Reply to Standaert, B. Comment on "Postma et al. Predicted Public Health and Economic Impact of Respiratory Syncytial Virus Vaccination with Variable Duration of Protection for Adults ≥60 Years in Belgium".

We have read the commentary from Baudouin Standaert [...].

Extrapolation of Survival Data Using a Bayesian Approach: A Case Study Leveraging External Data from Cilta-Cel Therapy in Multiple Myeloma.

INTRODUCTION: Extrapolating long-term overall survival (OS) from shorter-term clinical trial data is key to health technology assessment in oncology. However, extrapolation using conventional methods is often subject to uncertainty. Using ciltacabtagene autoleucel (cilta-cel), a chimeric antigen receptor T-cell therapy for multiple myeloma, we used a flexible Bayesian approach to demonstrate use of external longer-term data to reduce the uncertainty in long-term extrapolation. METHODS: The pivotal CARTITUDE-1 trial (NCT03548207) provided the primary efficacy data for cilta-cel, including a 12-month median follow-up snapshot of OS. Longer-term (48-month median follow-up) survival data from the phase I LEGEND-2 study (NCT03090659) were also available. Twelve-month CARTITUDE-1 OS data were extrapolated in two ways: (1) conventional survival models with standard parametric distributions (uninformed), and (2) Bayesian survival models whose shape prior was informed from 48-month LEGEND-2 data. For validation, extrapolations from 12-month CARTITUDE-1 data were compared with observed 28-month CARTITUDE-1 data. RESULTS: Extrapolations of the 12-month CARTITUDE-1 data using conventional uninformed parametric models were highly variable. Using informative priors from the 48-month LEGEND-2 dataset, the ranges of projected OS at different timepoints were consistently narrower. Area differences between the extrapolation curves and the 28-month CARTITUDE-1 data were generally lower in informed Bayesian models, except for the uninformed log-normal model, which had the lowest difference. CONCLUSIONS: Informed Bayesian survival models reduced variation of long-term projections and provided similar projections as the uninformed log-normal model. Bayesian models generated a narrower and more plausible range of OS projections from 12-month data that aligned with observed 28-month data. TRIAL REGISTRATION: CARTITUDE-1 ClinicalTrials.gov identifier, NCT03548207. LEGEND-2 ClinicalTrials.gov identifier, NCT03090659, registered retrospectively on 27 March 2017, and ChiCTR-ONH-17012285.

Predicted Public Health and Economic Impact of Respiratory Syncytial Virus Vaccination with Variable Duration of Protection for Adults ≥60 Years in Belgium.

Respiratory syncytial virus (RSV) is a leading cause of acute respiratory infection (ARI) in older adults. This study used a static, cohort-based decision-tree model to estimate the public health and economic impact of vaccination against RSV in Belgians aged ≥60 years compared with no vaccination for different vaccine duration of protection profiles from a healthcare payer perspective. Three vaccine protection durations were compared (1, 3, and 5 years), and several sensitivity and scenario analyses were performed. Results showed that an RSV vaccine with a 3-year duration of protection would prevent 154,728 symptomatic RSV-ARI cases, 3688 hospitalizations, and 502 deaths over three years compared to no vaccination in older adults and would save EUR 35,982,857 in direct medical costs in Belgium. The number needed to vaccinate to prevent one RSV-ARI case was 11 for the 3-year duration profile, while it was 28 and 8 for the 1- and 5-year vaccine duration profiles, respectively. The model was generally robust in sensitivity analyses varying key input values. This study suggested that vaccination could substantially decrease the public health and economic burden of RSV in adults ≥60 years in Belgium, with benefits increasing with a longer duration of vaccine protection.

Economic Burden of COVID-19: A Systematic Review.

Objective: To review and qualitatively synthesize the evidence related to the economic burden of COVID-19, including healthcare resource utilization and costs. Methods: A systematic review of studies that assessed the economic burden [eg, direct costs, productivity, macroeconomic impact due to non-pharmaceutical interventions (NPIs) and equity] of COVID-19 was conducted by searches in EMBASE, MEDLINE, MEDLINE-IN-PROCESS, and The Cochrane Library, as well as manual searches of unpublished research for the period between January 2020 to February 2021. Single reviewer data extraction was confirmed independently by a second reviewer. Results: The screening process resulted in a total of 27 studies: 25 individual publications, and 2 systematic literature reviews, of narrower scopes, that fulfilled the inclusion criteria. The patients diagnosed with more severe COVID-19 were associated with higher costs. The main drivers for higher costs were consistent across countries and included ICU admission, in-hospital resource use such as mechanical ventilation, which lead to increase costs of $2082.65 ± 345.04 to $2990.76 ± 545.98. The most frequently reported indirect costs were due to productivity losses. On average, older COVID-19 patients incurred higher costs when compared to younger age groups. An estimation of a 20% COVID-19 infection rate based on a Monte Carlo simulation in the United States led to a total direct medical cost of $163.4 billion over the course of the pandemic. Conclusion: The COVID-19 pandemic has generated a considerable economic burden on patients and the general population. Preventative measures such as NPIs only have partial success in lowering the economic costs of the pandemic. Implementing additional preventative measures such as large-scale vaccination is vital in reducing direct and indirect medical costs, decreased productivity, and GDP losses.

