Economic models in type 2 diabetes

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.

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).

Health State Utility Values of Type 2 Diabetes Mellitus and Related Complications: A Systematic Review and Meta-Analysis

OBJECTIVES

This study aims to synthesize health state utility values (HSUVs) of type 2 diabetes mellitus (T2DM) and its related complications published in the literature, conducting a meta-analysis of the data when possible.

METHODS

We conducted a systematic search in MEDLINE and School of Health and Related Research Health Utilities Database repository. Studies focused on T2DM and its complications reporting utility values elicited using direct and indirect methods were selected. We categorized the results according to the instrument to describe health and meta-analyzed them accordingly. Data included in the analysis were pooled in a fixed-effect model by the inverse of variance mean and random-effects DerSimonian-Laird method. Two approaches on sensitivity analysis were performed: leave-one-out method and including data of HSUVs obtained by foreign population value sets.

RESULTS

We identified 70 studies for the meta-analysis from a total of 467 studies. Sufficient data to pool T2DM HSUVs from EQ-5D instrument, hypoglycemia, and stroke were obtained. HSUVs varied from 0.7 to 0.92 in direct valuations, and the pooled mean of 3-level version of EQ-5D studies was 0.772 (95% confidence interval 0.763-0.78) and of 5-level version of EQ-5D 0.815 (95% confidence interval 0.808-0.823). HSUVs of complications varied from 0.739 to 0.843, or reductions of HSUVs between -0.014 and -0.094. In general, HSUVs obtained from 3-level version of EQ-5D and Health Utility Index 3 instruments were lower than those directly elicited. A considerable amount of heterogeneity was observed. Some complications remained unable to be pooled due to scarce of original articles.

CONCLUSIONS

T2DM and its complications have a considerable impact on health-related quality of life. 5-level version of EQ-5D estimates seems comparable with direct elicited HSUVs.

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 of second-line empagliflozin versus liraglutide for type 2 diabetes in the United States

AIM

To estimate the cost-effectiveness of sequential use of the sodium-glucose co-transporter-2 inhibitor empagliflozin and glucagon-like peptide-1 receptor agonist liraglutide after metformin in patients with type 2 diabetes (T2D) from the US payer perspective.

MATERIALS AND METHODS

An economic simulation model with a lifetime horizon was developed to estimate T2D-related complications (including cardiovascular [CV] death, myocardial infarction, stroke, and renal outcomes) using EMPA-REG OUTCOME data or UK Prospective Diabetes Study risk equations, in patients with or without a history of cardiovascular disease (CVD), respectively. Evidence synthesis methods were used to provide effectiveness inputs for empagliflozin and liraglutide. Population characteristics, adverse event rates, treatment escalation, costs ($2019), and utilities (both discounted 3%/year) were taken from US sources.

RESULTS

Compared with second-line liraglutide in the overall T2D population, second-line empagliflozin was dominant as it was associated with lower total lifetime cost ($11 244/patient less) and resulted in a quality-adjusted life-year (QALY) gain (0.32/patient). Second-line empagliflozin was associated with reductions in CV death (by 5%) and lower cumulative complication rates in patients with CVD (by 2%), relative to second-line liraglutide. These findings were consistent among patients with co-morbid CVD, with gains in incremental QALYs (0.43/patient) and lower lifetime cost (by $10 175/patient) relative to second-line liraglutide. Scenario analyses consistently showed dominance for second-line empagliflozin.

CONCLUSION

For patients with T2D, use of second-line empagliflozin combined with metformin was a dominant strategy for US payers, associated with extended survival, improved QALYs, and lower costs compared with second-line liraglutide.

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.

Decision models in type 2 diabetes mellitus: A systematic review

AIMS

To reduce the burden of type 2 diabetes (T2DM), the disease decision model plays a vital role in supporting decision-making. Currently, there is no comprehensive summary and assessment of the existing decision models for T2DM. The objective of this review is to provide an overview of the characteristics and capabilities of published decision models for T2DM. We also discuss which models are suitable for different study demands.

MATERIALS AND METHODS

Four databases (PubMed, Web of Science, Embase, and the Cochrane Library) were electronically searched for papers published from inception to August 2020. Search terms were: "Diabetes-Mellitus, Type 2", "cost-utility", "quality-of-life", and "decision model". Reference lists of the included studies were manually searched. Two reviewers independently screened the titles and abstracts following the inclusion and exclusion criteria. If there was insufficient information to include or exclude a study, then a full-text version was sought. The extracted information included basic information, study details, population characteristics, basic modeling methodologies, model structure, and data inputs for the included applications, model outcomes, model validation, and uncertainty.

