Computer Modeling of Diabetes and Its Transparency: A Report on the Eighth Mount Hood Challenge

Estimating Risk Factor Time Paths Among People with Type 2 Diabetes and QALY Gains from Risk Factor Management

OBJECTIVES

Most type 2 diabetes simulation models utilise equations mapping out lifetime trajectories of risk factors [e.g. glycated haemoglobin (HbA1c)]. Existing equations, using historic data or assuming constant risk factors, frequently underestimate or overestimate complication rates. Updated risk factor time path equations are needed for simulation models to more accurately predict complication rates.

AIMS

(1) Update United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2) risk factor time path equations; (2) compare quality-adjusted life-years (QALYs) using original and updated equations; and (3) compare QALY gains for reference case simulations using different risk factor equations.

METHODS

Using pooled contemporary data from two randomised trials EXSCEL and TECOS (n = 28,608), we estimated: dynamic panel models of seven continuous risk factors (high-density lipoprotein cholesterol, low density lipoprotein cholesterol, HbA1c, haemoglobin, heart rate, blood pressure and body mass index); two-step models of estimated glomerular filtration rate; and survival analyses of peripheral arterial disease, atrial fibrillation and albuminuria. UKPDS-OM2-derived lifetime QALYs were extrapolated over 70 years using historical and the new risk factor equations.

RESULTS

All new risk factor equation predictions were within 95% confidence intervals of observed values, displaying good agreement between observed and estimated values. Historical risk factor time path equations predicted trial participants would accrue 9.84 QALYs, increasing to 10.98 QALYs using contemporary equations.

DISCUSSION

Incorporating updated risk factor time path equations into diabetes simulation models could give more accurate predictions of long-term health, costs, QALYs and cost-effectiveness estimates, as well as a more precise understanding of the impact of diabetes on patients' health, expenditure and quality of life.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01144338 and NCT00790205.

Evaluating the Cost-Utility of Continuous Glucose Monitoring in Individuals with Type 1 Diabetes: A Systematic Review of the Methods and Quality of Studies Using Decision Models or Empirical Data

INTRODUCTION

This review presents a critical appraisal of differences in the methodologies and quality of model-based and empirical data-based cost-utility studies on continuous glucose monitoring (CGM) in type 1 diabetes (T1D) populations. It identifies key limitations and challenges in health economic evaluations on CGM and opportunities for their improvement.

METHODS

The review and its documentation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. Searches for articles published between January 2000 and January 2023 were conducted using the MEDLINE, Embase, Web of Science, Cochrane Library, and Econlit databases. Published studies using models and empirical data to evaluate the cost utility of all CGM devices used by T1D patients were included in the search. Two authors independently extracted data on interventions, populations, model settings (e.g., perspectives and time horizons), model types and structures, clinical outcomes used to populate the model, validation, and uncertainty analyses. They subsequently met to confirm consensus. Quality was assessed using the Philips checklist for model-based studies and the Consensus Health Economic Criteria (CHEC) checklist for empirical studies. Model validation was assessed using the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) checklist. The extracted data were used to generate summary tables and figures. The study protocol is registered with PROSPERO (CRD42023391284).

RESULTS

In total, 34 studies satisfied the selection criteria, two of which only used empirical data. The remaining 32 studies applied 10 different models, with a substantial majority adopting the CORE Diabetes Model. Model-based studies often lacked transparency, as their assumptions regarding the extrapolation of treatment effects beyond available evidence from clinical studies and the selection and processing of the input data were not explicitly stated. Initial scores for disagreements concerning checklists were relatively high, especially for the Philips checklist. Following their resolution, overall quality scores were moderate at 56%, whereas model validation scores were mixed. Strikingly, costing approaches differed widely across studies, resulting in little consistency in the elements included in intervention costs.

DISCUSSION AND CONCLUSION

The overall quality of studies evaluating CGM was moderate. Potential areas of improvement include developing systematic approaches for data selection, improving uncertainty analyses, clearer reporting, and explaining choices for particular modeling approaches. Few studies provided the assurance that all relevant and feasible options had been compared, which is required by decision makers, especially for rapidly evolving technologies such as CGM and insulin administration. High scores for disagreements indicated that several checklists contained questions that were difficult to interpret consistently for quality assessment. Therefore, simpler but comprehensive quality checklists may be needed for model-based health economic evaluation studies.

Health state utility values ranges across varying stages and severity of type 2 diabetes-related complications: A systematic review

INTRODUCTION

Health state utility values (HSUV) for Type 2 diabetes mellitus (T2DM) complications are useful in economic evaluations to determine cost effectiveness of an intervention. However, there is a lack of reference ranges for different severity and stages of individual complications. This study aimed to provide an overview of HSUV decrement ranges for common T2DM complications focusing on different severity and stages of complications.

METHOD

A systematic search was conducted in MEDLINE, SCOPUS, WEB OF SCIENCE. (Jan 2000 to April 2022). Included studies for HSUV estimates were from outpatient setting, regardless of treatment types, complication stages, regions and HRQoL instruments. Health Related Quality of Life (HRQoL) outcomes was to be presented as HSUV decrement values, adjusted according to social demographics and comorbidities. Adjusted HSUV decrements were extracted and compiled according to individual complications. After which, subsequently grouped into mild or severe category for comparison.

RESULTS

Searches identified 35 studies. The size of the study population ranged from 160 to 14,826. The HSUV decrement range was widest for cerebrovascular disease (stroke): -0.0060 to -0.0780 for mild stroke and -0.035 to -0.266 for severe stroke; retinopathy: mild (-0.005 to -0.0862), moderate (-0.0030 to -0.1845) and severe retinopathy (-0.023 to -0.2434); amputation: (-0.1050 to -0.2880). Different nature of complication severity defined in studies could be categorized into: those with acute nature, chronic with lasting effects, those with symptoms at early stage or those with repetitive frequency or episodes.

DISCUSSION

Overview of HSUV decrement ranges across different stages of each T2DM diabetes-related complications shows that chronic complications with lasting impact such as amputation, severe stroke with sequelae and severe retinopathy with blindness were generally associated with larger HSUV decrement range. Considerable heterogeneities exist across the studies. Promoting standardized complication definitions and identifying the most influential health state stages on HSUV decrements may assist researchers for future cost-effectiveness studies.

The Determination of Diabetes Utilities, Costs, and Effects Model: A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation

OBJECTIVES

To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes.

METHODS

The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error.

RESULTS

The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios.

CONCLUSIONS

The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

A Systematic Review of Cost-Effectiveness Studies of Newer Non-Insulin Antidiabetic Drugs: Trends in Decision-Analytical Models for Modelling of Type 2 Diabetes Mellitus

BACKGROUND

We performed a systematic overview of the cost-effectiveness analyses (CEAs) comparing Non-insulin antidiabetic drugs (NIADs) with other NIADs for the treatment of type 2 diabetes mellitus (T2DM), using decision-analytical modelling (DAM), focusing on both the economic results and the underlying methodological choices.

METHODS

Eligible studies were CEAs using DAM to compare NIADs within the glucagon-like peptide-1 (GLP1) receptor agonists, sodium-glucose cotransporter-2 (SGLT2) inhibitors, or dipeptidyl peptidase-4 (DPP4) inhibitor classes with other NIADs within those classes for the treatment of T2DM. The PubMed, Embase and Econlit databases were searched from 1 January 2018 to 15 November 2022. Two reviewers screened the studies for relevance by titles and abstracts and then for eligibility via full-text screening, extracted the data from the full texts and appendices, and then stored the data in a spreadsheet.

RESULTS

The search yielded 890 records and 50 studies were eligible for inclusion. The studies were mainly based on a European setting (60%). Industry sponsorship was found in 82% of studies. The CORE diabetes model was used in 48% of the studies. GLP1 and SGLT2 products were the main comparators in 31 and 16 studies, respectively, while one study had DPP4 and two had no easily discernible main comparator. Direct comparison between SGLT2 and GLP1 occurred in 19 studies. At a class level, SGLT2 dominated GLP1 in six studies and was cost effective against GLP1 once as part of a treatment pathway. GLP1 was cost effective in nine studies and not cost effective against SGLT2 in three studies. At a product level, oral and injectable semaglutide, and empagliflozin, were cost effective against other within-class products. Injectable and oral semaglutide were more frequently found cost effective in these comparisons, with some conflicting results. Most of the modelled cohorts and treatment effects were sourced from randomised controlled trials. The following model assumptions varied depending on the class of the main comparator: choice of and reasoning behind risk equations, the time until the treatment switch, and how often the comparators were discontinued. Diabetes-related complications were emphasised on par with quality-adjusted life-years as model outputs. The main quality issues were regarding the description of alternatives, the perspective of analysis, the measurement of costs and consequences, and patient subgroups.

CONCLUSION

The included CEAs using DAMs have limitations that hinder their ability to inform decision makers on the cost-effective choice: lack of updated reasoning behind the choice of key model assumptions, over-reliance on risk equations based on older treatment practices, and sponsorship bias. The question of which NIAD is cost effective for the treatment of which T2DM patient is a pressing one and the answer remains unclear.

Cost-Effectiveness of SGLT2 Inhibitors in a Real-World Population: A MICADO Model-Based Analysis Using Routine Data from a GP Registry

OBJECTIVE

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have been shown to reduce the risk of cardiovascular complications, which largely drive diabetes' health and economic burdens. Trial results indicated that SGLT2i are cost effective. However, these findings may not be generalizable to the real-world target population. This study aims to evaluate the cost effectiveness of SGLT2i in a routine care type 2 diabetes population that meets Dutch reimbursement criteria using the MICADO model.

METHODS

Individuals from the Hoorn Diabetes Care System cohort (N = 15,392) were filtered to satisfy trial inclusion criteria (including EMPA-REG, CANVAS, and DECLARE-TIMI58) or satisfy the current Dutch reimbursement criteria for SGLT2i. We validated a health economic model (MICADO) by comparing simulated and observed outcomes regarding the relative risks of events in the intervention and comparator arm from three trials, and used the validated model to evaluate the long-term health outcomes using the filtered cohorts' baseline characteristics and treatment effects from trials and a review of observational studies. The incremental cost-effectiveness ratio (ICER) of SGLT2i, compared with care-as-usual, was assessed from a third-party payer perspective, measured in euros (2021 price level), using a discount rate of 4% for costs and 1.5% for effects.

RESULTS

From Dutch individuals with diabetes in routine care, 15.8% qualify for the current Dutch reimbursement criteria for SGLT2i. Their characteristics were significantly different (lower HbA1c, higher age, and generally more preexisting complications) than trial populations. After validating the MICADO model, we found that lifetime ICERs of SGLT2i, when compared with usual care, were favorable (< €20,000/QALY) for all filtered cohorts, resulting in an ICER of €5440/QALY using trial-based treatment effect estimates in reimbursed population. Several pragmatic scenarios were tested, the ICERs remained favorable.