10 Years of End-of-Life Criteria in the United Kingdom.

OBJECTIVES: In January 2009, the National Institute for Health and Care Excellence introduced supplementary guidance for end-of-life (EoL) treatments, which allowed treatments with an incremental cost-effectiveness ratio over the regular threshold (£20 000-£30 000) to be recommended, if they satisfied the EoL criteria. The aims of this study were (1) to systematically review 10 years of EoL supplementary guidance implementation and explore how it could be improved, and (2) to create a framework for incorporating the uncertainty relating to EoL criteria satisfaction into model-based cost-effectiveness analyses for decision making. METHODS: All appraisals between January 2009 and 2019 were screened for EoL discussions. Data were extracted on the EoL criteria and cost-effectiveness assessment details. Additionally, a quantitative method was developed to include the EoL criteria satisfaction uncertainty into model-based cost-effectiveness analyses. A stylized example was created to provide a case study for the inclusion of EoL criteria satisfaction uncertainty. RESULTS: An EoL discussion was identified in 35% of appraisals, 57% of which led to a positive EoL decision. Only 5.7% of technologies with positive EoL decisions were not recommended, versus 43.8% of technologies with negative EoL decisions. EoL criteria assessment was often reported insufficiently and evaluated inconsistently and nontransparently. A total of 54.9% of EoL decisions were made while at least 1 criterion was surrounded by considerable uncertainty. By applying the proposed quantitative method, this EoL criteria satisfaction uncertainty was accounted for in decision making. The stylized example demonstrated that the impact of EoL criteria satisfaction uncertainty can be substantial enough to reverse the reimbursement decision. CONCLUSIONS: To improve consistency/transparency and correct reimbursement decisions' likelihood, new guidelines on the implementation of the EoL criteria are needed.

A MEA is a MEA is a MEA? Sequential decision making and the impact of different managed entry agreements at the manufacturer and payer level, using a case study for an oncology drug in England.

BACKGROUND: In a typical single-payer setting that uses an explicit cost-effectiveness (CE) threshold in its decision-making, the payer aims to maximize the net-monetary-benefit (NMB) given the CE threshold, whilst the manufacturer aims to maximize the expected discounted-cash-flow (DCF) resulting from the sales of that technology. Managed entry agreements (MEAs) are tools that are used to improve access to expensive technologies that would otherwise not be deemed to be cost-effective to payers. While simple discount on the list price is the most commonly applied MEA type, there are different forms, each having a different impact on the cost-effectiveness of the technology, on the lifetime DCF-per-patient and on the decision uncertainty. We aim to analyze the sequential decision-making (SDM) of different MEAs (i.e. simple discount, free treatment initiation, lifetime treatment acquisition cost-capping [LTTACC], performance-based money-back guarantee [MBG]) at the manufacturer and at the payer level, respectively. METHODS: We first model the SDM of the manufacturer and the payer as a sequential game and explain the challenges to find an equilibrium analytically. Then we propose a heuristic computational method to follow for each of the MEA types, based on practice. To demonstrate this SDM on a case study, a UK-based cost-utility analysis using a three-state, partitioned-survival-model was constructed to determine the cost-effectiveness of regorafenib versus best-supportive-care for the second-line treatment of hepatocellular carcinoma. The optimal agreement terms that would maximise the lifetime DCF-per-patient for each MEA, whilst remaining below the CE-threshold (£50,000/QALY gained) were obtained in the deterministic base-case. Robustness for each optimized MEA was then assessed using probabilistic sensitivity and scenario analyses, the value of information (VoI), and HTA-risk analyses. RESULTS: As expected, the introduction of all MEAs improved the probabilistic ICER and NMB values to (almost) acceptable levels, compared to the "no-MEA" case (ICER ~ £78,000/QALY-gained). The expected DCFs across the explored MEAs were all similar, whilst the payer strategy & uncertainty burden (PSUB) for regorafenib decreased in all MEAs explored. VoI analyses revealed that regorafenib mean-dose-intensity and time-on-treatment (ToT) parameters attributed most to the decision uncertainty. LTTACC provided the smallest PSUB and the most robust NMB estimates under parametric uncertainty. For scenarios assuming increased regorafenib ToT or mean-dose-intensity, LTACC again provided acceptable cost-effectiveness outcomes, whereas for scenarios assuming decreased regorafenib progression-free/overall survival effectiveness, only MBG resulted in plausible ICER values. In scenarios, where the source of uncertainty was not targeted by MEA parameters (e.g. the scenario assuming higher progressed disease resource utilization), all investigated MEA types resulted in unacceptable cost-effectiveness outcomes. CONCLUSION: Each MEA type has a different implication. The impact of different MEAs on the NMB is more noteworthy than on the DCF, in relative terms, hence payers will benefit from the early participation of the MEA design rather than leaving this up to the prerogative of the manufacturer. While simple discount might be practical for implementation purposes, other MEAs can provide additional benefits to the payer in terms of increased NMB, reduced decision risk and reduced uncertainty. MEA performance should be investigated not only under parametric uncertainty, but also under-identified structural uncertainty, and the barriers of implementation should be considered thoroughly before choosing the most appropriate MEA type.

