Budget Impact of Belantamab Mafodotin (Belamaf) Adoption in the Treatment of Patients with Relapsed or Refractory Multiple Myeloma in the United States.

PURPOSE: Estimate the budget impact of belantamab mafodotin (belamaf) for patients with relapsed/refractory multiple myeloma (RRMM) who have received ≥4 prior therapies, including an anti-CD38 monoclonal antibody, a proteasome inhibitor, and an immunomodulatory agent. METHODS: A budget impact analysis (BIA) was developed to estimate the cost difference between current (no belamaf) and projected (with belamaf) market scenarios over 3 years. Comparators were identified from a systematic literature review and included selinexor + dexamethasone or best supportive care. The number of treatment-eligible patients were estimated using an epidemiology model. Base-case analyses were conducted from a US commercial payer perspective (cost year: 2019). Model inputs included market share estimates, treatment duration, and costs of drug acquisition/administration, concomitant medications, adverse event (AE) management, treatment monitoring, and subsequent treatments based on published literature/cost databases. Budget impact, calculated as the difference in costs between current and projected scenarios over 3 years, was reported as cost per member per month (PMPM) and per member per year (PMPY). One-way sensitivity analysis assessed which key parameters most affected model outcomes. Alternative scenarios were tested (1- or 5-year time horizon; Medicare perspective; negligible cost of mental status change AE). RESULTS: In a hypothetical commercial payer health plan with 1 million members, 33 patients were identified as treatment-eligible over 3 years. Introducing belamaf for patients with RRMM resulted in an estimated budget-neutral PMPM cost of -$0.0003 and PMPY of -$0.004, based on n=9/33 patients receiving treatment. Sensitivity analyses showed that budget impact in the base case was most sensitive to changes in treatment duration and drug acquisition costs. Base-case results were consistent across all scenarios assessed. CONCLUSION: BIA indicates that adoption of belamaf in this patient population would be budget neutral for a US health plan.

Application of Constrained Optimization Methods in Health Services Research: Report 2 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

BACKGROUND: Constrained optimization methods are already widely used in health care to solve problems that represent traditional applications of operations research methods, such as choosing the optimal location for new facilities or making the most efficient use of operating room capacity. OBJECTIVES: In this paper we illustrate the potential utility of these methods for finding optimal solutions to problems in health care delivery and policy. To do so, we selected three award-winning papers in health care delivery or policy development, reflecting a range of optimization algorithms. Two of the three papers are reviewed using the ISPOR Constrained Optimization Good Practice Checklist, adapted from the framework presented in the initial Optimization Task Force Report. The first case study illustrates application of linear programming to determine the optimal mix of screening and vaccination strategies for the prevention of cervical cancer. The second case illustrates application of the Markov Decision Process to find the optimal strategy for treating type 2 diabetes patients for hypercholesterolemia using statins. The third paper (described in Appendix 1) is used as an educational tool. The goal is to describe the characteristics of a radiation therapy optimization problem and then invite the reader to formulate the mathematical model for solving it. This example is particularly interesting because it lends itself to a range of possible models, including linear, nonlinear, and mixed-integer programming formulations. From the case studies presented, we hope the reader will develop an appreciation for the wide range of problem types that can be addressed with constrained optimization methods, as well as the variety of methods available. CONCLUSIONS: Constrained optimization methods are informative in providing insights to decision makers about optimal target solutions and the magnitude of the loss of benefit or increased costs associated with the ultimate clinical decision or policy choice. Failing to identify a mathematically superior or optimal solution represents a missed opportunity to improve economic efficiency in the delivery of care and clinical outcomes for patients. The ISPOR Optimization Methods Emerging Good Practices Task Force's first report provided an introduction to constrained optimization methods to solve important clinical and health policy problems. This report also outlined the relationship of constrained optimization methods relative to traditional health economic modeling, graphically illustrated a simple formulation, and identified some of the major variants of constrained optimization models, such as linear programming, dynamic programming, integer programming, and stochastic programming. The second report illustrates the application of constrained optimization methods in health care decision making using three case studies. The studies focus on determining optimal screening and vaccination strategies for cervical cancer, optimal statin start times for diabetes, and an educational case to invite the reader to formulate radiation therapy optimization problems. These illustrate a wide range of problem types that can be addressed with constrained optimization methods.