CONCLUSIONS

Although the Dutch reimbursement indications led to a target group that deviates from trial populations, SGLT2i are likely to be cost effective when compared with usual care.

Prediction of complications in health economic models of type 2 diabetes: a review of methods used

AIM

Diabetes health economic (HE) models play important roles in decision making. For most HE models of diabetes 2 diabetes (T2D), the core model concerns the prediction of complications. However, reviews of HE models pay little attention to the incorporation of prediction models. The objective of the current review is to investigate how prediction models have been incorporated into HE models of T2D and to identify challenges and possible solutions.

METHODS

PubMed, Web of Science, Embase, and Cochrane were searched from January 1, 1997, to November 15, 2022, to identify published HE models for T2D. All models that participated in The Mount Hood Diabetes Simulation Modeling Database or previous challenges were manually searched. Data extraction was performed by two independent authors. Characteristics of HE models, their underlying prediction models, and methods of incorporating prediction models were investigated.

RESULTS

The scoping review identified 34 HE models, including a continuous-time object-oriented model (n = 1), discrete-time state transition models (n = 18), and discrete-time discrete event simulation models (n = 15). Published prediction models were often applied to simulate complication risks, such as the UKPDS (n = 20), Framingham (n = 7), BRAVO (n = 2), NDR (n = 2), and RECODe (n = 2). Four methods were identified to combine interdependent prediction models for different complications, including random order evaluation (n = 12), simultaneous evaluation (n = 4), the 'sunflower method' (n = 3), and pre-defined order (n = 1). The remaining studies did not consider interdependency or reported unclearly.

CONCLUSIONS

The methodology of integrating prediction models in HE models requires further attention, especially regarding how prediction models are selected, adjusted, and ordered.

Cost-Effectiveness of Semaglutide vs. Empagliflozin, Canagliflozin, and Sitagliptin for Treatment of Patients with Type 2 Diabetes in Denmark: A Decision-Analytic Modelling Study

OBJECTIVE

The aim was to evaluate the cost-effectiveness of oral and subcutaneous semaglutide versus other oral glucose-lowering drugs (i.e., empagliflozin, canagliflozin, and sitagliptin) for the management of type 2 diabetes (T2D) in Denmark using clinically relevant treatment intensification rules.

METHODS

A Markov-type cohort model for evaluating the cost-effectiveness of treatment pathways for T2D was used to produce cost-effectiveness estimates based on four head-to-head trials. Evidence from PIONEER 2 and 3 trials was used to evaluate the cost-effectiveness of oral semaglutide vs. empagliflozin and sitagliptin. Evidence from SUSTAIN 2 and 8 trials was used to evaluate the cost-effectiveness of subcutaneous semaglutide vs. sitagliptin and canagliflozin. Base case analyses used trial product estimands of treatment efficacy to avoid the confounding effects of rescue medication use during trials. Deterministic scenario analyses and probabilistic sensitivity analyses were conducted to assess robustness of cost-effectiveness estimates.

RESULTS

Semaglutide-based treatment regimens were consistently associated with higher lifetime diabetes treatment costs, lower costs of complications, and higher lifetime accumulated QALYs. The PIONEER 2 analysis estimated the cost-effectiveness of oral semaglutide vs. empagliflozin was DKK 150,618/QALY (€20,189). The PIONEER 3 analysis estimated the cost-effectiveness of oral semaglutide vs. sitagliptin was DKK 95,093/QALY (€12,746). The SUSTAIN 2 analysis estimated the cost-effectiveness of subcutaneous semaglutide vs. sitagliptin was DKK 79,982/QALY (€10,721). The SUSTAIN 8 analysis estimated the cost-effectiveness of subcutaneous semaglutide vs. canagliflozin was DKK 167,664/QALY (€22,474).

CONCLUSIONS

Daily oral and weekly subcutaneous semaglutide are likely to both increase cost and health benefits, but are likely to do so under commonly considered cost-effectiveness thresholds.

TRIAL REGISTRATIONS

Clinicaltrials.gov: NCT02863328 (PIONEER 2; registered August 11, 2016); NCT02607865 (PIONEER 3; registered November 18, 2015); NCT01930188 (SUSTAIN 2; registered August 28, 2013); NCT03136484 (SUSTAIN 8; registered May 2, 2017).

Cost-effectiveness of the tubeless automated insulin delivery system vs standard of care in the management of type 1 diabetes in the United States

BACKGROUND: A tubeless, on-body automated insulin delivery (AID) system (Omnipod 5 Automated Insulin Delivery System) demonstrated improved glycated hemoglobin A1c levels and increased time in range (70 mg/dL to 180 mg/dL) for both adults and children with type 1 diabetes in a 13-week multicenter, single-arm study. OBJECTIVE: To assess the cost-effectiveness of the tubeless AID system compared with standard of care (SoC) in the management of type 1 diabetes (T1D) in the United States. METHODS: Cost-effectiveness analyses were conducted from a US payer's perspective, using the IQVIA Core Diabetes Model (version 9.5), with a time horizon of 60 years and an annual discount of 3.0% on both costs and effects. Simulated patients received either tubeless AID or SoC, the latter being defined as either continuous subcutaneous insulin infusion (86% of patients) or multiple daily injections. Two cohorts (children: <18 years; adults: ≥18 years) of patients with T1D and 2 thresholds for nonsevere hypoglycemia (nonsevere hypoglycemia event [NSHE] <54 mg/dL and <70 mg/dL) were considered. Baseline cohort characteristics and treatment effects of different risk factors for tubeless AID were sourced from the clinical trial. Utilities and cost of diabetes-related complications were obtained from published sources. Treatment costs were derived from US national database sources. Scenario analyses and probabilistic sensitivity analyses were performed to test the robustness of the results. RESULTS: Treating children with T1D with tubeless AID, considering an NSHE threshold of less than 54 mg/dL, brings incremental life-years (1.375) and quality-adjusted life-years (QALYs) (1.521) at an incremental cost of $15,099 compared with SoC, resulting in an incremental cost-effectiveness ratio of $9,927 per QALY gained. Similar results were obtained for adults with T1D assuming an NSHE threshold of less than 54 mg/dL (incremental cost-effectiveness ratio = $10,310 per QALY gained). Furthermore, tubeless AID is a dominant treatment option for children and adults with T1D assuming an NSHE threshold of less than 70 mg/dL compared with SoC. The probabilistic sensitivity analyses results showed that compared with SoC, in both children and adults with T1D, tubeless AID was cost-effective in more than 90% of simulations, assuming a willingness-to-pay threshold of $100,000 per QALY gained. The key drivers of the model were the cost of ketoacidosis, duration of treatment effect, threshold of NSHE, and definition of severe hypoglycemia. CONCLUSIONS: The current analyses suggest that the tubeless AID system can be considered a cost-effective treatment compared with SoC in people with T1D from a US payer's perspective. DISCLOSURES: This research was funded by Insulet. Mr Hopley, Ms Boyd, and Mr Swift are full-time Insulet employees and own stock in Insulet Corporation. IQVIA, the employer of Ms Ramos and Dr Lamotte, received consulting fees for this work. Dr Biskupiak is receiving research support and consulting fees from Insulet. Dr Brixner has received consulting fees from Insulet. The University of Utah has received research funding from Insulet. Dr Levy is a consultant with Dexcom and Eli Lilly and has received grant/research support from Insulet, Tandem, Dexcom, and Abbott Diabetes. Dr Forlenza conducted research sponsored by Medtronic, Dexcom, Abbott, Tandem, Insulet, Beta Bionics, and Lilly. He has been speaker/consultant/advisory board member for Medtronic, Dexcom, Abbott, Tandem, Insulet, Beta Bionics, and Lilly.

Value of GLP-1 receptor agonists versus long-acting insulins for type 2 diabetes patients with and without established cardiovascular or chronic kidney diseases: A model-based cost-effectiveness analysis using real-world data

AIMS

To evaluate the cost-effectiveness of glucagon-like peptide-1 receptor agonists (GLP-1RAs) versus long-acting insulins (LAIs) in patients with type 2 diabetes (T2D) using real-world data.

METHODS

A Markov model was utilized to estimate healthcare costs (US$) and quality-adjusted life-years (QALYs) of receiving treatments over 10 years from the healthcare sector perspective. Model inputs were derived from the analyses of Taiwan's National Health Insurance Research Database or published literature on Taiwanese T2D populations. Base-case analysis was performed for the overall study cohort and subgroup analyses were stratified by the presence or absence of established cardiovascular diseases (CVDs) or chronic kidney diseases (CKDs).

RESULTS

Overall, using GLP-1RAs versus LAIs cost $6,053 per QALY gained. Results were robust across sensitivity and scenario analyses. Among patients with established CVDs and CKDs, GLP-1RA versus LAI therapy saved $673 (cost-saving) and cost $1,675 per QALY gained, respectively. Among patients without established CVDs and CKDs, GLP-1RA versus LAI therapy cost $9,093 and $7,659 per QALY gained, respectively.

CONCLUSIONS

Using GLP-1RAs versus LAIs for T2D patients represented good economic value in real-world practice. Pronounced economic benefits of GLP-1RA therapy among those with prior CVDs or CKDs support rational treatment decisions and optimal healthcare resource allocation for these patients.

Model-based predictions on health benefits and budget impact of implementing empagliflozin in people with type 2 diabetes and established cardiovascular disease

AIM

To perform a model-based analysis of the short- and long-term health benefits and costs of further increased implementation of empagliflozin for people with type 2 diabetes and established cardiovascular disease (eCVD) in Sweden.

MATERIALS AND METHODS

The validated Institute for Health Economics Diabetes Cohort Model (IHE-DCM) was used to estimate health benefits and a 3-year budget impact, and lifetime costs per quality-adjusted life years (QALY) gained of increased implementation of adding empagliflozin to standard of care (SoC) for people with type 2 diabetes and eCVD in a Swedish setting. Scenarios with 100%/75%/50% implementation were explored. Analyses were based on 30 model cohorts with type 2 diabetes and eCVD (n = 131 412 at baseline) from national health data registers. Sensitivity analyses explored the robustness of results.

RESULTS

Over 3 years, SoC with empagliflozin (100% implementation) versus SoC before empagliflozin resulted in 7700 total life years gained and reductions in cumulative incidence of cardiovascular deaths by 30% and heart failures by 28%. Annual costs increased by 15% from higher treatment costs and increased survival. Half of these benefits and costs are not yet reached with current implementation below 50%. SoC with empagliflozin yielded 0.37 QALYs per person, with an incremental cost-effectiveness ratio of 16 000 EUR per QALY versus SoC before empagliflozin.