The Methodological Quality and Challenges in Conducting Economic Evaluations of Newborn Screening: A Scoping Review.

INTRODUCTION: Cost-effectiveness (CEA) and cost-utility analyses (CUA) have become popular types of economic evaluations (EE) used for evidence-based decision-making in healthcare resource allocation. Newborn screening programs (NBS) can have significant clinical benefits for society, and cost-effectiveness analysis may help to select the optimal strategy among different screening programs, including the no-screening option, on different conditions. These economic analyses of NBS, however, are hindered by several methodological challenges. This study explored the methodological quality in recent NBS economic evaluations and analyzed the main challenges and strategies adopted by researchers to deal with them. METHODS: A scoping review was conducted according to PRISMA methodology to identify CEAs and CUAs of NBS. The methodological quality of the retrieved studies was assessed quantitatively using a specific guideline for the quality assessment of NBS economic evaluations, by calculating a general score for each EE. Challenges in the studies were then explored using thematic analysis as a qualitative synthesis approach. RESULTS: Thirty-five studies met the inclusion criteria. The quantitative analysis showed that the methodological quality of NBS economic evaluations was heterogeneous. Lack of clear description of items related to results, discussion, and discounting were the most frequent flaws. Methodological challenges in performing EEs of neonatal screenings include the adoption of a long time horizon, the use of quality-adjusted life years as health outcome measure, and the assessment of costs beyond the screening interventions. CONCLUSIONS: The results of this review can support future economic evaluation research, aiding researchers to develop a methodological guidance to perform EEs aimed at producing solid results to inform decisions for resource allocation in neonatal screening.

Avatrombopag and lusutrombopag for thrombocytopenia in people with chronic liver disease needing an elective procedure: a systematic review and cost-effectiveness analysis.

BACKGROUND: There have been no licensed treatment options in the UK for treating thrombocytopenia in people with chronic liver disease requiring surgery. Established management largely involves platelet transfusion prior to the procedure or as rescue therapy for bleeding due to the procedure. OBJECTIVES: To assess the clinical effectiveness and cost-effectiveness of two thrombopoietin receptor agonists, avatrombopag (Doptelet®; Dova Pharmaceuticals, Durham, NC, USA) and lusutrombopag (Mulpleta®; Shionogi Inc., London, UK), in addition to established clinical management compared with established clinical management (no thrombopoietin receptor agonist) in the licensed populations. DESIGN: Systematic review and cost-effectiveness analysis. SETTING: Secondary care. PARTICIPANTS: Severe thrombocytopenia (platelet count of < 50,000/µl) in people with chronic liver disease requiring surgery. INTERVENTIONS: Lusutrombopag 3 mg and avatrombopag (60 mg if the baseline platelet count is < 40,000/µl and 40 mg if it is 40,000-< 50,000/µl). MAIN OUTCOME MEASURES: Risk of platelet transfusion and rescue therapy or risk of rescue therapy only. REVIEW METHODS: Systematic review including meta-analysis. English-language and non-English-language articles were obtained from several databases including MEDLINE, EMBASE and Cochrane Central Register of Controlled Trials, all searched from inception to 29 May 2019. ECONOMIC EVALUATION: Model-based cost-effectiveness analysis. RESULTS: From a comprehensive search retrieving 11,305 records, six studies were included. Analysis showed that avatrombopag and lusutrombopag were superior to no thrombopoietin receptor agonist in avoiding both platelet transfusion and rescue therapy or rescue therapy only, and mostly with a statistically significant difference (i.e. 95% confidence intervals not overlapping the point of no difference). However, only avatrombopag seemed to be superior to no thrombopoietin receptor agonist in reducing the risk of rescue therapy, although far fewer patients in the lusutrombopag trials than in the avatrombopag trials received rescue therapy. When assessing the cost-effectiveness of lusutrombopag and avatrombopag, it was found that, despite the success of these in avoiding platelet transfusions prior to surgery, the additional long-term gain in quality-adjusted life-years was very small. No thrombopoietin receptor agonist was clearly cheaper than both lusutrombopag and avatrombopag, as the cost savings from avoiding platelet transfusions were more than offset by the drug cost. The probabilistic sensitivity analysis showed that, for all thresholds below £100,000, no thrombopoietin receptor agonist had 100% probability of being cost-effective. LIMITATIONS: Some of the rescue therapy data for lusutrombopag were not available. There were inconsistencies in the avatrombopag data. From the cost-effectiveness point of view, there were several additional important gaps in the evidence required, including the lack of a price for avatrombopag. CONCLUSIONS: Avatrombopag and lusutrombopag were superior to no thrombopoietin receptor agonist in avoiding both platelet transfusion and rescue therapy, but they were not cost-effective given the lack of benefit and increase in cost. FUTURE WORK: A head-to-head trial is warranted. STUDY REGISTRATION: This study is registered as PROSPERO CRD42019125311. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 51. See the NIHR Journals Library website for further project information.

