with evaluation of survival until availability of cancer immunotherapy (CIT). METHODS: This was a retrospective analysis of electronic health records from a US nationwide deidentified database including data from approximately 280 cancer clinics. Participants were patients with advanced or metastatic melanoma diagnosed after January 1, 2011, who initiated treatment before April 19, 2015, and were treated with first-line and second-line ipilimumab or chemotherapy, up to availability of CIT. The proportions of patients surviving and receiving CIT and overall survival by line of therapy were calculated. Baseline demographics were used to weight Kaplan-Meier curves using stabilized inverse probability of treatment weighting. ROV was estimated for patients receiving first-line or second-line ipilimumab with or without subsequent CIT and first-line or second-line chemotherapy with or without subsequent CIT. RESULTS: Overall, 721 patients were included in the study, with a total sample size of 733 (12 patients in both groups). For first-line ipilimumab, 50% of patients survived to the availability of CIT, while only 18% of first-line chemotherapy users survived to the same date. For second-line ipilimumab, 37% of patients survived to availability of CIT vs 21% of patients using second-line chemotherapy. 45% of first-line ipilimumab and 52% of second-line ipilimumab patients who survived to the availability date received CIT. ROV for first-line ipilimumab averaged 3.7 months of additional survival, while those who initiated second-line ipilimumab averaged 4.8 months. The combined estimated ROV was 3.9 months. CONCLUSIONS: This study provides real-world evidence of ROV and adds to the growing literature that may support inclusion of this novel value concept for innovative therapies alongside more traditional measures of value. Further evaluation of ROV in clinical areas with varying survival and innovation is warranted. DISCLOSURES: This study was funded by Genentech, Inc., which was involved in conducting the study. Wong and To are employees of Genentech, Inc. Veenstra, Garrison, Li, and Lee have served as consultants to Genentech, Inc. Data were presented at ISPOR 2021; May 17-20, 2021; as a virtual podium presentation.

The challenge of value-based pricing in combination therapy: the case of trastuzumab and pertuzumab in HER2+ metastatic breast cancer.

BACKGROUND: Under current reimbursement (CR) practice even though an add-on drug in a combination therapy may produce marginal value in terms of health gain, the original therapy may also share in the reward for this additional value. We examine an alternative 'marginal value-based reimbursement' (MVBR) model in which an original therapy would not share in the marginal value. METHODS: In a case study for treatment of HER2+ metastatic breast cancer, we computed the incremental cost-effectiveness ratios (ICERs) of adding pertuzumab to trastuzumab and docetaxel (PHT) vs. trastuzumab and docetaxel (HT) under the CR and the MVBR models, respectively. We further estimated the revised cost of pertuzumab under three alternative willingness-to-pay thresholds based on (a) using the current ICER of PHT vs. HT, (b) the historical ICER of HT vs. docetaxel, and (c) applying the oft-used $150,000/quality-adjusted life year (QALY) gained. RESULTS: If reimbursement were changed from CR to MVBR, at the current price of pertuzumab, the ICER would decline from $409,213 to $323,236/QALY gained. If the price were adjusted under the three thresholds, the payment for pertuzumab would be increased by between 32% and 93%. CONCLUSION: The proposed MVBR model would provide a stronger economic incentive to develop add-on drugs.

Current challenges for assessing the long-term clinical benefit of cancer immunotherapy: a multi-stakeholder perspective.

Immuno-oncologics (IOs) differ from chemotherapies as they prime the patient's immune system to attack the tumor, rather than directly destroying cancer cells. The IO mechanism of action leads to durable responses and prolonged survival in some patients. However, providing robust evidence of the long-term benefits of IOs at health technology assessment (HTA) submission presents several challenges for manufacturers. The aim of this article was to identify, analyze, categorize, and further explore the key challenges that regulators, HTA agencies, and payers commonly encounter when assessing the long-term benefits of IO therapies. Insights were obtained from an international, multi-stakeholder steering committee (SC) and expert panels comprising of payers, economists, and clinicians. The selected individuals were tasked with developing a summary of challenges specific to IOs in demonstrating their long-term benefits at HTA submission. The SC and expert panels agreed that standard methods used to assess the long-term benefit of anticancer drugs may have limitations for IO therapies. Three key areas of challenges were identified: (1) lack of a disease model that fully captures the mechanism of action and subsequent patient responses; (2) estimation of longer-term outcomes, including a lack of agreement on ideal methods of survival analyses and extrapolation of survival curves; and (3) data limitations at the time of HTA submission, for which surrogate survival end points and real-world evidence could prove useful. A summary of the key challenges facing manufacturers when submitting evidence at HTA submission was developed, along with further recommendations for manufacturers in what evidence to produce. Despite almost a decade of use, there remain significant challenges around how best to demonstrate the long-term benefit of checkpoint inhibitor-based IOs to HTA agencies, clinicians, and payers. Manufacturers can potentially meet or mitigate these challenges with a focus on strengthening survival analysis methodology. Approaches to doing this include identifying reliable biomarkers, intermediate and surrogate end points, and the use of real-world data to inform and validate long-term survival projections. Wider education across all stakeholders-manufacturers, payers, and clinicians-in considering the long-term survival benefit with IOs is also important.