CONCLUSIONS

Model simulations using real-world data and trial treatment effects indicated that a broader implementation of empagliflozin, in line with current guidelines for treatment of people with type 2 diabetes and eCVD, would lead to further benefits even from a short-term perspective.

Recent advances in addressing the market failure of new antimicrobials: Learnings from NICE's subscription-style payment model

Background

Antimicrobial resistance (AMR) is a growing threat to global health. With pathogenic bacteria inevitably becoming more resistant to existing antimicrobials, mortality and costs due to AMR will significantly increase over the next few decades if adequate action is not taken. A major challenge in addressing AMR is the lack of financial incentives for manufacturers to invest in developing new antimicrobials. This is partly because current approaches in health technology assessment (HTA) and standard modeling methods fail to capture the full value of antimicrobials.

Aim

We explore recent reimbursement and payment frameworks, particularly pull incentives, aimed to address the market failures in antimicrobials. We focus on the "subscription-style" payment model recently used in the UK and discuss the learnings for other European countries.

Methods

A pragmatic literature review was conducted to identify recent initiatives and frameworks between 2012 and 2021, across seven European markets. The National Institute for Health and Care Excellence (NICE) technology appraisals for cefiderocol and for ceftazidime with avibactam were reviewed to evaluate how the new UK model has been applied in practice and identify the key challenges.

Conclusion

The UK and Sweden are the first European countries to pilot the feasibility of implementing pull incentives through fully and partially delinked payment models, respectively. The NICE appraisals highlighted the complexity and large areas of uncertainty of modeling antimicrobials. If HTA and value-based pricing are part of the future in tackling the market failure in AMR, European-level efforts may be needed to overcome some of the key challenges.

Costs of major complications in people with and without diabetes in Tasmania, Australia

Objective We set out to estimate healthcare costs of diabetes complications in the year of first occurrence and the second year, and to quantify the incremental costs of diabetes versus non-diabetes related to each complication. Methods In this cohort study, people with diabetes (n  = 45 378) and their age/sex propensity score matched controls (n  = 90 756) were identified from a linked dataset in Tasmania, Australia between 2004 and 2017. Direct costs (including hospital, emergency room visits and pathology costs) were calculated from the healthcare system perspective and expressed in 2020 Australian dollars. The average-per-patient costs and the incremental costs in people with diabetes were calculated for each complication. Results First-year costs when the complications occurred were: dialysis $78 152 (95% CI 71 095, 85 858), lower extremity amputations $63 575 (58 290, 68 688), kidney transplant $48 487 (33 862, 68 283), non-fatal myocardial infarction $30 827 (29 558, 32 197), foot ulcer/gangrene $29 803 (27 183, 32 675), ischaemic heart disease $29 160 (26 962, 31 457), non-fatal stroke $27 782 (26 285, 29 354), heart failure $27 379 (25 968, 28 966), kidney failure $24 904 (19 799, 32 557), angina pectoris $18 430 (17 147, 19 791), neuropathy $15 637 (14 265, 17 108), nephropathy $15 133 (12 285, 18 595), retinopathy $14 775 (11 798, 19 199), transient ischaemic attack $13 905 (12 529, 15 536), vitreous hemorrhage $13 405 (10 241, 17 321), and blindness/low vision $12 941 (8164, 19 080). The second-year costs ranged from 16% (ischaemic heart disease) to 74% (dialysis) of first-year costs. Complication costs were 109-275% higher than in people without diabetes. Conclusions Diabetes complications are costly, and the costs are higher in people with diabetes than without diabetes. Our results can be used to populate diabetes simulation models and will support policy analyses to reduce the burden of diabetes.

Application of decision analytical models to diabetes in low- and middle-income countries: a systematic review

BACKGROUND

Decision analytical models (DAMs) are used to develop an evidence base for impact and health economic evaluations, including evaluating interventions to improve diabetes care and health services-an increasingly important area in low- and middle-income countries (LMICs), where the disease burden is high, health systems are weak, and resources are constrained. This study examines how DAMs-in particular, Markov, system dynamic, agent-based, discrete event simulation, and hybrid models-have been applied to investigate non-pharmacological population-based (NP) interventions and how to advance their adoption in diabetes research in LMICs.

METHODS

We systematically searched peer-reviewed articles published in English from inception to 8th August 2022 in PubMed, Cochrane, and the reference list of reviewed articles. Articles were summarised and appraised based on publication details, model design and processes, modelled interventions, and model limitations using the Health Economic Evaluation Reporting Standards (CHEERs) checklist.

RESULTS

Twenty-three articles were fully screened, and 17 met the inclusion criteria of this qualitative review. The majority of the included studies were Markov cohort (7, 41%) and microsimulation models (7, 41%) simulating non-pharmacological population-based diabetes interventions among Asian sub-populations (9, 53%). Eleven (65%) of the reviewed studies evaluated the cost-effectiveness of interventions, reporting the evaluation perspective and the time horizon used to track cost and effect. Few studies (6,35%) reported how they validated models against local data.

CONCLUSIONS

Although DAMs have been increasingly applied in LMICs to evaluate interventions to control diabetes, there is a need to advance the use of DAMs to evaluate NP diabetes policy interventions in LMICs, particularly DAMs that use local research data. Moreover, the reporting of input data, calibration and validation that underlies DAMs of diabetes in LMICs needs to be more transparent and credible.

Cost‐effectiveness models for Alzheimer's disease and related dementias: IPECAD modeling workshop cross‐comparison challenge

INTRODUCTION

The credibility of model-based economic evaluations of Alzheimer's disease (AD) interventions is central to appropriate decision-making in a policy context. We report on the International PharmacoEconomic Collaboration on Alzheimer's Disease (IPECAD) Modeling Workshop Challenge.

METHODS

Two common benchmark scenarios, for the hypothetical treatment of AD mild cognitive impairment (MCI) and mild dementia, were developed jointly by 29 participants. Model outcomes were summarized, and cross-comparisons were discussed during a structured workshop.

RESULTS

A broad concordance was established among participants. Mean 10-year restricted survival and time in MCI in the control group ranged across 10 MCI models from 6.7 to 9.5 years and 3.4 to 5.6 years, respectively; and across 4 mild dementia models from 5.4 to 7.9 years (survival) and 1.5 to 4.2 years (mild dementia).

DISCUSSION

The model comparison increased our understanding of methods, data used, and disease progression. We established a collaboration framework to assess cost-effectiveness outcomes, an important step toward transparent and credible AD models.

Invited Commentary: Mechanistic and Biologically Based Models in Epidemiology-A Powerful Underutilized Tool

Mechanistic and biologically based mathematical models of chronic and behavioral disease processes aim to capture the main mechanistic or biological features of the disease development and to connect these with epidemiologic outcomes. These approaches have a long history in epidemiologic research and are complementary to traditional epidemiologic or statistical approaches to investigate the role of risk factor exposures on disease risk. Simonetto et al. (Am J Epidemiol. 2022;191(10):1766-1775) present a mechanistic, process-oriented model to investigate the role of smoking, hypertension, and dyslipidemia in the development of atherosclerotic lesions and their progression to myocardial infarction. Their approach builds on and brings to cardiovascular disease the ideas and perspectives of earlier mechanistic and biologically based models for the epidemiology of cancer and other chronic diseases, providing important insights into the mechanisms and epidemiology of smoking related myocardial infarction. We argue that although mechanistic modeling approaches have demonstrated their value and place in epidemiology, they are highly underutilized. We call for efforts to grow mechanistic and biologically based modeling research, expertise, and awareness in epidemiology, including the development of training and collaboration opportunities to attract more students and researchers from science, technology, engineering, and medical field into the epidemiology field.

Cost-Effectiveness of iGlarLixi Versus Premix BIAsp 30 in People with Type 2 Diabetes Suboptimally Controlled by Basal Insulin in the US

INTRODUCTION

Many people with type 2 diabetes mellitus (T2DM) experience suboptimal glycemic control and require therapy advancement. This cost-effectiveness analysis was conducted to compare iGlarLixi (insulin glargine 100 U/mL plus lixisenatide) versus BIAsp 30 (biphasic insulin aspart 30) in people with T2DM suboptimally controlled with basal insulin.

METHODS

The IQVIA Core Diabetes Model was used to estimate lifetime costs and outcomes for people with T2DM from a US healthcare payer perspective. Initial clinical data were based on the phase 3 randomized, open-label, active-controlled SoliMix clinical study, which compared the efficacy and safety of once-daily iGlarLixi with twice-daily BIAsp 30. Lifetime costs (US$) and quality-adjusted life-years (QALYs) were predicted, and the incremental cost-effectiveness ratio (ICER) for iGlarLixi versus BIAsp 30 was estimated; the willingness-to-pay threshold was considered to be $50,000. A subgroup analysis considered people with T2DM aged ≥ 65 years.

RESULTS

Estimated QALYs gained were slightly higher with iGlarLixi compared with BIAsp 30 (9.3 vs. 9.2), with lower costs for iGlarLixi ($117,854 vs. $120,109); the ICER for iGlarLixi was therefore considered dominant over BIAsp 30 in the base case. Key drivers for cost savings were the higher dose and twice-daily administration for BIAsp 30 versus once-daily administration for iGlarLixi. The robustness of the base-case results was confirmed by sensitivity and scenario analyses. Results were similar in a subgroup of people with T2DM aged ≥ 65 years.

CONCLUSION

In people with T2DM with suboptimal glycemic control on basal insulin, iGlarLixi confers improved QALYs and reduced costs compared with BIAsp 30.

The Cost of Control: Cost-effectiveness Analysis of Hybrid Closed-Loop Therapy in Youth

OBJECTIVE

Hybrid closed-loop (HCL) therapy is an efficacious management strategy for young people with type 1 diabetes. However, high costs prevent equitable access. We thus sought to evaluate the cost-effectiveness of HCL therapy compared with current care among young people with type 1 diabetes in Australia.

RESEARCH DESIGN AND METHODS

A patient-level Markov model was constructed to simulate disease progression for young people with type 1 diabetes using HCL therapy versus current care, with follow-up from 12 until 25 years of age. Downstream health and economic consequences were compared via decision analysis. Treatment effects and proportions using different technologies to define "current care" were based primarily on data from an Australian pediatric randomized controlled trial. Transition probabilities and utilities for health states were sourced from published studies. Costs were considered from the Australian health care system's perspective. An annual discount rate of 5% was applied to future costs and outcomes. Uncertainty was evaluated with probabilistic and deterministic sensitivity analyses.