Thrombocytopenia, which is a reduction in platelet numbers in the blood, is a common complication of chronic liver disease. It increases the risk of bleeding during procedures including liver biopsy and transplantation. It can delay or prevent procedures, leading to illness and death. Established treatment largely involves platelet transfusion before the procedure or as rescue therapy for bleeding. This report aims to systematically review the clinical effectiveness and estimate the cost-effectiveness of the first two recently licensed treatments, thrombopoietin receptor agonists avatrombopag (Doptelet^®; Dova Pharmaceuticals, Durham, NC, USA) (60 mg if platelet count is < 40,000/µl and 40 mg if platelet count is 40,000­< 50,000/µl) and lusutrombopag (Mulpleta^®; Shionogi Inc., London, UK) (3 mg if platelet count is < 50,000/µl), compared with established treatment. From a comprehensive search, six studies were included. Clinical effectiveness analysis showed that avatrombopag and lusutrombopag were superior to no thrombopoietin receptor agonist in avoiding both platelet transfusion and rescue therapy. Only avatrombopag seemed superior to no thrombopoietin receptor agonist in reducing rescue therapy alone. Cost-effectiveness analysis found that lusutrombopag and avatrombopag were more expensive than no thrombopoietin receptor agonist over a lifetime, as the savings from avoiding platelet transfusions were exceeded by the drug cost, and without long-term health benefits. The probabilistic sensitivity analysis, which examined the effect of uncertainty, showed that no thrombopoietin receptor agonist had 100% probability of being cost-effective. Uncertainty about the price of avatrombopag and the content and costs of platelet transfusions and the potential under-reporting of use to estimate platelet transfusion-specific mortality had the greatest impact on results. If the price of avatrombopag was (confidential information has been removed) below the price of lusutrombopag, avatrombopag would become cost saving in the 40,000­< 50,000/µl subgroup. However, although in some scenarios avatrombopag costs could decrease in the 40,000­< 50,000/µl subgroup to around 10% more than the cost of no thrombopoietin receptor agonist, there would be negligible health benefits and the incremental cost-effectiveness ratios would remain very high, meaning that lusutrombopag and avatrombopag would still not be considered cost-effective.

TECH-VER: A Verification Checklist to Reduce Errors in Models and Improve Their Credibility.

BACKGROUND: In health economic literature, checklists or best practice recommendations on model validation/credibility always declare verification of the programmed model as a fundamental step, such as 'is the model implemented correctly and does the implementation accurately represent the conceptual model?' However, to date, little operational guidance for the model verification process has been given. In this study, we aimed to create an operational checklist for model users or reviewers to verify the technical implementation of health economic decision analytical models and document their verification efforts. METHODS: Literature on model validation, verification, programming errors and credibility was reviewed systematically from scientific databases. An initial beta version of the checklist was developed based on the checklists/tests identified from the literature and from authors' previous modeling/appraisal experience. Next, the first draft checklist was presented to a number of health economists on several occasions and was tested on different models (built in different software, developed by different stakeholders, including drug manufacturers, consultancies or academia), each time leading to an update of the checklist and culminating in the final version of the TECHnical VERification (TECH-VER) checklist, introduced in this paper. RESULTS: The TECH-VER necessitates a model reviewer (preferably independent), an executable and transparent model, its input sources, and detailed documentation (e.g. technical report/scientific paper) in which the conceptual model, its implementation, programmed model inputs, and results are reported. The TECH-VER checklist consists of five domains: (1) input calculations; (2) event-state (patient flow) calculations; (3) result calculations; (4) uncertainty analysis calculations; and (5) other overall checks (e.g. validity or interface). The first four domains reflect the verification of the components of a typical health economic model. For these domains, as a prerequisite of verification tests, the reviewer should identify the relevant calculations in the electronic model and assess the provided justifications for the methods used in the identified calculations. For this purpose, we recommend completeness/consistency checks. Afterwards, the verification tests can be conducted for the calculations in each of these stages by checking the correctness of the implementation of these calculations. For this purpose, the following type of tests are recommended in consecutive order: (i) black-box tests, i.e. checking if model calculations are in line with a priori expectations; (ii) white-box testing, i.e. going through the program code details line by line, or cell by cell (recommended for some crucial calculations and if there are some unexpected results from the black-box tests); and (iii) model replication/parallel programming (recommended only in certain situations, and if the issues related to the identified unexpected results from black-box tests could not be resolved through white-box testing). To reduce the time burden of model verification, we suggest a hierarchical order in tests i-iii, where going to the next step is necessary when the previous step fails. CONCLUSIONS: The TECH-VER checklist is a comprehensive checklist for the technical verification of decision analytical models, aiming to help identify model implementation errors and their root causes while improving the transparency and efficiency of the verification efforts. In addition to external reviews, we consider that the TECH-VER can be used as an internal training and quality control tool for new health economists, while developing their initial models. It is the authors' aim that the TECH-VER checklist transforms itself to an open-source living document, with possible future versions, or 'bolt-on' extensions for specific applications with additional 'fit-for-purpose' tests, as well as 'tips and tricks' and some demonstrative error examples. For this reason, the TECH-VER checklist and the list of black-box tests created in this paper and a few model verification examples is uploaded to an open access, online platform (github and the website of the institute), where other users will also be able to upload their original verification efforts and tests.