RESULTS

Fourteen unique decision models for T2DM were identified. Markov chains and risk equations were utilized by four and three models, respectively. Three models utilized both. Except for the Archimedes model, all other models (n = 13) implemented an annual cycle length. The time horizon of most models was flexible. Fourteen models had differences in the division of health states. Ten models emphasized macrovascular and microvascular complications. Six models included adverse events. Majority of the models (n = 11) were patient-level simulation models. Eleven models simulated annual changes in risk factors (body mass index, glycemia, HbA1c, blood pressure (systolic and/or diastolic), and lipids (total cholesterol and/or high-density lipoprotein)). All models reported the main data sources used to develop health states of complications. Most models (n = 11) could deal with the uncertainty of models, which were described in varying levels of detail in the primary studies. Eleven studies reported that one or more validation checks were performed.

CONCLUSIONS

The existing decision models for T2DM are heterogeneous in terms of the level of detail in the classification of health states. Thus, more attention should be focused on balancing the desired level of complexity against the required level of transparency in the development of T2DM decision models.

Data Analysis of the Risks of Type 2 Diabetes Mellitus Complications before Death Using a Data-Driven Modelling Approach: Methodologies and Challenges in Prolonged Diseases

(1) Background: A disease prediction model derived from real-world data is an important tool for managing type 2 diabetes mellitus (T2D). However, an appropriate prediction model for the Asian T2D population has not yet been developed. Hence, this study described construction details of the T2D Holistic Care model via estimating the probability of diabetes-related complications and the time-to-occurrence from a population-based database. (2) Methods: The model was based on the database of a Taiwan pay-for-performance reimbursement scheme for T2D between November 2002 and July 2017. A nonhomogeneous Markov model was applied to simulate multistate (7 main complications and death) transition probability after considering the sequential and repeated difficulties. (3) Results: The Markov model was constructed based on clinical care information from 163,452 patients with T2D, with a mean follow-up time of 5.5 years. After simulating a cohort of 100,000 hypothetical patients over a 10-year time horizon based on selected patient characteristics at baseline, a good predicted complication and mortality rates with a small range of absolute error (0.3–3.2%) were validated in the original cohort. Better and optimal predictabilities were further confirmed compared to the UKPDS Outcomes model and applied the model to other Asian populations, respectively. (4) Contribution: The study provides well-elucidated evidence to apply real-world data to the estimation of the occurrence and time point of major diabetes-related complications over a patient’s lifetime. Further applications in health decision science are encouraged.

Overview and Use of Tools for Selecting Modelling Techniques in Health Economic Studies

The availability and use of tools to guide the choice of modelling technique are not well understood. Our study aims to review existing tools and explore the use of those tools in health economic models. Two reviews and one case study were conducted. Review 1 aimed to identify tools based on expert opinion and citation searching and explore the value of the tools for health economic models. Review 2, based on citation searching, aimed to describe how those tools have been used in health economic models. Both reviews were conducted using Web of Science and Scopus. Two independent reviewers selected studies for inclusion. A case study, focused on economic evaluations of antipsychotic medication in schizophrenia, was conducted to compare the modelling techniques used by existing models with modelling techniques recommended by identified tools. Seven tools were identified, of which the revised Brennan's toolkit, was assessed to be the most appropriate for health economic models. The seven tools were cited 126 times in publications reporting health economic models. Only 17 of these (13.5%) reported that they used the tool(s) to guide the choice of modelling technique. Application of these tools suggested discrete event simulation is most appropriate for modelling antipsychotic medication in schizophrenia, but discrete event simulation was only used by 17% of existing models. There is considerable inconsistency between the modelling techniques used by existing models and modelling techniques recommended by tools. It is recommended that for future modelling studies the choice of modelling technique should be justified, this can be achieved by the application of model selection tools, such as the revised Brennan's toolkit. Future research is required to explore the barriers to using model selection tools in health economic models and to update existing tools and make them easier to use.

Replication of Published Health Economic Obesity Models: Assessment of Facilitators, Hurdles and Reproduction Success

OBJECTIVES

This research aims to (1) replicate published health economic models, (2) compare reproduced results with original results, (3) identify facilitators and hurdles to model replicability and determine reproduction success, and (4) suggest model replication reporting standards to enhance model reproducibility, in the context of health economic obesity models.

METHODS

Four health economic obesity models simulating an adult UK population were identified, selected for replication, and evaluated using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist. Reproduction results were compared to original results, focusing on cost-effectiveness outcomes, and the resulting reproduction success was assessed by published criteria. Replication facilitators and hurdles were identified and transferred into related reporting standards.

RESULTS

All four case studies were state-transition models simulating costs and quality-adjusted life-years (QALYs). Comparing original versus reproduction outcomes, the following deviation ranges were observed: costs - 3.9 to 16.1% (mean over all model simulations 3.78%), QALYs - 3.7 to 2.1% (mean - 0.11%), and average cost-utility ratios - 3.0 to 17.9% (mean 4.28%). Applying different published criteria, an overall reproduction success was observed for three of four models. Key replication facilitators were input data tables and model diagrams, while missing standard deviations and missing formulas for equations were considered as key hurdles.