RESULTS

Use of HCL therapy resulted in an incremental cost-effectiveness ratio of Australian dollars (AUD) $32,789 per quality-adjusted life year (QALY) gained. The majority of simulations (93.3%) were below the commonly accepted willingness-to-pay threshold of AUD $50,000 per QALY gained in Australia. Sensitivity analyses indicated that the base-case results were robust.

CONCLUSIONS

In this first cost-effectiveness analysis of HCL technologies for the management of young people with type 1 diabetes, HCL therapy was found to be cost-effective compared with current care in Australia.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge

BACKGROUND

Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models.

METHODS

Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences.

RESULTS

Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049).

CONCLUSIONS

Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

The transferability and validity of a population-level simulation model for the economic evaluation of interventions in diabetes: the MICADO model

AIMS

Valid health economic models are essential to inform the adoption and reimbursement of therapies for diabetes mellitus. Often existing health economic models are applied in other countries and settings than those where they were developed. This practice requires assessing the transferability of a model developed from one setting to another. We evaluate the transferability of the MICADO model, developed for the Dutch 2007 setting, in two different settings using a range of adjustment steps. MICADO predicts micro- and macrovascular events at the population level.

METHODS

MICADO simulation results were compared to observed events in an Italian 2000-2015 cohort (Casale Monferrato Survey [CMS]) and in a Dutch 2008-2019 (Hoorn Diabetes Care Center [DCS]) cohort after adjusting the demographic characteristics. Additional adjustments were performed to: (1) risk factors prevalence at baseline, (2) prevalence of complications, and (3) all-cause mortality risks by age and sex. Model validity was assessed by mean average percentage error (MAPE) of cumulative incidences over 10 years of follow-up, where lower values mean better accuracy.

RESULTS

For mortality, MAPE was lower for CMS compared to DCS (0.38 vs. 0.70 following demographic adjustment) and adjustment step 3 improved it to 0.20 in CMS, whereas step 2 showed best results in DCS (0.65). MAPE for heart failure and stroke in DCS were 0.11 and 0.22, respectively, while for CMS was 0.42 and 0.41.

CONCLUSIONS

The transferability of the MICADO model varied by event and per cohort. Additional adjustments improved prediction of events for MICADO. To ensure a valid model in a new setting it is imperative to assess the impact of adjustments in terms of model accuracy, even when this involves the same country, but a new time period.

The Cost-Effectiveness of Intermediate-Acting, Long-Acting, Ultralong-Acting, and Biosimilar Insulins for Type 1 Diabetes Mellitus: A Systematic Review

OBJECTIVES

The incidence of type 1 diabetes mellitus is increasing every year requiring substantial expenditure on treatment and complications. A systematic review was conducted on the cost-effectiveness of insulin formulations, including ultralong-, long-, or intermediate-acting insulin, and their biosimilar insulin equivalents.

METHODS

MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, HTA, and NHS EED were searched from inception to June 11, 2021. Cost-effectiveness and cost-utility analyses were included if insulin formulations in adults (≥ 16 years) with type 1 diabetes mellitus were evaluated. Two reviewers independently screened titles, abstracts, and full-text articles, extracted study data, and appraised their quality using the Drummond 10-item checklist. Costs were converted to 2020 US dollars adjusting for inflation and purchasing power parity across currencies.

RESULTS

A total of 27 studies were included. Incremental cost-effectiveness ratios ranged widely across the studies. All pairwise comparisons (11 of 11, 100%) found that ultralong-acting insulin was cost-effective compared with other long-acting insulins, including a long-acting biosimilar. Most pairwise comparisons (24 of 27, 89%) concluded that long-acting insulin was cost-effective compared with intermediate-acting insulin. Few studies compared long-acting insulins with one another.

CONCLUSIONS

Long-acting insulin may be cost-effective compared with intermediate-acting insulin. Future studies should directly compare biosimilar options and long-acting insulin options and evaluate the long-term consequences of ultralong-acting insulins.

Cost-Effectiveness of Once-Weekly Semaglutide 1 mg versus Canagliflozin 300 mg in Patients with Type 2 Diabetes Mellitus in a Canadian Setting

OBJECTIVE

Our objective was to evaluate the long-term cost-effectiveness of once-weekly semaglutide 1 mg versus once-daily canagliflozin 300 mg in patients with type 2 diabetes mellitus (T2DM) uncontrolled with metformin from the healthcare payer and societal perspectives in Canada.

METHODS

Head-to-head data from the SUSTAIN 8 randomised trial (NCT03136484) were extrapolated over 40 years using economic simulation modelling. The cost-effectiveness of once-weekly semaglutide 1 mg versus canagliflozin 300 mg for treating T2DM was estimated using the Swedish Institute for Health Economics-Diabetes Cohort Model (IHE-DCM) and the Economic and Health Outcomes Model of T2DM (ECHO-T2DM). Unit costs and disutility weights capturing treatments and key macro- and microvascular complications were sourced from the literature to best match the Canadian setting. A probabilistic base-case simulation and sensitivity analyses were conducted.

RESULTS

Once-weekly semaglutide 1 mg was associated with reductions in macro- and microvascular complications, yielding incremental cost-effectiveness ratios (ICERs) of (Canadian dollars [CAD]) CAD16,392 and 18,098 per incremental quality-adjusted life-year (QALY) gained versus canagliflozin 300 mg for IHE-DCM and ECHO-T2DM, respectively, from a healthcare payer perspective. Accounting for productivity loss as well, ICERs were CAD14,127 and 13,188 per QALY gained for IHE-DCM and ECHO-T2DM, respectively, from a societal perspective. Sensitivity analyses confirmed that the base-case results were robust to changes in input parameters and assumptions used.

CONCLUSIONS

At a willingness-to-pay threshold of CAD50,000 per QALY gained, once-weekly semaglutide 1 mg was cost-effective over 40 years versus once-daily canagliflozin 300 mg for the treatment of T2DM in patients failing to maintain glycemic control with metformin alone.

A Review of Economic Models Submitted to NICE's Technology Appraisal Programme, for Treatments of T1DM & T2DM

Background: In the UK, 4.7 million people are currently living with diabetes. This is projected to increase to 5 million by 2025. The direct and indirect costs of T1DM and T2DM are rising, and direct costs already account for approximately 10% of the National Health Service (NHS) budget.

Objective: The aim of this review is to assess the economic models used in the context of NICE’s Technology Appraisals (TA) Programme of T1DM and T2DM treatments, as well as to examine their compliance with the American Diabetes Association’s (ADA) guidelines on computer modelling.

Methods: A review of the economic models used in NICE’s TA programme of T1DM and T2DM treatments was undertaken. Relevant TAs were identified through searching the NICE website for published appraisals completed up to April 2021. The review also examined the associated Evidence Review Group (ERG) reports and Final Appraisal Documents (FAD), which are publicly accessible. ERG reports were scrutinised to identify major issues pertaining to the economic modelling. The FAD documents were then examined to assess how these issues reflected on NICE recommendations.

Results: Overall, 10 TAs pertaining to treatments of T1DM and T2DM were identified. Two TAs were excluded as they did not use economic models. Seven of the 8 included TAs related to a novel class of oral antidiabetic drugs (OADs), gliflozins, and one to continuous subcutaneous insulin infusion (CSII) devices. There is a lack of recent, robust data informing risk equations to enable the derivation of transition probabilities. Despite uncertainty surrounding its clinical relevance, bodyweight/BMI is a key driver in many T2DM-models. HbA1c’s reliability as a predictor of hard outcomes is uncertain, chiefly for macrovascular complications. The external validity of T1DM is even less clear. There is an inevitable trade-off between the sophistication of models’ design, their transparency and practicality.

Conclusion: Economic models are essential tools to support decision-making in relation to market access and ascertain diabetes technologies’ cost effectiveness. However, key structural and methodological issues exist. Models’ shortcomings should be acknowledged and contextualised within the framework of technology appraisals. Diabetes medications and other technologies should also be subject to regular and consistent re-appraisal to inform disinvestment decisions. Artificial intelligence could potentially enhance models’ transparency and practicality.

Cost-effectiveness of professional-mode flash glucose monitoring in general practice among adults with type 2 diabetes: Evidence from the GP-OSMOTIC trial

AIM

To assess the cost-effectiveness of professional-mode flash glucose monitoring in adults with type 2 diabetes in general practice compared with usual clinical care.

METHODS

An economic evaluation was conducted as a component of the GP-OSMOTIC trial, a pragmatic multicentre 12-month randomised controlled trial enrolling 299 adults with type 2 diabetes in Victoria, Australia. The economic evaluation was conducted from an Australian healthcare sector perspective with a lifetime horizon. Health-related quality of life (EQ-5D) and total healthcare costs were compared between the intervention and the usual care group within the trial period. The 'UKPDS Outcomes Model 2' was used to simulate post-trial lifetime costs, life expectancy and quality-adjusted life years (QALYs).

RESULTS

No significant difference in health-related quality of life and costs was found between the two groups within the trial period. Professional-mode flash glucose monitoring yielded greater QALYs (0.03 [95% CI: 0.02, 0.04]) and a higher cost (A$3807 [95% CI: 3604, 4007]) compared with usual clinical care using a lifetime horizon under the trial-based monitoring frequency, considered not cost-effective (incremental cost-effectiveness ratio = A$120,228). The intervention becomes cost-effective if sensor price is reduced to lower than 50%, or monitoring frequency is decreased to once per year while maintaining the same treatment effect on HbA_1c .

CONCLUSIONS

Including professional-mode flash glucose monitoring every 3 months as part of a management plan for people with type 2 diabetes in general practice is not cost-effective, but could be if the sensor price or monitoring frequency can be reduced.

The PRIME Type 2 Diabetes Model: a novel, patient-level model for estimating long-term clinical and cost outcomes in patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

The growing burden of diabetes mellitus and recent progress in understanding cardiovascular outcomes for type 2 diabetes (T2D) patients continue to make the disease a priority for healthcare decision-makers around the world. Our objective was to develop a new, product-independent model capable of projecting long-term clinical and cost outcomes for populations with T2D to support health economic evaluation.

METHODS

Following a systematic literature review to identify longitudinal study data, existing T2D models and risk formulae for T2D populations, a model was developed (the PRIME Type 2 Diabetes Model [PRIME T2D Model]) in line with good practice guidelines to simulate disease progression, diabetes-related complications and mortality. The model runs as a patient-level simulation and is capable of simulating treatment algorithms and risk factor progression, and projecting the cumulative incidence of macrovascular and microvascular complications as well as hypoglycemic events. The PRIME T2D Model can report clinical outcomes, quality-adjusted life expectancy, direct and indirect costs, along with standard measures of cost-effectiveness and is capable of probabilistic sensitivity analysis. Several approaches novel to T2D modeling were utilized, such as combining risk formulae using a weighted model averaging approach that takes into account patient characteristics to evaluate complication risk.