The Cost-effectiveness of Sequences of Biological Disease-modifying Antirheumatic Drug Treatment in England for Patients with Rheumatoid Arthritis Who Can Tolerate Methotrexate.

OBJECTIVE: To ascertain whether strategies of treatment with a biological disease-modifying antirheumatic drug (bDMARD) are cost-effective in an English setting. Results are presented for those patients with moderate to severe rheumatoid arthritis (RA) and those with severe RA. METHODS: An economic model to assess the cost-effectiveness of 7 bDMARD was developed. A systematic literature review and network metaanalysis was undertaken to establish relative clinical effectiveness. The results were used to populate the model, together with estimates of Health Assessment Questionnaire (HAQ) score following European League Against Rheumatism response; annual costs, and utility, per HAQ band; trajectory of HAQ for patients taking bDMARD; and trajectory of HAQ for patients using nonbiologic therapy (NBT). Results were presented as those associated with the strategy with the median cost-effectiveness. Supplementary analyses were undertaken assessing the change in cost-effectiveness when only patients with the most severe prognoses taking NBT were provided with bDMARD treatment. The costs per quality-adjusted life-year (QALY) values were compared with reported thresholds from the UK National Institute for Health and Care Excellence of £20,000 to £30,000 (US$24,700 to US$37,000). RESULTS: In the primary analyses, the cost per QALY of a bDMARD strategy was £41,600 for patients with severe RA and £51,100 for those with moderate to severe RA. Under the supplementary analyses, the cost per QALY fell to £25,300 for those with severe RA and to £28,500 for those with moderate to severe RA. CONCLUSION: The cost-effectiveness of bDMARD in RA in England is questionable and only meets current accepted levels in subsets of patients with the worst prognoses.

Health state utility values for diabetic retinopathy: protocol for a systematic review and meta-analysis.

BACKGROUND: People with diabetic retinopathy tend to have lower levels of health-related quality of life than individuals with no retinopathy. Strategies for screening and treatment have been shown to be cost-effective. In order to reduce the bias in cost-effectiveness estimates, systematic reviews of health state utility values (HSUVs) are crucial for health technology assessment and the development of decision analytic models. A review and synthesis of HSUVs for the different stages of disease progression in diabetic retinopathy has not previously been conducted. METHODS/DESIGN: We will conduct a systematic review of the available literature that reports HSUVs for people with diabetic retinopathy, in correspondence with current stage of disease progression and/or visual acuity. We will search Medline, EMBASE, Web of Science, Cost-Effectiveness Analysis Registry, Centre for Reviews and Dissemination Database, and EconLit to identify relevant English-language articles. Data will subsequently be synthesized using linear mixed effects modeling meta-regression. Additionally, reported disease severity classifications will be mapped to a four-level grading scale for diabetic retinopathy. DISCUSSION: The systematic review and meta-analysis will provide important evidence for future model-based economic evaluations of technologies for diabetic retinopathy. The meta-regression will enable the estimation of utility values at different disease stages for patients with particular characteristics and will also highlight where the design of the study and HSUV instrument have influenced the reported utility values. We believe this protocol to be the first of its kind to be published. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42014012891.

Cost-effectiveness of combination nonbiologic disease-modifying antirheumatic drug strategies in patients with early rheumatoid arthritis.