CONCLUSIONS

This study confirms the feasibility of rebuilding health economic obesity models, but minor to major assumptions were needed to fill reporting gaps. Model replications can help to assess the quality of health economic model documentation and can be used to validate current model reporting practices. Simple changes to actual CHEERS reporting criteria may solve identified replication hurdles.

Cost-effectiveness analysis of empagliflozin versus sitagliptin as second-line therapy for treatment in patients with type 2 diabetes in the United States

AIM

To estimate the cost-effectiveness of sequential addition of empagliflozin versus sitagliptin after metformin in patients with type 2 diabetes (T2D) with or without cardiovascular disease (CVD) from the perspective of the US healthcare payer.

METHODS

An individual simulation model predicted lifetime diabetes-related complications, using UKPDS-OM2 equations in patients without CVD, and EMPA-REG OUTCOME equations in patients with CVD. Additional US-based sources informed inputs for population characteristics, adverse events, non-CV death, treatment escalation, quality of life and costs. Costs and quality-adjusted life-years (QALYs) were discounted 3.0% annually.

RESULTS

The incremental cost-effectiveness ratio (ICER) for second-line empagliflozin versus sitagliptin in the overall T2D population was $6967/QALY. Empagliflozin led to longer CVD-free survival (0.07 years) and an 11% reduction in CV death in patients with CVD compared with sitagliptin. Empagliflozin resulted in greater benefits with greater costs in patients with versus without baseline CVD, yielding ICERs of $3589/QALY versus $12 577/QALY, respectively. Results were consistent across a range of deterministic and probabilistic sensitivity analyses and scenarios.

CONCLUSION

Compared with sitagliptin, empagliflozin was cost-effective (at $50 000/QALY US threshold) as a second-line treatment to metformin for T2D patients with or without CVD in the United States. Our findings lend additional support for more widespread adoption of guidelines by healthcare decision-makers for T2D treatment.

Cost-effectiveness of intensive interventions compared to standard care in individuals with type 2 diabetes: A systematic review and critical appraisal of decision-analytic models

AIMS

The objective of this systematic review is to identify and assess the quality of published decision-analytic models evaluating the long-term cost-effectiveness of target-driven intensive interventions for single and multifactorial risk factor control compared to standard care in people with type 2 diabetes.

METHODS

We searched the electronic databases MEDLINE, the National Health Service Economic Evaluation Database, Web of Science and the Cochrane Library from inception to October 31, 2019. Articles were eligible for inclusion if the studies had used a decision-analytic model evaluating both the long-term costs and benefits associated with intensive interventions for risk factor control compared to standard care in people with type 2 diabetes. Data were extracted using a standardised form, while quality was assessed using the decision-analytic model-specific Philips-criteria.

RESULTS

Overall, nine articles (11 models) were identified, four models evaluated intensive glycaemic control, three evaluated intensive blood pressure control, two evaluated intensive lipid control, and two evaluated intensive multifactorial interventions. Six reported using discrete-time simulations modelling approach, whereas five reported using a Markov modelling framework. The majority, seven studies, reported that the intensive interventions were dominant or cost-effective, given the assumptions and analytical perspective taken. The methodological and reporting quality of the studies was generally weak, with only four studies fulfilling more than 50% of their applicable Philips-criteria.

CONCLUSIONS

This is the first systematic review of decision-analytic models of target-driven intensive interventions for single and multifactorial risk factor control in individuals with type 2 diabetes. Identified shortcomings are lack of transparency in data identification and evidence synthesis as well as for the selection of the modelling approaches. Future models should aim to include greater evaluation of the quality of the data sources used and the assessment of uncertainty in the model.

Development and validation of a Health Policy Model of Type 2 diabetes in Chinese setting

Aim: Due to the difference in epidemiology and outcomes between eastern and western populations with Type 2 diabetes mellitus (T2DM), an important challenge is determining how useful the outcomes from diabetes models based on western populations are for eastern patients. Consequently, the principal aim of this study was to develop and validate a Health Policy Model (Chinese Outcomes Model for T2DM [COMT]) for supporting Chinese medical and health economic studies. Methods: The model is created to simulate a series of important complications of T2DM diabetes based on the latest Risk Equations for Complications of Type 2 Diabetes, which was adjusted by adding the adjustment regulator to the linear predictor within the risk equation. The validity of the model was conducted by using a total of 171 validation outcomes from seven studies in eastern populations and ten studies in western populations. The simulation cohorts in the COMT model were generated by copying each validation study's baseline characteristics. Concordance was tested by assessing the difference between the identity (45°) line and the best-fitting regression of the scatterplots for the predicted versus observed outcomes. Results: The slope coefficients of the best-fitting regression line between the predicted and corresponding observed actual outcomes was 0.9631 and the R² was 0.8701. There were major differences between western and eastern populations. The slope and R² of predictions were 0.9473 and 0.9272 in the eastern population and 1.0566 and 0.8863 in the western population, which showed more perfect agreement with the observed values in the eastern population than the western populations. The subset of macro-vascular and micro-vascular outcomes in the eastern population showed an identical tendency (the slope coefficient was close to 1), and mortality outcomes showed a slight tendency toward overestimation (the slope coefficient was close to 0.9208). Some degree of underprediction of macro-vascular and micro-vascular end points and overprediction of mortality end point was found in the western population. Conclusion: The COMT diabetes model simulated the long-term patient outcomes observed in eastern Asian T2DM patients with prediction accuracy. This study supports the COMT as a credible tool for Chinese healthcare decision makers. Further work is necessary to incorporate new local data to improve model validity and credibility.

