Model Structuring for Economic Evaluations of New Health Technologies

The conceptualisation of cardiometabolic disease policy model in the UK

BACKGROUND

Decision models are increasingly used to inform policy-making processes, and there is a need to improve their credibility. The estimation of health and economic outcomes generated from decision models is influenced by the development process itself. This paper aims to present the conceptual model development process of cardiometabolic disease (CMD) policy models in the UK setting.

METHODS

This conceptual model followed the International Society of Pharmacoeconomics and Outcomes Research-Society of Medical Decision Making (ISPOR-SMDM) Modelling Good Research Practices Task Force-2.

RESULTS

First, for the conceptualisation of the problem, the CMD disease staging, progression and current clinical guidelines were summarised, followed by a systematic review of published policy models. We critically appraised policy models such as cardiovascular disease and type 2 diabetes. Key messages from the review emphasised the importance of understanding various determinants influencing model development, including risk factors, model structure, models' parameters, data utilisation, economic perspective, equality/equity consideration, transparency and validation process. Second, as a sequential process, is model conceptualisation, to determine which modelling types and their attributes best represent the defined problem. Expert opinions, including a clinician and experienced modellers, provided input on the state transition model to ensure the structure is clinically relevant. From this stage, the consideration and agreement to establish a disease state in a state transition model was discussed.

CONCLUSION

This conceptual model serves as a basis for representing the systematic process for structuring a CMD policy model to enhance its transparency and credibility.

Challenges in the Evaluation of Emerging Highly Specialised Technologies: Is There a Role for Living HTA?

There is currently deep uncertainty about the clinical benefits and cost effectiveness of highly specialised technologies (HSTs), like gene and cell therapies. These treatments are novel, typically have high upfront costs, the patient populations are small and heterogenous, there is minimal information on their long-term safety and effectiveness, and data are limited and often of poor quality. With the increasing number of these technologies and their high cost burden on governments and health care providers, policy makers are currently walking a decision tightrope. On the one hand, an unfavourable funding decision could potentially limit patient access to life-saving treatments, while on the other, a favourable decision could result in unsustainable budget impacts and perhaps poorer patient health outcomes. Health technology assessment (HTA) is meant to determine the value of a health technology in order to promote an equitable, efficient, and high-quality health system. However, standard HTA processes have failed to mitigate the deep uncertainties associated with these technologies. In this paper, we propose a Living HTA framework to address these challenges. This framework includes a one-off process for making explicit the societal values associated with HSTs. These would inform the decision-making approach, data collection and the development of disease-specific reference models to be used by industry sponsors as the basis for their submissions for public funding. Coverage with an evidence development mechanism is also proposed by which data can be collected in real time to update the reference model on a rolling basis, thereby allowing re-assessment of the clinical and cost effectiveness of individual HSTs. The HTA would be 'live' until the results indicate there is sufficient certainty for the funding decision to be confirmed, the price changed or the funding removed.

Cost-effectiveness of metabolic surgery for the treatment of type 2 diabetes and obesity: a systematic review of economic evaluations

AIM

To systematically identify and appraise the international literature on the cost-effectiveness of metabolic surgery for the treatment of comorbid type 2 diabetes (T2D) and obesity.

METHODS

A systematic search was conducted in electronic databases and grey literature sources up to 20 January 2021. Economic evaluations in a T2D population or a subpopulation with T2D were eligible for inclusion. Screening, data extraction, critical appraisal of methodological quality (Consensus Health Economic Criteria list) and assessment of transferability (International Society for Pharmacoeconomics and Outcomes Research questionnaire) were undertaken in duplicate. The incremental cost-effectiveness ratio (ICER) was the main outcome. Costs were reported in 2020 Irish Euro. Cost-effectiveness was interpreted using willingness-to-pay (WTP) thresholds of €20,000 and €45,000/quality-adjusted life year (QALY). Due to heterogeneity arising from various sources, a narrative synthesis was undertaken.

RESULTS

Thirty studies across seventeen jurisdictions met the inclusion criteria; 16 specifically in a T2D population and 14 in a subpopulation with T2D. Overall, metabolic surgery was found to be cost-effective or cost-saving. Where undertaken, the results were robust to sensitivity and scenario analyses. Of the 30 studies included, 15 were considered high quality. Identified limitations included limited long-term follow-up data and uncertainty regarding the utility associated with T2D remission.