RESULTS

Validation analyses comparing modeled outcomes with published studies demonstrated that the PRIME T2D Model projects long-term patient outcomes consistent with those reported for a number of long-term studies, including cardiovascular outcomes trials. All root mean squared deviation (RMSD) values for internal validations (against published studies used to develop the model) were 1.1% or less and all external validation RMSDs were 3.7% or less.

CONCLUSIONS

The PRIME T2D Model is a product-independent analysis tool that is available online and offers new approaches to long-standing challenges in diabetes modeling and may become a useful tool for informing healthcare policy.HIGHLIGHTSThe PRIME Type 2 Diabetes (T2D) Model is a new, product-independent simulation model.The model offers new approaches to long-standing challenges in diabetes modeling.PRIME T2D Model projects outcomes consistent with those from clinical trials.The model is designed to be a useful tool for informing healthcare policy in T2D.

A review of simulation models for the long-term management of type 2 diabetes in low-and-middle income countries

INTRODUCTION

The burden of type 2 diabetes is steadily increasing in low-and-middle-income countries, thereby posing a major threat from both a treatment, and funding standpoint. Although simulation modelling is generally relied upon for evaluating long-term costs and consequences associated with diabetes interventions, no recent article has reviewed the characteristics and capabilities of available models used in low-and-middle-income countries. We review the use of computer simulation modelling for the management of type 2 diabetes in low-and-middle-income countries.

METHODS

A search for studies reporting computer simulation models of the natural history of individuals with type 2 diabetes and/or decision models to evaluate the impact of treatment strategies on these populations was conducted in PubMed. Data were extracted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and assessed using modelling checklists. Publications before the year 2000, from high-income countries, studies involving animals and analyses that did not use mathematical simulations were excluded. The full text of eligible articles was sourced and information about the intervention and population being modelled, type of modelling approach and the model structure was extracted.

RESULTS

Of the 79 articles suitable for full text review, 44 studies met the inclusion criteria. All were cost-effectiveness/utility studies with the majority being from the East Asia and Pacific region (n = 29). Of the included studies, 34 (77.3%) evaluated the cost-effectiveness of pharmacological interventions and approximately 75% of all included studies used HbA1c as one of the treatment effects of the intervention. 32 (73%) of the publications were microsimulation models, and 29 (66%) were state-transition models. Most of the studies utilised annual cycles (n = 29, 71%), and accounted for costs and outcomes over 20 years or more (n = 38, 86.4%).

CONCLUSIONS

While the use of simulation modelling in the management of type 2 diabetes has been steadily increasing in low-and-middle-income countries, there is an urgent need to invest in evaluating therapeutic and policy interventions related to type 2 diabetes in low-and-middle-income countries through simulation modelling, especially with local research data. Moreover, it is important to improve transparency and credibility in the reporting of input data underlying model-based economic analyses, and studies.

Cost-Effectiveness of iGlarLixi Versus iDegLira in Type 2 Diabetes Mellitus Inadequately Controlled by GLP-1 Receptor Agonists and Oral Antihyperglycemic Therapy

INTRODUCTION

The fixed-ratio combinations (FRCs) of glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and basal insulin, insulin glargine 100 U/mL plus lixisenatide (iGlarLixi), and insulin degludec plus liraglutide (iDegLira), have demonstrated safety and efficacy in patients with type 2 diabetes mellitus (T2DM) inadequately controlled on GLP-1 RAs. However, a comparative cost-effectiveness analysis between these FRCs from a UK Health Service perspective has not been conducted.

METHODS

The IQVIA Core Diabetes Model was used to estimate lifetime costs and outcomes in patients with T2DM receiving iGlarLixi (based on the LixiLan-G trial) versus iDegLira (based on relative treatment effects from an indirect treatment comparison using data from DUAL III). Utilities, medical costs, and costs of diabetes-related complications were derived from literature. Model outputs included costs and quality-adjusted life years (QALYs). Incremental cost-effectiveness ratios were calculated with a local willingness-to-pay threshold of £20,000 per QALY. Extensive scenario, one-way sensitivity, and probabilistic sensitivity analyses were conducted to evaluate the robustness of the model.

RESULTS

iGlarLixi was less costly (iGlarLixi, £30,011; iDegLira, £40,742), owing to lower acquisition costs, and similar in terms of QALYs gained (iGlarLixi, 8.437; iDegLira, 8.422). Extensive scenario and sensitivity analyses supported the base case findings.

CONCLUSION

In patients with T2DM and inadequate glycemic control despite GLP-1 RAs, use of iGlarLixi was associated with substantial cost savings and comparable utility outcomes. iGlarLixi can be considered as cost-effective versus iDegLira from the UK Health Service perspective.

Estimating risk factor progression equations for the UKPDS Outcomes Model 2 (UKPDS 90)

OBJECTIVES

To estimate 13 equations that predict clinically plausible risk factor time paths to inform the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model version 2 (UKPDS-OM2).

METHODS

Data from 5102 UKPDS participants from the 20-year trial, and the 4031 survivors with 10 years further post-trial follow-up, were used to derive equations for the time paths of 13 clinical risk factors: HbA_1c , systolic blood pressure, LDL-cholesterol, HDL-cholesterol, BMI, micro- or macro-albuminuria, creatinine, heart rate, white blood cell count, haemoglobin, estimated glomerular filter rate, atrial fibrillation and peripheral vascular disease (PVD). The incidence of events and death predicted by the UKPDS-OM2 when informed by the new risk factor equations was compared with the observed cumulative rates up to 25 years.

RESULTS

The new equations were based on 24 years of follow-up and up to 65,252 person-years of data. Women were associated with higher values of all continuous risk factors except for haemoglobin. Older age and higher BMI at diagnosis were associated with higher rates of PVD (HR 1.06 and 1.02), atrial fibrillation (HR 1.10 and 1.08) and micro- or macro-albuminuria (HR 1.01 and 1.18). Smoking was associated with higher rates of developing PVD (HR 2.38) and micro- and macro-albuminuria (HR 1.39). The UKPDS-OM2, informed by the new risk factor equations, predicted event rates for complications and death consistent with those observed.

CONCLUSIONS

The new equations allow risk factor time paths beyond observed data, which should improve modelling of long-term health outcomes for people with type 2 diabetes when using the UKPDS-OM2 or other models.

Development and validation of the risk engine for an Australian Health Economics Model of Osteoporosis

The Australian Health Economics Model of Osteoporosis (AusHEMO) has shown good face, internal and cross validities, and can be used to assist healthcare decision-making in Australia.

PURPOSE

This study aimed to document and validate the risk engine of the Australian Health Economics Model of Osteoporosis (AusHEMO).

METHODS

AusHEMO is a state-transition microsimulation model. The fracture risks were simulated using fracture incidence rates from the Dubbo Osteoporosis Epidemiology Study. The AusHEMO was validated regarding its face, internal and cross validities. Goodness-of-fit analysis was conducted and Lin's coefficient of agreement and mean absolute difference with 95% limits of agreement were reported.

RESULTS

The development of AusHEMO followed general and osteoporosis-specific health economics guidelines. AusHEMO showed good face validity regarding the model's structure, evidence, problem formulation and results. In addition, the model has been proven good internal and cross validities in goodness-of-fit test. Lin's coefficient was 0.99, 1 and 0.94 for validation against the fracture incidence rates, Australian life expectancies and residual lifetime fracture risks, respectively.

CONCLUSIONS

In summary, the development of the risk engine of AusHEMO followed the best practice for osteoporosis disease modelling and the model has been shown to have good face, internal and cross validities. The AusHEMO can be confidently used to predict long-term fracture-related outcomes and health economic evaluations when costs data are included. Health policy-makers in Australia can use the AusHEMO to select which osteoporosis interventions such as medications and public health interventions represent good value for money.

Simulation Modeling for the Economic Evaluation of Population-Based Dietary Policies: A Systematic Scoping Review

Simulation modeling can be useful to estimate the long-term health and economic impacts of population-based dietary policies. We conducted a systematic scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guideline to map and critically appraise economic evaluations of population-based dietary policies using simulation models. We searched Medline, Embase, and EconLit for studies published in English after 2005. Modeling studies were mapped based on model type, dietary policy, and nutritional target, and modeled risk factor-outcome pathways were analyzed. We included 56 studies comprising 136 model applications evaluating dietary policies in 21 countries. The policies most often assessed were reformulation (34/136), taxation (27/136), and labeling (20/136); the most common targets were salt/sodium (60/136), sugar-sweetened beverages (31/136), and fruit and vegetables (15/136). Model types included Markov-type (35/56), microsimulation (11/56), and comparative risk assessment (7/56) models. Overall, the key diet-related risk factors and health outcomes were modeled, but only 1 study included overall diet quality as a risk factor. Information about validation was only reported in 19 of 56 studies and few studies (14/56) analyzed the equity impacts of policies. Commonly included cost components were health sector (52/56) and public sector implementation costs (35/56), as opposed to private sector (18/56), lost productivity (11/56), and informal care costs (3/56). Most dietary policies (103/136) were evaluated as cost-saving independent of the applied costing perspective. An analysis of the main limitations reported by authors revealed that model validity, uncertainty of dietary effect estimates, and long-term intervention assumptions necessitate a careful interpretation of results. In conclusion, simulation modeling is widely applied in the economic evaluation of population-based dietary policies but rarely takes dietary complexity and the equity dimensions of policies into account. To increase relevance for policymakers and support diet-related disease prevention, economic effects beyond the health sector should be considered, and transparent conduct and reporting of model validation should be improved.

Psychological interventions to improve self-management of type 1 and type 2 diabetes: a systematic review

BACKGROUND

For people with diabetes mellitus to achieve optimal glycaemic control, motivation to perform self-management is important. The research team wanted to determine whether or not psychological interventions are clinically effective and cost-effective in increasing self-management and improving glycaemic control.

OBJECTIVES

The first objective was to determine the clinical effectiveness of psychological interventions for people with type 1 diabetes mellitus and people with type 2 diabetes mellitus so that they have improved (1) glycated haemoglobin levels, (2) diabetes self-management and (3) quality of life, and fewer depressive symptoms. The second objective was to determine the cost-effectiveness of psychological interventions.

DATA SOURCES

The following databases were accessed (searches took place between 2003 and 2016): MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, PsycINFO, EMBASE, Cochrane Controlled Trials Register, Web of Science, and Dissertation Abstracts International. Diabetes conference abstracts, reference lists of included studies and Clinicaltrials.gov trial registry were also searched.