Value of information analysis in telehealth for chronic heart failure management.

OBJECTIVES: Value of information (VOI) analysis provides information on opportunity cost of a decision in healthcare by estimating the cost of reducing parametric uncertainty and quantifying the value of generating additional evidence. This study is an application of the VOI methodology to the problem of choosing between home telemonitoring and nurse telephone support over usual care in chronic heart failure management in the Netherlands. METHODS: The expected value of perfect information (EVPI) and the expected value of partially perfect information (EVPPI) analyses were based on an informal threshold of €20K per quality-adjusted life-year. These VOI-analyses were applied to a probabilistic Markov model comparing the 20-year costs and effects in three interventions. The EVPPI explored the value of decision uncertainty caused by the following group of parameters: treatment-specific transition probabilities between New York Heart Association (NYHA) defined disease states, utilities associated with the disease states, number of hospitalizations and ER visits, health state specific costs, and the distribution of patients per NYHA group. We performed the analysis for two population sizes in the Netherlands-patients in all NYHA classes of severity, and patients in NYHA IV class only. RESULTS: The population EVPI for an effective population of 2,841,567 CHF patients in All NYHA classes of severity over the next 20 years is more than €4.5B, implying that further research is highly cost-effective. In the NYHA IV only analysis, for the effective population of 208,003 patients over next 20 years, the population EVPI at the same informal threshold is approx. €590M. The EVPPI analysis showed that the only relevant group of parameters that contribute to the overall decision uncertainty are transition probabilities, in both All NYHA and NYHA IV analyses. CONCLUSIONS: Results of our VOI exercise show that the cost of uncertainty regarding the decision on reimbursement of telehealth interventions for chronic heart failure patients is high in the Netherlands, and that future research is needed, mainly on the transition probabilities.

Severity-Adjusted Probability of Being Cost Effective.

BACKGROUND: In the context of priority setting, a differential cost-effectiveness threshold can be used to reflect a higher societal willingness to pay for quality-adjusted life-year gains in the worse off. However, uncertainty in the estimate of severity can lead to problems when evaluating the outcomes of cost-effectiveness analyses. OBJECTIVES: This study standardizes the assessment of severity, integrates its uncertainty with the uncertainty in cost-effectiveness results and provides decision makers with a new estimate: the severity-adjusted probability of being cost effective. METHODS: Severity is expressed in proportional and absolute shortfall and estimated using life tables and country-specific EQ-5D values. We use the three severity-based cost-effectiveness thresholds (€20.000, €50.000 and €80.000, per QALY) adopted in The Netherlands. We exemplify procedures of integrating uncertainty with a stylized example of a hypothetical oncology treatment. RESULTS: Applying our methods, taking into account the uncertainty in the cost-effectiveness results and in the estimation of severity identifies the likelihood of an intervention being cost effective when there is uncertainty about the appropriate severity-based cost-effectiveness threshold. CONCLUSIONS: Higher willingness-to-pay thresholds for severe diseases are implemented in countries to reflect societal concerns for an equitable distribution of resources. However, the estimates of severity are uncertain, patient populations are heterogeneous, and this can be accounted for with the severity-adjusted probability of being cost effective proposed in this study. The application to the Netherlands suggests that not adopting the new method could result in incorrect decisions in the reimbursement of new health technologies.