CONCLUSION

Published high-quality studies suggest metabolic surgery is a cost-effective or cost-saving intervention. As the prevalence of obesity and obesity-related diseases increases worldwide, significant investment and careful consideration of the resource requirements needed for metabolic surgery programmes will be necessary to ensure that service provision is adequate to meet demand.

Model parameters influencing the cost-effectiveness of sacubitril/valsartan in heart failure: evidence from a systematic literature review

OBJECTIVES

To summarize cost-effectiveness (CE) evidence of sacubitril/valsartan for the treatment of heart failure (HF) patients with reduced ejection fraction (HFrEF). The impact of different modeling approaches and parameters on the CE results is also described.

METHODS

We conducted a systematic literature review using multiple databases: Embase^®; MEDLINE^®; MEDLINE^®-In Process; NIHR CRD database including DARE, NHS EED, and HTA databases; and the Cost Effectiveness Analysis registry. We also reviewed HTA countries' websites to identify CE reports of sacubitril/valsartan, published up to 25-July-2021. Articles published in English as full-texts, conference-abstracts, or HTA reports were included.

RESULTS

We included 44 CE models [39 from 37 publications (22 full-texts; 15 conference-abstracts) and 5 HTAs; Europe, n = 20; North and South Americas, n = 14; Asia and Australia, n = 10]. Most models adopted a Markov structure with constant transition probabilities of events (n = 27) or a mix of Markov and regression-based models (n = 16), with variations in structural assumptions and chosen parameters. Study authors concluded sacubitril/valsartan to be a cost-effective therapy in 37/41 models in chronic HFrEF patients and 2/3 models in hospitalized patients stabilized after an acute decompensation for HF. CE models showing sacubitril/valsartan not to be a cost-effective treatment generally modeled a shorter time horizon. Effect of sacubitril/valsartan on cardiovascular and all-cause mortality, cost, duration of effect and time horizon was the main model drivers.

CONCLUSIONS

Most evidence indicated sacubitril/valsartan is cost-effective in HFrEF. The use of a lifetime horizon is recommended in future models as HF is a chronic disease. Data on the CE of sacubitril/valsartan in the inpatient setting were limited and further research is warranted.

Modelling the Cost-Effectiveness of Diagnostic Tests

Diagnostic tests are used to determine whether a disease or condition is present or absent in a patient, who will typically be suspected of having the disease or condition due to symptoms or clinical signs. Economic evaluations of diagnostic tests (e.g. cost-effectiveness analyses) can be used to determine whether a test produces sufficient benefit to justify its cost. Evidence on the benefits conferred by a test is often restricted to its accuracy, which means mathematical models are required to estimate the impact of a test on outcomes that matter to patients and health payers. It is important to realise the case for introducing a new test may not be restricted to its accuracy, but extend to factors such as time to diagnosis and acceptability for patients. These and other considerations may mean the common modelling approach, the decision tree, is inappropriate for underpinning an economic evaluation. There are no consensus guidelines on how economic evaluations of diagnostic tests should be conducted-this article attempts to explore the common challenges encountered in economic evaluations, suggests solutions to those challenges, and identifies some areas where further methodological work may be necessary.

Cost-effectiveness analysis of sugemalimab vs. chemotherapy as first-line treatment of metastatic nonsquamous non-small cell lung cancer