OBJECTIVE: To compare the costs and benefits of alternative combination strategies of disease-modifying antirheumatic drugs (DMARD) and DMARD monotherapy in patients with early, active rheumatoid arthritis (RA). METHODS: Data were drawn from randomized controlled trials that compared DMARD monotherapy or any DMARD combination strategy, with or without combined steroid therapy. Mixed treatment comparison methods were used to estimate the relative effectiveness of the different strategies. A mathematical model was developed to compare the longterm costs and benefits of the alternative strategies, combining data from a variety of sources. Costs were considered from a health sector viewpoint and benefits were expressed in terms of quality-adjusted life-years (QALY). RESULTS: If decision makers use a threshold of £20,000 (US$29,000) per QALY, then the strategies most likely to be cost-effective are either DMARD combination therapy with downward titration (probability of being optimal = 0.50) or intensive, triple DMARD combination therapy (probability of being optimal = 0.43). The intensive DMARD strategy generated an additional cost of £27,392 per additional QALY gained compared to the downward titration strategy. Other combination strategies were unlikely to be considered cost-effective compared to DMARD monotherapy. Results were robust to a range of scenario sensitivity analyses. CONCLUSION: Combination DMARD therapy is likely to be cost-effective compared to DMARD monotherapy where treatment entails rapid downward dose titration or intensive, triple DMARD therapy.

Bridging the gap between methods research and the needs of policy makers: a review of the research priorities of the National Institute for Health and Clinical Excellence.

OBJECTIVES: The aim of this study was to establish a list of priority topics for methods research to support decision making at the National Institute for Health and Clinical Excellence (NICE). METHODS: Potential priorities for methods research topics were identified through a focused literature review, interviews, an email survey, a workshop and a Web-based feedback exercise. Participants were members of the NICE secretariat and its advisory bodies, representatives from academia, industry, and other organizations working closely with NICE. The Web exercise was open to anyone to complete but publicized among the above groups. RESULTS: A list of potential topics was collated. Priorities for further research differed according to the type of respondent and the extent to which they work directly with NICE. Priorities emerging from the group closest to NICE included: methodology for indirect and mixed treatment comparisons; synthesis of qualitative evidence; research relating to the use of quality-adjusted life-years (QALYs) in decision making; methods and empirical research for establishing the cost-effectiveness threshold; and determining how data on the uncertainty of effectiveness and cost-effectiveness data should be taken into account in the decision-making process. Priorities emerging from the broadest group of respondents (through the Web exercise) included: methods for extrapolating beyond evidence observed in trials, methods for capturing benefits not included in the QALY and methods to assess when technologies should be recommended in the context of further evidence gathering. CONCLUSIONS: Consideration needs to be given to the needs of those who use the outputs of research for decision making when determining priorities for future methods research.

Utility values in National Institute for Health and Clinical Excellence (NICE) Technology Appraisals.

OBJECTIVE: To review the selection and use of health-related utility values for economic models included in National Institute for Health and Clinical Excellence (NICE) Technology Appraisals. METHOD: A cross-sectional review of reports of economic models submitted to the Technology Appraisals program was undertaken to review the health-related utility data included. Data reviewed included identification and selection of data and the methods used for utility elicitation. The methods used were compared with those from the 2004 Methods Guide issued by NICE. RESULTS: Appraisals conducted after the implementation of the NICE 2004 Methods Guide were reviewed. After exclusion of documents that did not include a de novo cost-utility analysis, 71 submissions (53 manufacturer submissions, 18 assessment group reports) from 39 appraisals were identified, containing 284 unique utility values. Variation was found in the selection, elicitation, valuation, and use of the utility values. Thirty-nine submissions (55%) took utility values from published studies, of which only 31% were identified through a systematic review. Forty-seven (66%) submissions contained health state descriptions reported by patients, and 55 (77%) submissions applied a valuation set derived from the general population. The EQ-5D was used in 35 (49%) submissions, and mapping to a generic health-related quality of life measure was performed in 19 (27%) submissions. CONCLUSIONS: Only 56% of submissions to NICE and assessment reports included utility values that met the NICE 2004 reference case. This highlights variation in the methods used to select and incorporate utility values in economic models for NICE Technology Appraisals.