Ribociclib with an Aromatase Inhibitor for Previously Untreated, HR-Positive, HER2-Negative, Locally Advanced or Metastatic Breast Cancer: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence, as part of the institute's single technology appraisal process, invited the manufacturer of ribociclib (Kisqali®, Novartis) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with an aromatase inhibitor for the treatment of previously untreated, hormone receptor-positive, human epidermal growth factor receptor 2-negative, locally advanced or metastatic breast cancer. Kleijnen Systematic Reviews Ltd and Erasmus University Rotterdam were commissioned as the Evidence Review Group for this submission. The Evidence Review Group reviewed the evidence submitted by the manufacturer, corrected and validated the manufacturer's decision analytic model, and conducted exploratory analyses to assess the robustness and validity of the presented clinical and cost-effectiveness results. This article describes the company submission, the Evidence Review Group assessment and National Institute for Health and Care Excellence subsequent decisions. The main clinical effectiveness evidence was obtained from the MONALEESA-2 trial, a randomised controlled trial comparing ribociclib plus letrozole with placebo plus letrozole. Progression-free survival was significantly longer in the ribociclib group (95% confidence interval, 19.3-not reached) vs. 14.7 months (95% confidence interval 13.0-16.5) in the placebo group. To assess the cost effectiveness of ribociclib in combination with an aromatase inhibitor, the company developed an individual patient-level model using a discrete-event simulation approach in Microsoft® Excel. In the model, simulated patients move through a series of three health states until death, i.e. first-line progression-free survival, second-line progression-free survival and progressive disease. The length of progression-free survival during the first line was informed by the MONALEESA-2 trial. The benefit in progression-free survival in the first line was transferred to a benefit in overall survival assuming full progression-free survival to overall survival surrogacy (because of the immaturity of overall survival data from the MONALEESA-2 trial). Patient-level data from the BOLERO-2 trial, evaluating the addition of everolimus to exemestane in the second-line treatment of postmenopausal HR-positive advanced breast cancer, were used to inform the length of progression-free survival during the second line. Costs included in the model were treatment costs (e.g. technology acquisition costs of first, second, third and/or later line treatments), drug administration costs, monitoring costs and health state costs (including terminal care). Additionally, the costs of adverse events associated with the first-line treatment were incorporated. The Evidence Review Group recalculated the incremental cost-effectiveness ratio using data from a different data cut-off date from the MONALEESA-2 trial and by changing some assumptions (e.g. progression-free survival to overall survival surrogacy approach and post-progression third and/or later line treatment-related costs). After two appraisal committee meetings and a revised base case submitted by the company (including a second enhanced patient access scheme discount), the committee concluded that taking into account the uncertainties in the calculation of the cost effectiveness, there were plausible cost-effectiveness estimates broadly in the range that could be considered as a cost-effective use of National Health Service resources. Therefore, ribociclib was recommended as a treatment option for the first-line treatment of hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer, contingent on the company providing ribociclib with the discount agreed in the second enhanced patient access scheme.

Obinutuzumab in Combination with Chemotherapy for the First-Line Treatment of Patients with Advanced Follicular Lymphoma : An Evidence Review Group Evaluation of the NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE), as part of the institute's single technology appraisal (STA) process, invited the company that makes obinutuzumab (Roche Products Limited) to submit evidence of the clinical and cost effectiveness of the drug in combination with chemotherapy, with or without obinutuzumab as maintenance therapy for adult patients with untreated, advanced follicular lymphoma (FL) in the UK. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company's submission, the ERG review, and NICE's subsequent decisions. The clinical evidence was derived from two phase III, company-sponsored, randomised, open-label studies. Most evidence on obinutuzumab was based on the GALLIUM trial that compared obinutuzumab in combination with chemotherapy as induction followed by obinutuzumab maintenance monotherapy with rituximab in combination with chemotherapy as induction followed by rituximab maintenance monotherapy in previously untreated patients with FL (grades 1-3a). Long-term clinical evidence was based on the PRIMA trial, studying the benefit of two years of rituximab maintenance after first-line treatment in patients with FL. The cost-effectiveness evidence submitted by the company relied on a partitioned survival cost-utility model, implemented in Microsoft® Excel. The base-case incremental cost-effectiveness ratio (ICER) presented in the company submission was <£20,000 per quality-adjusted life-year (QALY) gained. Although the ERG concluded that the economic model met the NICE reference case to a reasonable extent, some errors were identified and several assumptions made by the company were challenged. A new base-case scenario produced by the ERG suggested an ICER that was higher than the company base case, but still below £30,000 per QALY gained. However, some ERG scenario analyses were close to or even above the threshold. This was the case in particular for assuming a treatment effect that did not extend beyond trial follow-up. These results led to an initial negative recommendation by the appraisal committee. Subsequently, the company submitted a revised base case focusing on patients at intermediate or high risk of premature mortality. Simultaneously, a further price discount for obinutuzumab was granted. In addition to the company's revised base case, the ERG suggested a restriction of the treatment effect to 5 years and implemented biosimilar uptake and cheaper prices for rituximab. All of these adjustments did not exceed £30,000 per QALY gained and therefore the use of obinutuzumab for patients with advanced FL and a Follicular Lymphoma International Predictive Index (FLIPI) score of two or more could be recommended.

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.

Cost-Effectiveness Analysis in Telehealth: A Comparison between Home Telemonitoring, Nurse Telephone Support, and Usual Care in Chronic Heart Failure Management.