Objective: Sugemalimab is approved in China as a first-line treatment in combination with chemotherapy for metastatic nonsquamous non-small cell lung cancer (NSCLC). This study aims to evaluate the cost-effectiveness of first-line additional sugemalimab in combination with chemotherapy vs. chemotherapy from the perspective of the Chinese healthcare system. Materials and methods: A three-state Markov model was designed to evaluate the costs and quality-adjusted life years (QALYs) of first-line sugemalimab combination with chemotherapy vs. chemotherapy over a 10-year period. Data on clinical outcomes were obtained from GEMSTONE-302 clinical trials. Costs and health utilities were collected from local databases and published literature. The uncertainty of the model parameters was explored through sensitivity analysis. Results: Compared to chemotherapy, sugemalimab treatment for NSCLC resulted in an extra 0.50 QALYs at an additional cost of $73627.99, with an incremental cost-effectiveness ratio (ICER) of 148354.07/QALY at the willingness-to-pay (WTP) threshold of $37663.26/QALY. One-way sensitivity analysis indicated that the primary motivator in this model was the cost of sugemalimab. However, none of the parameters significantly affected the model's results. Conclusion: Sugemalimab combination therapy is not economically advantageous for the first-line management of metastatic non-squamous NSCLC, according to the Chinese healthcare system.

Hierarchical Structure Model of Safety Risk Factors in New Coastal Towns: A Systematic Analysis Using the DEMATEL-ISM-SNA Method

When a coastal town transforms from a rural area to an emerging city, it faces many safety risks. Some are new risks from urban construction, while some are traditional risks that belong to this coastal area. The joint efforts of these risks may lead to new hazards, harming public health, but this problem has not been noticed in previous studies. Therefore, this study constructs the Triangular Framework for Safety Risk in New Towns to identify the risks and proposes strategies to reduce the risks. In this study, multiple methods are integrated, including Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Modeling (ISM), and Social Network Analysis (SNA). This study takes the Lin-gang Special Area in China as a case study to verify the framework's effectiveness. Sixteen disaster-causing factors are identified, and the internal linkages among these factors are clarified. Results show that the hybrid method performs well in quantitatively analyzing the risk factors of new coastal towns. A typhoon, public risk perception, and population migration are essential influencing factors. Disaster prevention capability of high-rise buildings, disaster prevention capacity of port facilities, and transportation are the most direct influencing factors. Environmental degradation is the most conductive among all elements. This study contributes to the theoretical theory by proposing an effective framework to analyze the safety risks in new coastal towns. In addition, it provides practical references for governments to make emergency plans in the city.

Health Economic Models for Metastatic Colorectal Cancer: A Methodological Review

OBJECTIVE

The aim of this systematic review was to provide a comprehensive and detailed review of structural and methodological assumptions in model-based cost-effectiveness analyses of systemic metastatic colorectal cancer (mCRC) treatments, and discuss their potential impact on health economic outcome estimates.

METHODS

Five databases (EMBASE, MEDLINE, Cochrane Library, Health Technology Assessment and National Health Service Health Economic Evaluation Database) were searched on 26 August 2019 for model-based full health economic evaluations of systemic mCRC treatment using a combination of free-text terms and subject headings. Full-text publications in English were eligible for inclusion if they were published in or after the year 2000. The Consolidated Health Economic Evaluation Reporting Standards checklist was used to assess the reporting quality of included publications. Study selection, appraisal and data extraction were performed by two reviewers independently.

RESULTS

The search yielded 1418 publications, of which 54 were included, representing 51 unique studies. Most studies focused on first-line treatment (n = 29, 57%), followed by third-line treatment (n = 13, 25%). Model structures were health-state driven (n = 27, 53%), treatment driven (n = 19, 37%), or a combination (n = 5, 10%). Cohort-level state-transition modelling (STM) was the most common technique (n = 33, 65%), followed by patient-level STM and partitioned survival analysis (both n = 6, 12%). Only 15 studies (29%) reported some sort of model validation. Health economic outcomes for specific strategies differed substantially between studies. For example, survival following first-line treatment with fluorouracil, leucovorin and oxaliplatin ranged from 1.21 to 7.33 years, with treatment costs ranging from US$8125 to US$126,606.

CONCLUSIONS

Model-based cost-effectiveness analyses of systemic mCRC treatments have adopted varied modelling methods and structures, resulting in substantially different outcomes. As models generally focus on first-line treatment without consideration of downstream treatments, there is a profound source of structural uncertainty implying that the cost-effectiveness of treatments across the mCRC pathway remains uncertain.