External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement-a protocol for a systematic review

BACKGROUND

Type 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM.

METHODS

We will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards.

DISCUSSION

The proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017069983 .

Long-term cost reduction of routine medications following a residential programme combining physical activity and nutrition in the treatment of type 2 diabetes: a prospective cohort study

OBJECTIVES

To demonstrate that lifestyle modifications will reduce the cost of routine medications in individuals with type 2 diabetes (T2D), through a mechanism involving glycaemic control.

DESIGN

A within-trial cost-medication analysis with a 1-year time horizon.

SETTING

Controlled environment within the spa resort of Chatel-Guyon, France.

PARTICIPANTS

Twenty-nine participants (aged 50-70 years) with T2D.

INTERVENTIONS

A 1-year follow-up intervention, beginning with a 3-week residential programme combining high exercise volume (15-20 hours/week), restrictive diet (-500 kcal/day) and education. Participants continued their routine medication, independently managed by their general practitioner.

MAIN OUTCOME MEASURES

Number of medications, number of pills, cost of medications and health-related outcomes.

RESULTS

Twenty-six participants completed the 1-year intervention. At 1 year, 14 patients out of 26 (54%) stopped/decreased their medications whereas only 5 (19%) increased or introduced new drugs (χ²=6.3, p=0.02). The number of pills per day decreased by 1.3±0.3 at 12 months (p<0.001). The annual cost of medications for T2D were lower at 1 year (€135.1±43.9) versus baseline (€212.6±35.8) (p=0.03). The regression coefficients on costs of routine medication were 0.507 (95% CI 0.056 to 0.959, p=0.027) for HbA1c and 0.156 (95% CI -0.010 to 0.322, p=0.06) for blood glucose levels. Diabetics patients with HbA1c >6.5% in the highest (last) quartile doubled their routine medication costs (66% vs 33%, p=0.037).

CONCLUSIONS

Individuals with T2D reduced routine medication costs following a long-term lifestyle intervention that started with a 3-week residential programme. Combining high exercise volume, restrictive diet and education effectively supported the health of T2D. The main factor explaining reduced medication costs was better glycaemic control, independent of weight changes. Despite limitations precluding generalisability, cost-effective results of reduced medication should contribute to the evidence base required to promote lifestyle interventions for individuals with T2D.

TRIAL REGISTRATION NUMBER

NCT00917917; Post-results.

How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review

BACKGROUND

There are an increasing number of studies using simulation models to conduct cost-effectiveness analyses for type 2 diabetes mellitus.

OBJECTIVE

To evaluate the relationship between improvements in glycosylated haemoglobin (HbA_1c) and simulated health outcomes in type 2 diabetes cost-effectiveness studies.

METHODS

A systematic review was conducted on MEDLINE and EMBASE to collect cost-effectiveness studies using type 2 diabetes simulation models that reported modelled health outcomes of blood glucose-related interventions in terms of quality-adjusted life-years (QALYs) or life expectancy (LE). The data extracted included information used to characterise the study cohort, the intervention's treatment effects on risk factors and model outcomes. Linear regressions were used to test the relationship between the difference in HbA_1c (∆HbA_1c) and incremental QALYs (∆QALYs) or LE (∆LE) of intervention and control groups. The ratio between the ∆QALYs and ∆LE was calculated and a scatterplot between the ratio and ∆HbA_1c was used to explore the relationship between these two.

RESULTS

Seventy-six studies were included in this research, contributing to 124 pair of comparators. The pooled regressions indicated that the marginal effect of a 1% HbA_1c decrease in intervention resulted in an increase in life-time QALYs and LE of 0.371 (95% confidence interval 0.286-0.456) and 0.642 (95% CI 0.494-0.790), respectively. No evidence of heterogeneity between models was found. An inverse exponential relationship was found and fitted between the ratio (∆QALY/∆LE) and ∆HbA_1c.

CONCLUSION

There is a consistent relationship between ∆HbA_1c and ∆QALYs or ∆LE in cost-effectiveness analyses using type 2 diabetes simulation models. This relationship can be used as a diagnostic tool for decision makers.