OBJECTIVES: To assess the cost effectiveness of home telemonitoring (HTM) and nurse telephone support (NTS) compared with usual care (UC) in the management of patients with chronic heart failure, from a third-party payer's perspective. METHODS: We developed a Markov model with a 20-year time horizon to analyze the cost effectiveness using the original study (Trans-European Network-Home-Care Management System) and various data sources. A probabilistic sensitivity analysis was performed to assess the decision uncertainty in our model. RESULTS: In the original scenario (which concerned the cost inputs at the time of the original study), HTM and NTS interventions yielded a difference in quality-adjusted life-years (QALYs) gained compared with UC: 2.93 and 3.07, respectively, versus 1.91. An incremental net monetary benefit analysis showed €7,697 and €13,589 in HTM and NTS versus UC at a willingness-to-pay (WTP) threshold of €20,000, and €69,100 and €83,100 at a WTP threshold of €80,000, respectively. The incremental cost-effectiveness ratios were €12,479 for HTM versus UC and €8,270 for NTS versus UC. The current scenario (including telenurse cost inputs in NTS) yielded results that were slightly different from those for the original scenario, when comparing all New York Heart Association (NYHA) classes of severity. NTS dominated HTM, compared with UC, in all NYHA classes except NYHA IV. CONCLUSIONS: This modeling study demonstrated that HTM and NTS are viable solutions to support patients with chronic heart failure. NTS is cost-effective in comparison with UC at a WTP of €9000/QALY or higher. Like NTS, HTM improves the survival of patients in all NYHA classes and is cost-effective in comparison with UC at a WTP of €14,000/QALY or higher.

Pomalidomide with Dexamethasone for Treating Relapsed and Refractory Multiple Myeloma Previously Treated with Lenalidomide and Bortezomib: An Evidence Review Group Perspective of an NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE), as part of the institute's single technology appraisal (STA) process, invited the manufacturer of pomalidomide (POM; Imnovid®, Celgene) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with dexamethasone (POM + LoDEX) for the treatment of relapsed and refractory multiple myeloma (RRMM) after at least two regimens including lenalidomide (LEN) and bortezomib (BOR). Kleijnen Systematic Reviews Ltd (KSR) and Erasmus University Rotterdam were commissioned as the Evidence Review Group (ERG) for this submission. The ERG reviewed the evidence submitted by the manufacturer, validated the manufacturer's decision analytic model, and conducted exploratory analyses in order to assess the robustness and validity of the presented clinical and cost-effectiveness results. This paper describes the company submission, the ERG assessment, and NICE's subsequent decisions. The company conducted a systematic review to identify studies comparing POM with comparators outlined in the NICE scope: panobinostat with bortezomib and dexamethasone (PANO + BOR + DEX), bendamustine with thalidomide and dexamethasone (BTD) and conventional chemotherapy (CC). The main clinical effectiveness evidence was obtained from MM-003, a randomized controlled trial (RCT) comparing POM + LoDEX with high-dose dexamethasone (HiDEX; used as a proxy for CC). Additional data from other studies were also used as nonrandomized observational data sources for the indirect treatment comparison of POM + LoDEX with BTD and PANO + BOR + DEX. Covariate or treatment switching adjustment methods were used for each comparison. The model developed in Microsoft® Excel 2010 using a semi-Markov partitioned survival structure, submitted in the original submission to NICE for TA338, was adapted for the present assessment of the cost effectiveness of POM + LoDEX. Updated evidence from the clinical-effectiveness part was used for the survival modelling of progression-free survival and overall survival. For POM + LoDEX, the patient access scheme (PAS) discount was applied to the POM price. Three separate comparisons were conducted for each comparator, each comparison using a different dataset and adjustment methods. The ERG identified and corrected some errors, and the corrected incremental cost-effectiveness ratios (ICERs) for POM + LoDEX versus each comparator were presented: approximately £45,000 per quality-adjusted life-year (QALY) gained versus BTD, savings of approximately £143,000 per QALY lost versus PANO + BOR + DEX, and approximately £49,000 per QALY gained versus CC. The ERG also conducted full incremental analyses, which revealed that CC, POM + LoDEX and PANO + BOR + DEX were on the cost-effectiveness frontier. The committee's decision on the technology under analysis deemed that POM + LoDEX should be recommended as an option for treating multiple myeloma in adults at third or subsequent relapse of treatments including both LEN and BOR, contingent on the company providing POM with the discount agreed in the PAS.