Lifetime costs of invasive meningococcal disease: A Markov model approach

INTRODUCTION

Invasive meningococcal disease (IMD) is an uncommon but life-threatening infectious disease associated with high sequelae rates in young children and an increased risk of mortality in adolescents and young adults. Funding decisions to reject inclusion of new meningococcal serogroup B vaccines on national immunisation schedules have been criticised by IMD patients, their families, paediatricians and charity organisations. We aim to estimate the lifetime costs of IMD with the best available evidence to inform cost-effectiveness analyses.

METHODS

A Markov model was developed taking healthcare system and societal perspectives. A range of data including age-specific mortality rates, and probabilities of IMD-related sequelae were derived from a systematic review and meta-analysis. All currencies were inflated to year 2017 prices by using consumer price indexes in local countries and converted to US dollars by applying purchasing power parities conversion rates. Expert panels were used to inform the model development process including key structural choices and model validations.

RESULTS

The estimated lifetime societal cost is US$319,896.74 per IMD case including the direct healthcare cost of US$65,035.49. Using a discount rate of 5%, the costs are US$54,278.51 and US$13,968.40 respectively. Chronic renal failure and limb amputation result in the highest direct healthcare costs per patient. Patients aged < 5 years incur the higher healthcare expenditure compared with other age groups. The costing results are sensitive to the discount rate, disease incidence, acute admission costs, and sequelae rates and costs of brain injuries and epilepsy.

CONCLUSIONS

IMD can result in substantial costs to the healthcare system and society. Understanding the costs of care can assist decision-making bodies in evaluating cost-effectiveness of new vaccine programs.

Structuring a conceptual model for cost-effectiveness analysis of frailty interventions

BACKGROUND

Frailty is a major health issue which impacts the life of older people, posing a significant challenge to the health system. One of the key emerging areas is the development of frailty interventions to halt or reverse the progression of the condition. In many countries, economic evidence is required to inform public funding decisions for such interventions, and cost-effectiveness models are needed to estimate long-term costs and effects. Such models should capture current clinical understanding of frailty, its progression and its health consequences. The objective of this paper is to present a conceptual model of frailty that can be used to inform the development of a cost-effectiveness model to evaluate frailty interventions.

METHODS

After critical analysis of the clinical and economic literature, a Delphi study consisting of experts from the disciplines of clinical medicine and epidemiology was undertaken to inform the key components of the conceptual model. We also identified relevant databases that can be used to populate and validate the model.

RESULTS

A list of significant health states/events for which frailty is a strong independent risk factor was identified (e.g., hip fracture, hospital admission, delirium, death). We also identified a list of important patient attributes that may influence disease progression (e.g., age, gender, previous hospital admissions, depression). A number of large-scale relevant databases were also identified to populate and validate the cost-effectiveness model. Face validity of model structure was confirmed by experts.

DISCUSSION AND CONCLUSIONS

The proposed conceptual model is being used as a basis for developing a new cost-effectiveness model to estimate lifetime costs and outcomes associated with a range of frailty interventions. Using an appropriate model structure, which more accurately reflects the natural history of frailty, will improve model transparency and accuracy. This will ultimately lead to better informed public funding decisions around interventions to manage frailty.

Multivariable and Structural Uncertainty Analyses for Cost-Effectiveness Estimates: Back to the Future

BACKGROUND

In this commentary, celebrating the 20th anniversary of the journal Value in Health, I present a brief overview and illustration of the evolution over the past 20 years of the methodological literature providing guidelines for multivariable and structural uncertainty analysis for cost-effectiveness estimates.

METHODS

To illustrate the impact of the guidelines for uncertainty analyses, I show how the inclusion of multivariable and structural uncertainty analyses in cost-effectiveness analyses published in Value in Health changed over the past 20 years using publications from 1999/2000, 2007 and 2017.

RESULTS

The commentary is organized in three sections: past, focusing on the development and use of methods for multivariable uncertainty analysis; present, focusing on the growing awareness of the need for structural uncertainty analysis, suggested frameworks for structural uncertainty analysis and how it is currently implemented; and future, considering different methods for combining multivariable and structural uncertainty analyses over the next decades.

CONCLUSIONS

I conclude by suggesting how the continued evolution of uncertainty analyses in published studies and health technology assessment submissions can best take into account an important goal of cost-effectiveness analyses: to provide useful information to decision makers.