Cost effectiveness of rimonabant use in patients at increased cardiometabolic risk: estimates from a Markov model

Jaime, J.; Stillman, Ipek Özer; Danel, Aurelie; Getsios, Denis; McEwan, P.

doi:10.3111/13696990701438629

Cited by 20 publications

(2 citation statements)

References 38 publications

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“…In order to select high-quality obesity models, the related minimal structural requirements for health economic obesity models were applied, consisting of the following criteria: (1) simulation time horizon: long-term (lifetime or comparable) [n = 55 of 87]; (2) model type: state transition model (STM) or discrete event simulation (DES) [STM n = 74 or DES n = 2 of 87]; and (3) events simulated: at least coronary heart disease, type 2 diabetes and stroke (n = 39 of 87). To assure that the models were simulating a comparable setting and patient population, the United Kingdom (UK) country setting (n = 15 of 87) and the adult population were used (n = 70 of 87) as final model selection criteria, which resulted in four health economic obesity models [14][15][16][17]. Additional details of this step-wise model selection process are presented in the appendix (Online Resource 1, Table 6; see the electronic supplementary material).…”

Section: Model Selection and Model Overviewmentioning

confidence: 99%

“…The third obesity model (case study 3), funded by an industry research grant, is based on intervention-related clinical trials simulated over a lifetime horizon, using a health economic Markov modeling approach consisting of five main health states. All relevant information on the modeling approach and the input values was provided in the original paper, published in the Journal of Medical Economics [16]. Of the four case studies, this was the only one that presented information on internal and external validation of the model.…”

Section: Introductionmentioning

confidence: 99%

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

Schwander

Nuijten²,

Evers

et al. 2021

PharmacoEconomics

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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.

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Section: Model Selection and Model Overviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Schwander

Nuijten²,

Evers

et al. 2021

PharmacoEconomics

View full text Add to dashboard Cite

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Modellbasierte gesundheitsökonomische Evaluation der Diabetesprävention

et al. 2020

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Modelling the Economics of Type 2 Diabetes Mellitus Prevention: A Literature Review of Methods

Watson

Preston

Squires

et al. 2014

Appl Health Econ Health Policy

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Our objective was to review modelling methods for type 2 diabetes mellitus prevention cost-effectiveness studies. The review was conducted to inform the design of a policy analysis model capable of assisting resource allocation decisions across a spectrum of prevention strategies. We identified recent systematic reviews of economic evaluations in diabetes prevention and management of obesity. We extracted studies from two existing systematic reviews of economic evaluations for the prevention of diabetes. We extracted studies evaluating interventions in a non-diabetic population with type 2 diabetes as a modelled outcome, from two systematic reviews of obesity intervention economic evaluations. Databases were searched for studies published between 2008 and 2013. For each study, we reviewed details of the model type, structure, and methods for predicting diabetes and cardiovascular disease. Our review identified 46 articles and found variation in modelling approaches for cost-effectiveness evaluations for the prevention of type 2 diabetes. Investigation of the variables used to estimate the risk of type 2 diabetes suggested that impaired glucose regulation, and body mass index were used as the primary risk factors for type 2 diabetes. A minority of cost-effectiveness models for diabetes prevention accounted for the multivariate impacts of interventions on risk factors for type 2 diabetes. Twenty-eight cost-effectiveness models included cardiovascular events in addition to type 2 diabetes. Few cost-effectiveness models have flexibility to evaluate different intervention types. We conclude that to compare a range of prevention interventions it is necessary to incorporate multiple risk factors for diabetes, diabetes-related complications and obesity-related co-morbidity outcomes.

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Cost effectiveness of rimonabant use in patients at increased cardiometabolic risk: estimates from a Markov model

Cited by 20 publications

References 38 publications

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

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

Modellbasierte gesundheitsökonomische Evaluation der Diabetesprävention

Modelling the Economics of Type 2 Diabetes Mellitus Prevention: A Literature Review of Methods

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