REVIEW METHODS

Systematic review, aggregate meta-analysis, network meta-analysis, individual patient data meta-analysis and cost-effectiveness modelling were all used. Risk of bias of randomised and non-randomised controlled trials was assessed using the Cochrane Handbook (Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928).

DESIGN

Systematic review, meta-analysis, cost-effectiveness analysis and patient and public consultation were all used.

SETTING

Settings in primary or secondary care were included.

PARTICIPANTS

Adolescents and children with type 1 diabetes mellitus and adults with types 1 and 2 diabetes mellitus were included.

INTERVENTIONS

The interventions used were psychological treatments, including and not restricted to cognitive-behavioural therapy, counselling, family therapy and psychotherapy.

MAIN OUTCOME MEASURES

Glycated haemoglobin levels, self-management behaviours, body mass index, blood pressure levels, depressive symptoms and quality of life were all used as outcome measures.

RESULTS

A total of 96 studies were included in the systematic review (n = 18,659 participants). In random-effects meta-analysis, data on glycated haemoglobin levels were available for seven studies conducted in adults with type 1 diabetes mellitus (n = 851 participants) that demonstrated a pooled mean difference of -0.13 (95% confidence interval -0.33 to 0.07), a non-significant decrease in favour of psychological treatment; 18 studies conducted in adolescents/children with type 1 diabetes mellitus (n = 2583 participants) that demonstrated a pooled mean difference of 0.00 (95% confidence interval -0.18 to 0.18), indicating no change; and 49 studies conducted in adults with type 2 diabetes mellitus (n = 12,009 participants) that demonstrated a pooled mean difference of -0.21 (95% confidence interval -0.31 to -0.10), equivalent to reduction in glycated haemoglobin levels of -0.33% or ≈3.5 mmol/mol. For type 2 diabetes mellitus, there was evidence that psychological interventions improved dietary behaviour and quality of life but not blood pressure, body mass index or depressive symptoms. The results of the network meta-analysis, which considers direct and indirect effects of multiple treatment comparisons, suggest that, for adults with type 1 diabetes mellitus (7 studies; 968 participants), attention control and cognitive-behavioural therapy are clinically effective and cognitive-behavioural therapy is cost-effective. For adults with type 2 diabetes mellitus (49 studies; 12,409 participants), cognitive-behavioural therapy and counselling are effective and cognitive-behavioural therapy is potentially cost-effective. The results of the individual patient data meta-analysis for adolescents/children with type 1 diabetes mellitus (9 studies; 1392 participants) suggest that there were main effects for age and diabetes duration. For adults with type 2 diabetes mellitus (19 studies; 3639 participants), baseline glycated haemoglobin levels moderated treatment outcome.

LIMITATIONS

Aggregate meta-analysis was limited to glycaemic control for type 1 diabetes mellitus. It was not possible to model cost-effectiveness for adolescents/children with type 1 diabetes mellitus and modelling for type 2 diabetes mellitus involved substantial uncertainty. The individual patient data meta-analysis included only 40-50% of studies.

CONCLUSIONS

This review suggests that psychological treatments offer minimal clinical benefit in improving glycated haemoglobin levels for adults with type 2 diabetes mellitus. However, there was no evidence of benefit compared with control interventions in improving glycated haemoglobin levels for people with type 1 diabetes mellitus.

FUTURE WORK

Future work should consider the competency of the interventionists delivering a therapy and psychological approaches that are matched to a person and their life course.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016033619.

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. 28. See the NIHR Journals Library website for further project information.

Optimizing diabetes screening frequencies for at-risk groups

There is strong evidence that diabetes is underdiagnosed in the US: the Centers for Disease Control and Prevention (CDC) estimates that approximately 25% of diabetic patients are unaware of their condition. To encourage timely diagnosis of at-risk patients, we develop screening guidelines stratified by body mass index (BMI), age, and prior test history by using a Partially Observed Markov Decision Process (POMDP) framework to provide more personalized screening frequency recommendations. We identify structural results that prove the existence of threshold solutions in our problem and allow us to determine the relative timing and frequency of screening given different risk profiles. We then use nationally representative empirical data to identify a policy that provides the optimal action (screen or wait) every six months from age 45 to 90. We find that the current screening guidelines are suboptimal, and the recommended diabetes screening policy should be stratified by age and by finer BMI thresholds than in the status quo. We identify age ranges and BMI categories for which relatively less or more screening is needed compared to the existing guidelines to help physicians target patients most at risk. Compared to the status quo, we estimate that an optimal screening policy would generate higher net monetary benefits by $3,200-$3,570 and save $120-$1,290 in health expenditures per individual in the US above age 45.

Population norms for quality adjusted life years for the United States of America, China, the United Kingdom and Australia

Health economics uses quality adjusted life years (QALYs) to help healthcare decision makers. However, unlike life expectancy for which age- and sex-dependent national life tables are available, no general population norms exist to use as a benchmark against which to compare observed or modeled projections of QALYs in sub-populations or patients. We developed a 2-state Markov model to generate QALY population norms for the USA, UK, China and Australia. Annual age- and sex-specific probabilities of all-cause mortality were taken from life tables combined with general population country-specific age- and sex-specific health state utilities for the EQ-5D-3L (all countries); and SF-6D (Australia) multi-attribute utility instruments (MAUI). To validate our QALY benchmark model we found that the model closely predicted population life expectancies. Using EQ-5D-3L, undiscounted QALYs for males/females aged 18 years ranged 54.62/58.90 (USA), 55.55/60.21 (China), 57.11/60.16 (Australia), and 58.01/61.43 (UK) years. SF-6D benchmark QALYs for Australia were consistently lower than those generated from the EQ-5D-3L. The gap in undiscounted QALYs between the UK (highest) and the USA (lowest) was 2.53 QALYs in women and 3.39 QALYs in men aged 18 years. Our model's QALY population norms can be used for internal validation of future health economic models for the country-specific value sets for the instruments that we adopted, and when quantifying burden of disease in terms of QALYs lost due to illness compared to the general population. We have created a publicly available repository to continuously include QALY benchmarks that use country-specific value sets for other MAUIs and life expectancies.

Prediction of transient ischemic attack and minor stroke in people with type 2 diabetes mellitus

AIMS

People with type 2 diabetes (T2DM) have an increased risk of transient ischemic attack and minor stroke (TIA) which are frequently followed by an ischemic stroke. We aimed to develop a predictive model for incident TIA in people with T2DM.

METHODS

We pooled data from two longitudinal cohort studies, Atherosclerosis Risk in Communities (ARIC) and the Cardiovascular Health Study (CHS), using a two-stage approach. First, we used a random effects model to interpolate risk factors of individuals between follow-up exams. Second, we used forward selection to develop a proportional hazards model for time to incident TIA. We internally validated our model using 10-fold cross-validation.

RESULTS

Among 3575 participants with T2DM, mean (SD) age was 60 (10) years and body mass index was 30 (6) kg/m2. Sixty-nine incident TIAs occurred during 38,364 person-years of follow-up. The multivariable model included age at diagnosis of diabetes (hazard ratio 1.13 (95% confidence interval: 1.05,1.21) per year), systolic blood pressure (1.25 (1.04,1.49) per 10 mmHg), a quadratic function of diastolic blood pressure, and history of congestive heart failure (2.08 (1.26, 3.42)). The median cross-validated Harrell's C-index was 0.80.

CONCLUSION

Blood pressure and heart failure are risk factors for the earliest stages of cerebrovascular disease.

Modelling tool to support decision-making in the NHS Health Check programme: workshops, systematic review and co-production with users

BACKGROUND

Local authorities in England commission the NHS Health Check programme to invite everyone aged 40-74 years without pre-existing conditions for risk assessment and eventual intervention, if needed. However, the programme's effectiveness, cost-effectiveness and equity impact remain uncertain.

AIM

To develop a validated open-access flexible web-based model that enables local commissioners to quantify the cost-effectiveness and potential for equitable population health gain of the NHS Health Check programme.

OBJECTIVES

The objectives were as follows: (1) co-produce with stakeholders the desirable features of the user-friendly model; (2) update the evidence base to support model and scenario development; (3) further develop our computational model to allow for developments and changes to the NHS Health Check programme and the diseases it addresses; (4) assess the effectiveness, cost-effectiveness and equity of alternative strategies for implementation to illustrate the use of the tool; and (5) propose a sustainability and implementation plan to deploy our user-friendly computational model at the local level.

DESIGN

Co-production workshops surveying the best-performing local authorities and a systematic literature review of strategies to increase uptake of screening programmes informed model use and development. We then co-produced the workHORSE (working Health Outcomes Research Simulation Environment) model to estimate the health, economic and equity impact of different NHS Health Check programme implementations, using illustrative-use cases.

SETTING

Local authorities in England.

PARTICIPANTS

Stakeholders from local authorities, Public Health England, the NHS, the British Heart Foundation, academia and other organisations participated in the workshops. For the local authorities survey, we invited 16 of the best-performing local authorities in England.

INTERVENTIONS

The user interface allows users to vary key parameters that represent programme activities (i.e. invitation, uptake, prescriptions and referrals). Scenarios can be compared with each other.

MAIN OUTCOME MEASURES

Disease cases and case-years prevented or postponed, incremental cost-effectiveness ratios, net monetary benefit and change in slope index of inequality.

RESULTS

The survey of best-performing local authorities revealed a diversity of effective approaches to maximise the coverage and uptake of NHS Health Check programme, with no distinct 'best buy'. The umbrella literature review identified a range of effective single interventions. However, these generally need to be combined to maximally improve uptake and health gains. A validated dynamic, stochastic microsimulation model, built on robust epidemiology, enabled service options analysis. Analyses of three contrasting illustrative cases estimated the health, economic and equity impact of optimising the Health Checks, and the added value of obtaining detailed local data. Optimising the programme in Liverpool can become cost-effective and equitable, but simply changing the invitation method will require other programme changes to improve its performance. Detailed data inputs can benefit local analysis.

LIMITATIONS

Although the approach is extremely flexible, it is complex and requires substantial amounts of data, alongside expertise to both maintain and run.

CONCLUSIONS

Our project showed that the workHORSE model could be used to estimate the health, economic and equity impact comprehensively at local authority level. It has the potential for further development as a commissioning tool and to stimulate broader discussions on the role of these tools in real-world decision-making.

FUTURE WORK

Future work should focus on improving user interactions with the model, modelling simulation standards, and adapting workHORSE for evaluation, design and implementation support.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42019132087.

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. 25, No. 35. See the NIHR Journals Library website for further project information.