Direct medical costs attributable to type 2 diabetes mellitus: a population-based study in Catalonia, Spain

We estimated healthcare costs associated with patients with type 2 diabetes compared with non-diabetic subjects in a population-based primary care database through a retrospective analysis of economic impact during 2011, including 126,811 patients with type 2 diabetes in Catalonia, Spain. Total annual costs included primary care visits, hospitalizations, referrals, diagnostic tests, self-monitoring test strips, medication, and dialysis. For each patient, one control matched for age, gender and managing physician was randomly selected from a population database. The annual average cost per patient was €3110.1 and €1803.6 for diabetic and non-diabetic subjects, respectively (difference €1306.6; i.e., 72.4 % increased cost). The costs of hospitalizations were €1303.1 and €801.6 (62.0 % increase), and medication costs were €925.0 and €489.2 (89.1 % increase) in diabetic and non-diabetic subjects, respectively. In type 2 diabetic patients, hospitalizations and medications had the greatest impact on the overall cost (41.9 and 29.7 %, respectively), generating approximately 70 % of the difference between diabetic and non-diabetic subjects. Patients with poor glycaemic control (glycated haemoglobin >7 %; >53 mmol/mol) had average costs of €3296.5 versus €2848.5 for patients with good control. In the absence of macrovascular complications, average costs were €3008.1 for diabetic and €1612.4 for non-diabetic subjects, while its presence increased costs to €4814.6 and €3306.8, respectively. In conclusion, the estimated higher costs for type 2 diabetes patients compared with non-diabetic subjects are due mainly to hospitalizations and medications, and are higher among diabetic patients with poor glycaemic control and macrovascular complications.

Cost-effectiveness of a risk-based secondary screening programme of type 2 diabetes

OBJECTIVE

The objective of this study was to develop a long-term economic model for type 2 diabetes to describe the entire spectrum of the disease over a wide range of healthcare programmes. The model evaluates a public health, risk-based screening programme in a country specific setting.

METHODS

The lifespan of persons and important phases of the disease and related interventions are recorded in a Markov model, which first simulates the effect of screening, then replicates important complications of diabetes, follows the progression of individuals through physiological variables and finally calculates outcomes in monetary and naturalistic units.

RESULTS

The introduction of the screening programme nearly doubled the proportion of diagnosed patients at the age of 50 and prolonged life expectancy. Three-yearly screening gained 0.0229 quality adjusted life years for an additional €83 per person compared with no screening and resulted an incremental cost-effectiveness ratio of €3630/quality adjusted life years.

CONCLUSION

From the economic perspective introduction of the 3-yearly screening programme is justifiable and it provides a good value for money. Copyright © 2016 John Wiley & Sons, Ltd.

A Systematic Review of Cost-Effectiveness Models in Type 1 Diabetes Mellitus

BACKGROUND

Critiques of cost-effectiveness modelling in type 1 diabetes mellitus (T1DM) are scarce and are often undertaken in combination with type 2 diabetes mellitus (T2DM) models. However, T1DM is a separate disease, and it is therefore important to appraise modelling methods in T1DM.

OBJECTIVES

This review identified published economic models in T1DM and provided an overview of the characteristics and capabilities of available models, thus enabling a discussion of best-practice modelling approaches in T1DM.

METHODS

A systematic review of Embase(®), MEDLINE(®), MEDLINE(®) In-Process, and NHS EED was conducted to identify available models in T1DM. Key conferences and health technology assessment (HTA) websites were also reviewed. The characteristics of each model (e.g. model structure, simulation method, handling of uncertainty, incorporation of treatment effect, data for risk equations, and validation procedures, based on information in the primary publication) were extracted, with a focus on model capabilities.

RESULTS

We identified 13 unique models. Overall, the included studies varied greatly in scope as well as in the quality and quantity of information reported, but six of the models (Archimedes, CDM [Core Diabetes Model], CRC DES [Cardiff Research Consortium Discrete Event Simulation], DCCT [Diabetes Control and Complications Trial], Sheffield, and EAGLE [Economic Assessment of Glycaemic control and Long-term Effects of diabetes]) were the most rigorous and thoroughly reported. Most models were Markov based, and cohort and microsimulation methods were equally common. All of the more comprehensive models employed microsimulation methods. Model structure varied widely, with the more holistic models providing a comprehensive approach to microvascular and macrovascular events, as well as including adverse events. The majority of studies reported a lifetime horizon, used a payer perspective, and had the capability for sensitivity analysis.

CONCLUSIONS

Several models have been developed that provide useful insight into T1DM modelling. Based on a review of the models identified in this study, we identified a set of 'best in class' methods for the different technical aspects of T1DM modelling.