Ramucirumab for Treating Advanced Gastric Cancer or Gastro-Oesophageal Junction Adenocarcinoma Previously Treated with Chemotherapy: An Evidence Review Group Perspective of a NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE) invited the company that manufactures ramucirumab (Cyramza®, Eli Lilly and Company) to submit evidence of the clinical and cost effectiveness of the drug administered alone (monotherapy) or with paclitaxel (combination therapy) for treating adults with advanced gastric cancer or gastro-oesophageal junction (GC/GOJ) adenocarcinoma that were previously treated with chemotherapy, as part of the Institute's single technology appraisal (STA) process. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company's submission, the ERG review, and NICE's subsequent decisions. Clinical effectiveness evidence for ramucirumab monotherapy (RAM), compared with best supportive care (BSC), was based on data from the REGARD trial. Clinical effectiveness evidence for ramucirumab combination therapy (RAM + PAC), compared with paclitaxel monotherapy (PAC), was based on data from the RAINBOW trial. In addition, the company undertook a network meta-analysis (NMA) to compare RAM + PAC with BSC and docetaxel. Cost-effectiveness evidence of monotherapy and combination therapy relied on partitioned survival, cost-utility models. The base-case incremental cost-effectiveness ratio (ICER) of the company was £188,640 (vs BSC) per quality-adjusted life-year (QALY) gained for monotherapy and £118,209 (vs BSC) per QALY gained for combination therapy. The ERG assessment indicated that the modelling structure represented the course of the disease; however, a few errors were identified and some of the input parameters were challenged. The ERG provided a new base case, with ICERs (vs BSC) of £188,100 (monotherapy) per QALY gained and £129,400 (combination therapy) per QALY gained and conducted additional exploratory analyses. The NICE Appraisal Committee (AC), considered the company's decision problem was in line with the NICE scope, with the exception of the choice of comparators for the combination therapy model. The most plausible ICER for ramucirumab monotherapy compared with BSC was £188,100 per QALY gained. The Committee considered that the ERG's exploratory analysis in which RAM + PAC was compared with PAC by using the direct head-to-head data (including utilities) from the RAINBOW trial, provided the most plausible ICER (i.e. £408,200 per QALY gained) for ramucirumab combination therapy. The Committee concluded that end-of-life considerations cannot be applied for either case, since neither failed to offer an extension to life of at least 3 months. The company did not submit a patient access scheme (PAS). After consideration of the evidence, the Committee concluded that ramucirumab alone or with paclitaxel could not be considered a cost-effective use of National Health Service resources for treating advanced GC/GOJ patients that were previously treated with chemotherapy, and therefore its use could not be recommended. We might wonder if a complete STA process is necessary for treatments without a PAS, which are, according to the company's submission, already associated with ICERs far above the currently accepted threshold in all (base-case, sensitivity and scenario) analyses.

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning.

Development of an enhanced health-economic model and cost-effectiveness analysis of tiotropium + olodaterol Respimat® fixed-dose combination for chronic obstructive pulmonary disease patients in Italy.

BACKGROUND: The objective of this study was to compare the cost-effectiveness of the fixed-dose combination (FDC) of tiotropium + olodaterol Respimat(®) FDC with tiotropium alone for patients with chronic obstructive pulmonary disease (COPD) in the Italian health care setting using a newly developed patient-level Markov model that reflects the current understanding of the disease. METHODS: While previously published models have largely been based around a cohort approach using a Markov structure and GOLD stage stratification, an individual-level Markov approach was selected for the new model. Using patient-level data from the twin TOnado trials assessing Tiotropium + olodaterol Respimat(®) FDC versus tiotropium, outcomes were modelled based on the trough forced expiratory volume (tFEV1) of over 1000 patients in each treatment arm, tracked individually at trial visits through the 52-week trial period, and after the trial period it was assumed to decline at a constant rate based on disease stage. Exacerbation risk was estimated based on a random-effects logistic regression analysis of exacerbations in UPLIFT. Mortality by age and disease stage was estimated from an analysis of TIOSPIR trial data. Cost of bronchodilators and other medications, routine management, and costs of treatment for moderate and severe exacerbations for the Italian setting were included. A cost-effectiveness analysis was conducted over a 15-year time horizon from the perspective of the Italian National Health Service. RESULTS: Aggregating total costs and quality-adjusted life years (QALYs) for each treatment cohort over 15 years and comparing tiotropium + olodaterol Respimat(®) FDC with tiotropium alone, resulted in mean incremental costs per patient of €1167 and an incremental cost-effectiveness ratio (ICER) of €7518 per additional QALY with tiotropium + olodaterol Respimat(®) FDC. The lung function outcomes observed for tiotropium + olodaterol Respimat(®) FDC in TOnado drove the results in terms of slightly higher mean life-years (12.24 versus 12.07) exacerbation-free months (11.36 versus 11.32) per patient and slightly fewer moderate and severe exacerbations per patient-year (0.411 versus 0.415; 0.21 versus 0.24) versus tiotropium. Probabilistic sensitivity analyses showed tiotropium + olodaterol Respimat(®) FDC to be the more cost-effective treatment in 95.2% and 98.4% of 500 simulations at thresholds of €20,000 and €30,000 per QALY respectively. CONCLUSION: Tiotropium + olodaterol Respimat(®) FDC is a cost-effective bronchodilator in the maintenance treatment of COPD for the Italian health care system.