Development of a Sleep Apnea-Specific Health State Utility Algorithm.

Importance: With the increasing emphasis on economic evaluations, there is a need for additional methods of measuring patient utility in the obstructive sleep apnea population. Objective: To develop and validate a utility scoring algorithm for a sleep apnea-specific quality-of-life instrument. Design, Setting, and Participants: Development and validation were conducted at 2 tertiary referral sleep centers and associated sleep clinics and included patients with newly diagnosed obstructive sleep apnea from a randomized clinical trial and an associated observational cohort study. Baseline participants were randomly divided into a model development group (60%) and a cross-validation group (40%). Main Outcomes and Measures: Utility scoring of the Symptoms of Nocturnal Obstruction and Related Events (SNORE-25) was mapped from the SF-6D utility index through multiple linear regression in the development sample using the Akaike information criterion to determine the best model. Results: A total of 500 participants (development, n = 300; validation, n = 200) were enrolled; the analyzed sample of 500 participants included 295 men (59%), and the mean (SD) age was 48.6 (12.8) years, with a range of 18 to 90 years. The mean (SD) SF-6D utility among participants with untreated sleep apnea was 0.61 (0.08; range, 0.40-0.85) with similar utility across sleep apnea severity groups. The best-fit model (the SNORE Utility Index) was the natural log conversion of the instrument subscales (r2 = 0.32 in the development sample). The SNORE Utility Index retained this association within the validation sample (r2 = 0.33). Conclusions and Relevance: The SNORE Utility Index provides a validated, disease-specific, preference-weighted utility instrument that can be used in future studies of patients with obstructive sleep apnea.

Challenges in assessing the clinical utility and economic value of immune checkpoint inhibitor therapies of Cancer.

Advances in the immunotherapy of cancer have prolonged survival for cancer patients, but the clinical and financial impact of treatments must be considered in determining the overall clinical utility and economic value of therapeutic agents. Quality-adjusted life years and incremental cost-effectiveness ratios are clinical and economic metrics that can be used to evaluate the value of immune checkpoint inhibitors. This Commentary provides perspective on the limitations, benefits, and potential enhancement of this approach to support value-based medicine.

How Does Option Value Affect the Potential Cost-Effectiveness of a Treatment? The Case of Ipilimumab for Metastatic Melanoma.

BACKGROUND: Innovations that extend life can generate option value and cost of experiencing future technologies. OBJECTIVES: To understand how consideration of option value may affect the potential cost-effectiveness of a treatment through a case study of ipilimumab for previously untreated metastatic melanoma. METHODS: We estimated the cost-effectiveness of ipilimumab in 2 scenarios: a conventional scenario, for which we constructed the model using the standard methods that rely on efficacy data directly from the phase III trial of ipilimumab, and an option value scenario, where we incorporated future hypothetical improvements in mortality for metastatic melanoma owing to innovations. We developed 2 approaches to incorporate option value. In the first approach, we forecasted mortality trends based on historical trends from the Surveillance, Epidemiology, and End Results (SEER) Program registry. Alternatively, we identified drugs being studied in clinical trials at the time of ipilimumab's approval on clinicaltrials.gov and estimated their likelihood and timing of approval, potential efficacy, and cost. We accounted for increases in overall cancer treatment cost and unrelated medical cost in the option value scenario. RESULTS: In the option value scenario, using the SEER approach, the incremental quality-adjusted life-years (QALYs) gained and the incremental cost increased by 6.2% and 3.8%, respectively, whereas the incremental cost-effectiveness ratio (ICER) decreased by 2.3% compared with the conventional scenario. Using the clinicaltrials.gov approach, the incremental QALY gained and the incremental cost increased by 7.5% and 7.1%, respectively, whereas the ICER decreased by 0.40%. CONCLUSIONS: We developed generalizable approaches to estimating option value in cost-effectiveness analysis.