Use of quality checklists and need for disease-specific guidance in economic evaluations: a meta-review

Economic evaluations have become an essential part of reimbursement decisions in a wide range of countries. To ensure high quality, a variety of checklists with different purposes have been developed and implemented enabling assessment of these evaluations. Three of these checklists are most frequently used and are recommended by the Cochrane Handbook for Systematic Reviews for critical appraisal (Drummond, CHEC and Philips). Every checklist is developed with a different purpose having, for example, a focus on reporting or conducting and on modeling or trial-based evaluations. This review outlines the heterogeneity in choice and implementation of these quality checklists in an incorrect manner. This ultimately results in under- and even possibly overestimation of quality of included economic evaluations. More guidance in selecting correct checklists suiting the purpose of the quality check is therefore of utmost importance. Moreover, it appears that current checklists are lacking detailed disease-specific guidance resulting in models not correctly reflecting disease progression. Therefore, outcomes indicate that the problem of the wide variability of methodological choices is prevalent in some other disease areas too, regardless of the availability of quality checklists. More international collaboration should therefore be initiated in developing and publishing standardized and open source disease-specific reference models to overcome this problem.

Methods applied in cost-effectiveness models for treatment strategies in type 2 diabetes mellitus and their use in Health Technology Assessments: a systematic review of the literature from 2008 to 2013

OBJECTIVE

To identify and compare health-economic models that were developed to evaluate the cost-effectiveness of treatments for type 2 diabetes mellitus (T2DM), and their use within Health Technology Assessments (HTAs).

METHODS

In total, six commonly used databases were searched for articles published between October 2008 and January 2013, using a protocolized search strategy and inclusion criteria. The websites of HTA organizations in nine countries, and proceedings from five relevant conferences, were also reviewed. The identified new health-economic models were qualitatively assessed using six criteria that were developed based on technical components, and characteristics related to the disease or the treatments being assessed. Finally, the number of times the models were applied within HTA reports, published literature, and/or major conferences was determined.

RESULTS

Thirteen new models were identified and reviewed in depth. Most of these were based on identical key data sources, and applied a similar model structure, either using Markov modeling or microsimulation techniques. The UKPDS equations and panel regressions were frequently used to estimate the occurrence of diabetes-related complications and the probability of developing risk factors in the long term. The qualitative assessment demonstrated that the CARDIFF, Sheffield T2DM and ECHO T2DM models seem technically equipped to appropriately assess the long-term health-economic consequences of chronic treatments for patients with T2DM. It was observed that the CORE model is the most widely described in literature and conferences, and the most often applied model within HTA submissions, followed by the CARDIFF and UKPDS models.

CONCLUSION

This research provides an overview of T2DM models that were developed between 2008 and January 2013. The outcomes of the qualitative assessments, combined with frequent use in local reimbursement decisions, prove the applicability of the CORE, CARDIFF and UKPDS models to address decision problems related to the long-term clinical and economic consequences of new and existing T2DM treatments.

Using health economic models to help guide healthcare decisions

This editorial accompanies a research article being published by Clinical Medical Research and Opinion (CMRO) journal, entitled "Methods applied in cost-effectiveness models for treatment strategies in type 2 diabetes mellitus and their use in Health Technology Assessments: a systematic review of the literature from 2008 to 2013". The importance and the contribution of this research to the scientific community are presented on the grounds of serving the decision-making process of evaluating and approving T2DM treatments for public funding.

How Do Diabetes Models Measure Up? A Review of Diabetes Economic Models and ADA Guidelines

Introduction: Economic models and computer simulation models have been used for assessing short-term cost-effectiveness of interventions and modelling long-term outcomes and costs. Several guidelines and checklists have been published to improve the methods and reporting. This article presents an overview of published diabetes models with a focus on how well the models are described in relation to the considerations described by the American Diabetes Association (ADA) guidelines. Methods: Relevant electronic databases and National Institute for Health and Care Excellence (NICE) guidelines were searched in December 2012. Studies were included in the review if they estimated lifetime outcomes for patients with type 1 or type 2 diabetes. Only unique models, and only the original papers were included in the review. If additional information was reported in subsequent or paired articles, then additional citations were included. References and forward citations of relevant articles, including the previous systematic reviews were searched using a similar method to pearl growing. Four principal areas were included in the ADA guidance reporting for models: transparency, validation, uncertainty, and diabetes specific criteria. Results: A total of 19 models were included. Twelve models investigated type 2 diabetes, two developed type 1 models, two created separate models for type 1 and type 2, and three developed joint type 1 and type 2 models. Most models were developed in the United States, United Kingdom, Europe or Canada. Later models use data or methods from earlier models for development or validation. There are four main types of models: Markov-based cohort, Markov-based microsimulations, discrete-time microsimulations, and continuous time differential equations. All models were long-term diabetes models incorporating a wide range of compilations from various organ systems. In early diabetes modelling, before the ADA guidelines were published, most models did not include descriptions of all the diabetes specific components of the ADA guidelines but this improved significantly by 2004. Conclusion: A clear, descriptive short summary of the model was often lacking. Descriptions of model validation and uncertainty were the most poorly reported of the four main areas, but there exist conferences focussing specifically on the issue of validation. Interdependence between the complications was the least well incorporated or reported of the diabetes-specific criterion.