Prediction of mortality and major cardiovascular complications in type 2 diabetes: External validation of UK Prospective Diabetes Study outcomes model version 2 in two European observational cohorts

AIM

To externally validate the UK Prospective Diabetes Study Outcomes Model version 2 (UKPDS-OM2) by comparing the predicted and observed outcomes in two European population-based cohorts of people with type 2 diabetes.

MATERIALS AND METHODS

We used data from the Casale Monferrato Survey (CMS; n = 1931) and a subgroup of the Hoorn Diabetes Care System (DCS) cohort (n = 5188). The following outcomes were analysed: all-cause mortality, myocardial infarction (MI), ischaemic heart disease (IHD), stroke, and congestive heart failure (CHF). Model performance was assessed by comparing predictions with observed cumulative incidences in each cohort during follow-up.

RESULTS

All-cause mortality was overestimated by the UKPDS-OM2 in both the cohorts, with a bias of 0.05 in the CMS and 0.12 in the DCS at 10 years of follow-up. For MI, predictions were consistently higher than observed incidence over the entire follow-up in both cohorts (10 years bias 0.07 for CMS and 0.10 for DCS). The model performed well for stroke and IHD outcomes in both cohorts. CHF incidence was predicted well for the DCS (5 years bias -0.001), but underestimated for the CMS cohort.

CONCLUSIONS

The UKPDS-OM2 consistently overpredicted the risk of mortality and MI in both cohorts during follow-up. Period effects may partially explain the differences. Results indicate that transferability is not satisfactory for all outcomes, and new or adjusted risk equations may be needed before applying the model to the Italian or Dutch settings.

Cost-Effectiveness of the New 2018 American College of Physicians Glycemic Control Guidance Statements Among US Adults With Type 2 Diabetes

OBJECTIVES

This study aims to estimate the national impact and cost-effectiveness of the 2018 American College of Physicians (ACP) guidance statements compared to the status quo.

METHODS

Survey data from the 2011-2016 National Health and Nutrition Examination were used to generate a national representative sample of individuals with diagnosed type 2 diabetes in the United States. Individuals with A1c <6.5% on antidiabetic medications are recommended to deintensify their A1c level to 7.0% to 8.0% (group 1); individuals with A1c 6.5% to 8.0% and a life expectancy of <10 years are recommended to deintensify their A1c level >8.0% (group 2); and individuals with A1c >8.0% and a life expectancy of >10 years are recommended to intensify their A1c level to 7.0% to 8.0% (group 3). We used a Markov-based simulation model to evaluate the lifetime cost-effectiveness of following the ACP recommended A1c level.

RESULTS

14.41 million (58.1%) persons with diagnosed type 2 diabetes would be affected by the new guidance statements. Treatment deintensification would lead to a saving of $363 600 per quality-adjusted life-year (QALY) lost for group 1 and a saving of $118 300 per QALY lost for group 2. Intensifying treatment for group 3 would lead to an additional cost of $44 600 per QALY gain. Nationally, the implementation of the guidance would add 3.2 million life-years and 1.1 million QALYs and reduce healthcare costs by $47.7 billion compared to the status quo.

CONCLUSIONS

Implementing the new ACP guidance statements would affect a large number of persons with type 2 diabetes nationally. The new guidance is cost-effective.

Healthcare utilization and direct medical cost in the years during and after cancer diagnosis in patients with type 2 diabetes mellitus

AIMS/INTRODUCTION

There is uncertainty about the direct medical costs of type 2 diabetes patients with cancers.

MATERIALS AND METHODS

A population-based retrospective cohort of 99,915 type 2 diabetes patients from the Hong Kong Hospital Authority between 2006 and 2017 was assembled. A total of 16,869 patients who had an initial cancer diagnosis after type 2 diabetes diagnosis were matched with 83,046 patients without cancer (controls) using a matching ratio of up to one-to-five propensity score-matching method. Patients were divided into four categories according to life expectancy. Healthcare service utilization and direct medical costs during the index year, subsequent years and mortality year were compared between patients with and without cancer in each category.

RESULTS

Medical costs of cancer patients in the index year ranged from $US27,533 for patients who died in <1 year to $US11,303 for those survived >3 years. Cancer patients had significantly greater expenditures than controls in the index year (all P < 0.001) and subsequent years ($US4,569 vs $US4,155, P < 0.001). Cancer patients also had greater costs in the year of death, and the difference was significant for patients who survived >3 years after the index year ($US32,558 vs $US28,260). For patients in both groups, patients who survived >3 years had significantly lower costs than those who died in <1 year. Costs incurred in the mortality year were greater than those in the index year and subsequent years. Hospitalization accounted for >90% of the medical costs for both groups in the mortality year.

CONCLUSIONS

Type 2 diabetes patients with cancers incurred greater medical costs in the diagnosis, ensuing and mortality years than type 2 diabetes patients without cancers.

External Validation of the Core Obesity Model to Assess the Cost-Effectiveness of Weight Management Interventions

BACKGROUND

For economic models to be considered fit for purpose, it is vital that their outputs can be interpreted with confidence by clinicians, budget holders and other stakeholders. Consequently, thorough validation of models should be carried out to enhance confidence in their predictions. Here, we present results of external dependent and independent validations of the Core Obesity Model (COM), which was developed to assess the cost-effectiveness of weight management interventions.

OBJECTIVE

The aim was to assess the external validity of the COM (version 6.1), in line with best practice guidance from the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

METHODS

For validation, suitable sources and outcomes were identified, and used to populate the COM with relevant inputs to allow prediction of study outcomes. Study characteristics were entered into the COM to replicate either the studies used to develop the model (dependent validation) or those not included in the model (independent validation). The concordance between predicted and observed outcomes was then assessed using established statistical methods and generation of mean error estimates.

RESULTS

For most outcomes, the predictions of the COM showed good linear correlation with observed outcomes, as evidenced by the high coefficients of determination (R² values). The independent validation revealed a degree of underestimation in predictions of cardiovascular (CV) disease and mortality, and type 2 diabetes.

CONCLUSION

The predictions generated by the risk equations used in the COM showed good concordance both with the studies used to develop the model and with studies not included in the model. In particular, the concordance observed in the external dependent validation suggests that the COM accurately predicts obesity-related event rates observed in the studies used to develop the model. However, the impact of existing CV risk, as well as mortality, is a key area for future refinement of the COM. Our results should increase confidence in the estimates derived from the COM and reduce uncertainty associated with analyses using this model.

Economic Evaluation of Factorial Trials: Cost-Utility Analysis of the Atorvastatin in Factorial With Omega EE90 Risk Reduction in Diabetes 2 × 2 × 2 Factorial Trial of Atorvastatin, Omega-3 Fish Oil, and Action Planning

OBJECTIVES

We applied principles for conducting economic evaluations of factorial trials to a trial-based economic evaluation of a cluster-randomized 2 × 2 × 2 factorial trial. We assessed the cost-effectiveness of atorvastatin, omega-3 fish oil, and an action-planning leaflet, alone and in combination, from a UK National Health Service perspective.

METHODS

The Atorvastatin in Factorial With Omega EE90 Risk Reduction in Diabetes (AFORRD) Trial randomized 800 patients with type 2 diabetes to atorvastatin, omega-3, or their respective placebos and randomized general practices to receive a leaflet-based action-planning intervention designed to improve compliance or standard care. The trial was conducted at 59 UK general practices. Sixteen-week outcomes for each trial participant were extrapolated for 70 years using the United Kingdom Prospective Diabetes Study Outcomes Model v2.01. We analyzed the trial as a 2 × 2 factorial trial (ignoring interactions between action-planning leaflet and medication), as a 2 × 2 × 2 factorial trial (considering all interactions), and ignoring all interactions.

RESULTS

We observed several qualitative interactions for costs and quality-adjusted life-years (QALYs) that changed treatment rankings. However, different approaches to analyzing the factorial design did not change the conclusions. There was a ≥99% chance that atorvastatin is cost-effective and omega-3 is not, at a £20 000/QALY threshold.

CONCLUSIONS

Atorvastatin monotherapy was the most cost-effective combination of the 3 trial interventions at a £20 000/QALY threshold. Omega-3 fish oil was not cost-effective, while there was insufficient evidence to draw firm conclusions about action planning. Recently-developed methods for analyzing factorial trials and combining parameter and sampling uncertainty were extended to estimate cost-effectiveness acceptability curves within a 2x2x2 factorial design with model-based extrapolation.

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

OBJECTIVES

The cardiovascular outcomes challenge examined the predictive accuracy of 10 diabetes models in estimating hard outcomes in 2 recent cardiovascular outcomes trials (CVOTs) and whether recalibration can be used to improve replication.

METHODS

Participating groups were asked to reproduce the results of the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME) and the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program. Calibration was performed and additional analyses assessed model ability to replicate absolute event rates, hazard ratios (HRs), and the generalizability of calibration across CVOTs within a drug class.

RESULTS

Ten groups submitted results. Models underestimated treatment effects (ie, HRs) using uncalibrated models for both trials. Calibration to the placebo arm of EMPA-REG OUTCOME greatly improved the prediction of event rates in the placebo, but less so in the active comparator arm. Calibrating to both arms of EMPA-REG OUTCOME individually enabled replication of the observed outcomes. Using EMPA-REG OUTCOME-calibrated models to predict CANVAS Program outcomes was an improvement over uncalibrated models but failed to capture treatment effects adequately. Applying canagliflozin HRs directly provided the best fit.

CONCLUSIONS

The Ninth Mount Hood Diabetes Challenge demonstrated that commonly used risk equations were generally unable to capture recent CVOT treatment effects but that calibration of the risk equations can improve predictive accuracy. Although calibration serves as a practical approach to improve predictive accuracy for CVOT outcomes, it does not extrapolate generally to other settings, time horizons, and comparators. New methods and/or new risk equations for capturing these CV benefits are needed.

Comparing the Cohort and Micro-Simulation Modeling Approaches in Cost-Effectiveness Modeling of Type 2 Diabetes Mellitus: A Case Study of the IHE Diabetes Cohort Model and the Economics and Health Outcomes Model of T2DM

BACKGROUND

Economic modeling is widely used in estimating cost-effectiveness in type 2 diabetes mellitus. Because type 2 diabetes is complex and patients are heterogenous, the cohort modeling approach may generate biased estimates of costeffectiveness. The IHE Diabetes Cohort Model (IHE-DCM) was constructed using the cohort approach as an alternative for stakeholders with limited resources, some of whom have voiced reasonable concerns about a lack of transparency with type 2 diabetes micro-simulation models and long run times.

OBJECTIVES

The objective of this study was to inform decision makers by investigating the direction and magnitude of bias of IHE-DCM cost-effectiveness estimates that can be attributed to the cohort modeling approach.