The addition of E (Empowerment and Economics) to the ABCD algorithm in diabetes care

The ABCD (Age, Body weight, Complications, Duration of disease) algorithm was proposed as a simple and practical tool to manage patients with type 2 diabetes. Diabetes treatment, as for all chronic diseases, relies on patients' ability to cope with daily problems concerning the management of their disease in accordance with medical recommendations. Thus, it is important that patients learn to manage and cope with their disease and gain greater control over actions and decisions affecting their health. Healthcare professionals should aim to encourage and increase patients' perception about their ability to take informed decisions about disease management and to improve patient self-esteem and feeling of self-efficacy to become agents of their own health. E for Empowerment is therefore an additional factor to take into account in the management of patients with type 2 diabetes. E stands also for Economics to be considered in diabetes care. Attention should be paid to public health policies as well as to the physician faced with the dilemma of delivering the best possible care within the problem of limited resources. The financial impact of the new treatment modalities for diabetes represents an issue that needs to be addressed at multiple strata both globally and nationally.

Lexis diagram and illness-death model: simulating populations in chronic disease epidemiology

Chronic diseases impose a tremendous global health problem of the 21st century. Epidemiological and public health models help to gain insight into the distribution and burden of chronic diseases. Moreover, the models may help to plan appropriate interventions against risk factors. To provide accurate results, models often need to take into account three different time-scales: calendar time, age, and duration since the onset of the disease. Incidence and mortality often change with age and calendar time. In many diseases such as, for example, diabetes and dementia, the mortality of the diseased persons additionally depends on the duration of the disease. The aim of this work is to describe an algorithm and a flexible software framework for the simulation of populations moving in an illness-death model that describes the epidemiology of a chronic disease in the face of the different times-scales. We set up a discrete event simulation in continuous time involving competing risks using the freely available statistical software R. Relevant events are birth, the onset (or diagnosis) of the disease and death with or without the disease. The Lexis diagram keeps track of the different time-scales. Input data are birth rates, incidence and mortality rates, which can be given as numerical values on a grid. The algorithm manages the complex interplay between the rates and the different time-scales. As a result, for each subject in the simulated population, the algorithm provides the calendar time of birth, the age of onset of the disease (if the subject contracts the disease) and the age at death. By this means, the impact of interventions may be estimated and compared.

HTA agencies facing model biases: the case of type 2 diabetes

When evaluating new drugs or treatments eligible for reimbursement, health technology assessment (HTA) agencies are repeatedly faced with cost-effectiveness analyses that evidence lack of adequate data and modeling biases. The case of type 2 diabetes illustrates this difficulty. In spite of its high disease burden, type 2 diabetes is poorly documented through existing cost-effectiveness analyses. We support this statement by an exhaustive literature review that enables us to precisely pinpoint the limitations of models used for the assessment of newly marketed (and expensive) drugs. We find that models are mostly restricted to surrogate endpoints and based on non-inferiority clinical trial data; they also show biases in the choice of comparators and inclusion criteria. Such limitations undermine the scope and applicability of HTA practice guidelines based on cost-effectiveness evidence. Nevertheless, cost-effectiveness models remain an opportunity to better inform decision makers and to reduce the uncertainty surrounding their decisions. HTA agencies are best placed to provide incentives for companies to improve the quality of the cost-effectiveness studies submitted for pricing and reimbursement decisions. One such incentive is to include stages of discussion between the company and the health authority during the evaluation process.

Role of NADPH oxidase-4 in saturated fatty acid-induced insulin resistance in SK-Hep-1 cells

We aimed to develop a cell culture model of type 2 diabetes by treating SK-Hep-1 cells with four free fatty acids [i.e., palmitic acid, stearic acid (SA), linoleic acid and oleic acid]. The results showed that Akt phosphorylation was increased in SK-Hep-1 cells treated with insulin in a time- and concentration-dependent manner, which was inhibited by saturated fatty acids, but not by unsaturated fatty acids. Moreover, protein levels of NADPH oxidase (NOX) 4 but not NOX2 were increased following SA treatment and, consequently, increased reactive oxygen species production and decreased cellular glutathione were observed. Apocynin, a NOX4 inhibitor, restored the SA-induced inhibition of Akt phosphorylation, suggesting the role of NOX4 in insulin resistance induced by SA. Neither phosphorylation level nor protein level of the stress signaling kinases, such as c-Jun N-terminal kinase or p38 mitogen activated protein kinase, was changed by SA treatment. Although binding immunoglobulin protein, a marker of endoplasmic reticulum stress, was transiently increased in SKHep-1 cells treated with SA, 4-phenyl butyric acid, a chemical chaperone, had no effect on the insulin-mediated Akt phosphorylation inhibited by SA. The present study provides a useful model for screening anti-insulin resistance drugs and finding new drug targets for treatment of diabetes.

Development of an economic evaluation of diagnostic strategies: the case of monogenic diabetes

OBJECTIVES

To describe the development process for defining an appropriate model structure for the economic evaluation of test-treatment strategies for patients with monogenic diabetes (caused by mutations in the GCK, HNF1A or HNF4A genes).

DESIGN

Experts were consulted to identify and define realistic test-treatment strategies and care pathways. A systematic assessment of published diabetes models was undertaken to inform the model structure.

SETTING

National Health Service in England and Wales.

PARTICIPANTS

Experts in monogenic diabetes whose collective expertise spans the length of the patient care pathway.

PRIMARY AND SECONDARY OUTCOMES

A defined model structure, including the test-treatment strategies, and the selection of a published diabetes model appropriate for the economic evaluation of strategies to identify patients with monogenic diabetes.

RESULTS

Five monogenic diabetes test-treatment strategies were defined: no testing of any kind, referral for genetic testing based on clinical features as noted by clinicians, referral for genetic testing based on the results of a clinical prediction model, referral for genetic testing based on the results of biochemical and immunological tests, referral for genetic testing for all patients with a diagnosis of diabetes under the age of 30 years. The systematic assessment of diabetes models identified the IMS CORE Diabetes Model (IMS CDM) as a good candidate for modelling the long-term outcomes and costs of the test-treatment strategies for monogenic diabetes. The short-term test-treatment events will be modelled using a decision tree which will feed into the IMS CDM.

CONCLUSIONS

Defining a model structure for any economic evaluation requires decisions to be made. Expert consultation and the explicit use of critical appraisal can inform these decisions. Although arbitrary choices have still been made, decision modelling allows investigation into such choices and the impact of assumptions that have to be made due to a lack of data.

A lifetime Markov model for the economic evaluation of chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is currently the fourth leading cause of death worldwide. It has serious health effects and causes substantial costs for society.

OBJECTIVES

The aim of the present paper was to develop a state-of-the-art decision-analytic model of COPD whereby the cost effectiveness of interventions in Germany can be estimated. To demonstrate the applicability of the model, a smoking cessation programme was evaluated against usual care.

METHODS

A seven-stage Markov model (disease stages I to IV according to the GOLD [Global Initiative for Chronic Obstructive Lung Disease] classification, states after lung-volume reduction surgery and lung transplantation, death) was developed to conduct a cost-utility analysis from the societal perspective over a time horizon of 10, 40 and 60 years. Patients entered the cohort model at the age of 45 with mild COPD. Exacerbations were classified into three levels: mild, moderate and severe. Estimation of stage-specific probabilities (for smokers and quitters), utilities and costs was based on German data where possible. Data on effectiveness of the intervention was retrieved from the literature. A discount rate of 3% was applied to costs and effects. Probabilistic sensitivity analysis was used to assess the robustness of the results.

RESULTS

The smoking cessation programme was the dominant strategy compared with usual care, and the intervention resulted in an increase in health effects of 0.54 QALYs and a cost reduction of &U20AC;1115 per patient (year 2007 prices) after 60 years. In the probabilistic analysis, the intervention dominated in about 95% of the simulations. Sensitivity analyses showed that uncertainty primarily originated from data on disease progression and treatment cost in the early stages of disease.

CONCLUSIONS

The model developed allows the long-term cost effectiveness of interventions to be estimated, and has been adapted to Germany. The model suggests that the smoking cessation programme evaluated was more effective than usual care as well as being cost-saving. Most patients had mild or moderate COPD, stages for which parameter uncertainty was found to be high. This raises the need to improve data on the early stages of COPD.

The quality of three decision-analytic diabetes models: a systematic health economic assessment

AIMS

Diabetes mellitus has important economic impacts worldwide. Interventions to prevent diabetes-related complications are often analyzed using model-based cost-effectiveness analyses. As model results are usually influenced by structural assumptions and by the data used, decision-makers should be able to assess the quality of diabetes models. The aim of this study was to assess the quality of selected diabetes models and to determine if modeling recommendations by the American Diabetes Association are considered.

METHODS

The quality of three selected diabetes models (Archimedes Model, CDC Model and Center for Outcomes Research [CORE] Diabetes Model) was assessed using systematic methods.

RESULTS

This systematic approach to assess model quality proved to be feasible and highlighted two areas for improvement: the rationale for model structure and methods to identify parameter values, which should be presented more transparently.

CONCLUSIONS

Overall, the need for a quality assessment of diabetes models is emphasized.