METHODS

Simulation scenarios inspired by the 9th Mount Hood Diabetes Challenge were simulated with IHE-DCM and with a micro-simulation model, the Economic and Health Outcomes Model of T2DM (ECHO-T2DM), and key metrics (absolute and incremental costs and quality-adjusted life-years, event rates, and cost-effectiveness) were compared for evidence of systematic differences. The models were harmonized to the extent possible to ensure that differences were driven primarily by the unit of observation and not by other model differences.

RESULTS

IHE-DCM run times were faster and IHE-DCM produced uniformly larger estimates of absolute life-years, quality-adjusted life-years, and costs than ECHO-T2DM but smaller between-arm (incremental) differences. Estimated incremental cost-effectiveness ratios and net monetary benefits varied similarly and predictably across the scenarios. On average, IHE-DCM estimates of incremental cost-effectiveness ratios and net monetary benefits were CAN$269 (3%) and CAN$2935 (10%) smaller, respectively, than ECHO-T2DM.

CONCLUSIONS

There was little evidence that estimated cost-effectiveness metrics, the outcomes that matter most to stakeholders, differed systematically.

Characterizing the Validity and Real-World Utility of Health Technology Assessments in Healthcare: Future Directions Comment on "Problems and Promises of Health Technologies: The Role of Early Health Economic Modelling"

With their article, Grutters et al raise an important question: What do successful health technology assessments (HTAs) look like, and what is their real-world utility in decision-making? While many HTAs are published in peer-reviewed journals, many are considered proprietary and their attributes remain confidential, limiting researchers’ ability to answer these questions. Models for economic evaluations like cost-effectiveness analyses (CEAs) synthesize a wide range of evidence, are often statistically and mathematically sophisticated, and require untestable assumptions. As such, there is nearly universal agreement among researchers that enhancing transparency is an important issue in health economic modeling. However, the definition of transparency and guidelines for its implementation vary. Model registration combined with a linked database of model-based economic evaluations has been proposed as a solution, whereby registered models and their accompanying technical and nontechnical documentation are sourced into a single publicly-available repository, ideally in a standardized format to ensure consistent and complete representation of features, code, data sources, results, validation exercises, and policy recommendations. When such a repository is ultimately created, modelers will not have to reinvent the wheel for every new drug launched or new treatment pathway. These more open and transparent approaches will have substantial implications for model accuracy, reliability, and validity, improving trust and acceptance by healthcare decision-makers.

A Patient-Level Model to Estimate Lifetime Health Outcomes of Patients With Type 1 Diabetes

OBJECTIVE

To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort.

RESEARCH DESIGN AND METHODS

Data for model development were obtained from the Swedish National Diabetes Register. We derived parametric proportional hazards models predicting the absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed.

RESULTS

The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between the predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was ∼13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for ∼40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycemia, and hyperglycemia as well as lowering HbA_1c in reducing the risk of complications and death.

CONCLUSIONS

Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes and to project events occurring over patients' lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.

Using the BRAVO Risk Engine to Predict Cardiovascular Outcomes in Clinical Trials With Sodium-Glucose Transporter 2 Inhibitors

OBJECTIVE

This study evaluated the ability of the Building, Relating, Assessing, and Validating Outcomes (BRAVO) risk engine to accurately project cardiovascular outcomes in three major clinical trials-BI 10773 (Empagliflozin) Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME), Canagliflozin Cardiovascular Assessment Study (CANVAS), and Dapagliflozin Effect on Cardiovascular Events-Thrombolysis in Myocardial Infarction (DECLARE-TIMI 58) trial-on sodium-glucose cotransporter 2 inhibitors (SGLT2is) to treat patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Baseline data from the publications of the three trials were obtained and entered into the BRAVO model to predict cardiovascular outcomes. Projected benefits of reducing risk factors of interest (A1C, systolic blood pressure [SBP], LDL, or BMI) on cardiovascular events were evaluated, and simulated outcomes were compared with those observed in each trial.

RESULTS

BRAVO achieved the best prediction accuracy when simulating outcomes of the CANVAS and DECLARE-TIMI 58 trials. For EMPA-REG OUTCOME, a mild bias was observed (∼20%) in the prediction of mortality and angina. The effect of risk reduction on outcomes in treatment versus placebo groups predicted by the BRAVO model strongly correlated with the observed effect of risk reduction on the trial outcomes as published. Finally, the BRAVO engine revealed that most of the clinical benefits associated with SGLT2i treatment are through A1C control, although reductions in SBP and BMI explain a proportion of the observed decline in cardiovascular events.

CONCLUSIONS

The BRAVO risk engine was effective in predicting the benefits of SGLT2is on cardiovascular health through improvements in commonly measured risk factors, including A1C, SBP, and BMI. Since these benefits are individually small, the use of the complex, dynamic BRAVO model is ideal to explain the cardiovascular outcome trial results.

A Systematic Review of Model-Based Economic Evaluations of Treatments for Venous Leg Ulcers

OBJECTIVE

The aim of this review was to identify, and assess the quality of, published model-based economic evaluations relating to treatments for patients with venous leg ulcers to help inform future decision-analytic models in this clinical area.

METHODS

A systematic literature search was performed on six electronic databases, from database inception until 21 May 2018. Search results were screened against predefined criteria by two independent reviewers. Data was then extracted from the included studies using a standardised form, whilst the decision-analytic model-specific Philips Checklist was used to assess quality and to inform model critique.

RESULTS

A total of 23 models were identified, 12 studies used a Markov modelling approach, five used decision trees and six studies did not detail the model type. Studies were predominantly from the National Health Service (NHS)/payer perspective, with only two taking a societal perspective. Interventions were wide ranging, but dressing technologies (11/23) were most common. The intervention studied was found to be dominant in 22/23 studies. The reporting quality of papers was mostly low, with evidence behind model structures, time horizons and data selection consistently underreported across the included papers.

CONCLUSIONS

This review has identified a sizeable literature of model-based economic evaluations, evaluating treatments for venous leg ulcers. However, the methods used to conduct such studies were generally poorly reported. In particular, the reporting of evidence surrounding the model structure, justification of the time horizon used and the rationale for selecting data inputs should be focused on in any future models developed.

Economic Simulation Modeling in Type 2 Diabetes

PURPOSE OF REVIEW

This paper provides an overview of type 2 diabetes economic simulation modeling and reviews current topics of discussion and major challenges in the field.

RECENT FINDINGS

Important challenges in the field include increasing the generalizability of models and improving transparency in model reporting. To identify and address these issues, modeling groups have organized through the Mount Hood Diabetes Challenge meetings and developed tools (i.e., checklist, impact inventory) to standardize modeling methods and reporting of results. Accordingly, many newer diabetes models have begun utilizing these tools, allowing for improved comparability between diabetes models. In the last two decades, type 2 diabetes simulation models have improved considerably, due to the collaborative work performed through the Mount Hood Diabetes Challenge meetings. To continue to improve diabetes models, future work must focus on clarifying diabetes progression in racial/ethnic minorities and incorporating equity considerations into health economic analysis.

Systematic Literature Review and Critical Appraisal of Health Economic Models Used in Cost-Effectiveness Analyses in Non-Alcoholic Steatohepatitis: Potential for Improvements

BACKGROUND

Non-alcoholic steatohepatitis (NASH) is a severe, typically progressive form of non-alcoholic fatty liver disease (NAFLD). The global prevalence of NASH is increasing, driven partly by the global increase in obesity and type 2 diabetes mellitus (T2DM), such that NASH is now a leading cause of cirrhosis. There is currently an unmet clinical need for efficacious and cost-effective treatments for NASH; no pharmacologic agents have an approved indication for NASH.

OBJECTIVE

Our objective was to summarise and critically appraise published health economic models of NASH, to evaluate their quality and suitability for use in the assessment of novel treatments for NASH, and to identify knowledge gaps, challenges and opportunities for future modelling.

METHODS

A systematic literature review was performed using the MEDLINE, Embase, Cochrane Library and EconLit databases to identify published health economic analyses in patients with NAFLD or NASH. Supplementary hand searches of grey literature were also performed. Articles published up to November 2019 were included in the review. Quality assessment of identified studies was also performed.

RESULTS

A total of 19 articles comprising 16 unique models including either NAFLD as a whole or NASH alone were included in the review. Structurally, most models had a state-transition component; in terms of health states, two different approaches to early disease states were used, modelling either progression through fibrosis stages or NAFLD/NASH-specific health states. Conditions that frequently co-exist with NASH, such as obesity, T2DM and cardiovascular disease were not captured in models identified here. Late-stage complications such as cirrhosis, decompensated cirrhosis and hepatocellular carcinoma were consistently included, but input data (e.g. costs, utilities and transition probabilities) for late-stage complications were frequently sourced from other liver disease areas. The quality of included studies was heterogenous, and only a small proportion of studies reported internal and external validation processes.

CONCLUSION

The health economic models identified in this review are associated with limitations primarily driven by a lack of NASH-specific data. Identified models also largely overlooked the intricate association between NASH and other conditions, including obesity and T2DM, and did not capture the increased risk of cardiovascular events associated with NASH. High-quality, transparent, validated health economic models of NASH will be required to evaluate the cost effectiveness of treatments currently in development, particularly compounds that may target other non-hepatic outcomes.

The Use of Computer Simulation Modeling to Estimate Complications in Patients with Type 2 Diabetes Mellitus: Comparative Validation of the Cornerstone Diabetes Simulation Model

OBJECTIVE

The objective of this study was to assess the validity of the Cornerstone Diabetes Simulation (CDS), a Microsoft Excel^®-based patient-level simulation for type 2 diabetes mellitus based on risk equations from the revised United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2, also known as UKPDS 82).

METHODS

Three levels of validation were conducted. Internal validation was assessed through independent review and model stress-testing. External validation was addressed by populating the CDS with baseline characteristics and treatment effects from three major diabetes clinical trials used in the Fifth Mount Hood Diabetes Challenge (MH5) for computer simulation models. Cross-validation of predicted outcomes was tested versus eight models that participated in the MH5. Simulated results were compared with observed clinical outcomes via the coefficient of determination (R²) for both the absolute risk of each clinical outcome and the difference in absolute risk between control and intervention arm in each trial. We ensured transparency of all model inputs and assumptions in reporting.

RESULTS

The CDS could be used to predict 18 of 39 single and composite endpoints across the three trials. The model obtained an R² of 0.637 for predicted versus observed absolute risks, and an R² of 0.442 for predicted versus observed risk differences between control and intervention. Among the other eight models, only one obtained a higher R² value under both definitions, albeit based on only four predicted endpoints.

CONCLUSIONS

The CDS provides good predictions of diabetes-related complications when compared to observed trial outcomes and previously validated models. The model has value as a validated tool in cost-effectiveness evaluations.