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Li X, Li F, Wang J, van Giessen A, Feenstra TL. Prediction of complications in health economic models of type 2 diabetes: a review of methods used. Acta Diabetol 2023; 60:861-879. [PMID: 36867279 PMCID: PMC10198865 DOI: 10.1007/s00592-023-02045-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 01/31/2023] [Indexed: 03/04/2023]
Abstract
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.
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Affiliation(s)
- Xinyu Li
- Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan1, 9713AV, Groningen, The Netherlands.
| | - Fang Li
- Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan1, 9713AV, Groningen, The Netherlands
| | - Junfeng Wang
- Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Anoukh van Giessen
- Expertise Center for Methodology and Information Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Talitha L Feenstra
- Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan1, 9713AV, Groningen, The Netherlands
- Center for Nutrition, Prevention and Health Services Research, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
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Li J, Bao Y, Chen X, Tian L. Decision models in type 2 diabetes mellitus: A systematic review. Acta Diabetol 2021; 58:1451-1469. [PMID: 34081206 PMCID: PMC8505393 DOI: 10.1007/s00592-021-01742-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/07/2021] [Indexed: 12/21/2022]
Abstract
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.
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Affiliation(s)
- Jiayu Li
- Department of Endocrinology, Gansu Provincial Hospital, Lanzhou, 730000, Gansu Province, China
- Clinical Research Center for Metabolic Diseases, No. 204 Donggang west road, Lanzhou, 730000, Gansu Province, China
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, 750004, Ningxia Province, China
| | - Yun Bao
- Clinical Research Center for Metabolic Diseases, No. 204 Donggang west road, Lanzhou, 730000, Gansu Province, China
| | - Xuedi Chen
- Department of Endocrinology, Gansu Provincial Hospital, Lanzhou, 730000, Gansu Province, China
- Clinical Research Center for Metabolic Diseases, No. 204 Donggang west road, Lanzhou, 730000, Gansu Province, China
| | - Limin Tian
- Department of Endocrinology, Gansu Provincial Hospital, Lanzhou, 730000, Gansu Province, China.
- Clinical Research Center for Metabolic Diseases, No. 204 Donggang west road, Lanzhou, 730000, Gansu Province, China.
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Wu B, Ma J, Zhang S, Zhou L, Wu H. Development and validation of a Health Policy Model of Type 2 diabetes in Chinese setting. J Comp Eff Res 2018; 7:749-763. [PMID: 30132342 DOI: 10.2217/cer-2018-0001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
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.
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Affiliation(s)
- Bin Wu
- Medical Decision & Economic Group, Department of Pharmacy, Ren Ji Hospital, South Campus, School of Medicine, Shanghai Jiaotong University, PR China
| | - Jing Ma
- Department of Endocrinology, Ren Ji Hospital, South Campus, School of Medicine, Shanghai Jiao Tong University, Shanghai, PR China
| | - Suhua Zhang
- Department of Nephrology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, PR China
| | - Lei Zhou
- Department of Cardiology, Ren Ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, PR China
| | - Haixiang Wu
- Department of Ophthalmology, Eye & ENT Hospital of Fudan University, Shanghai, PR China
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Ogurtsova K, Heise TL, Linnenkamp U, Dintsios CM, Lhachimi SK, Icks A. External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement-a protocol for a systematic review. Syst Rev 2017; 6:267. [PMID: 29284543 PMCID: PMC5746956 DOI: 10.1186/s13643-017-0664-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Accepted: 12/12/2017] [Indexed: 12/30/2022] Open
Abstract
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 .
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Affiliation(s)
- Katherine Ogurtsova
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich Heine University, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany. .,German Center for Diabetes Research (DZD), Neuherberg, Germany.
| | - Thomas L Heise
- Institute for Public Health and Nursing Research-IPP, Health Sciences Bremen, University of Bremen, Bremen, Germany.,Research Group for Evidence-Based Public Health, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany
| | - Ute Linnenkamp
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich Heine University, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
| | | | - Stefan K Lhachimi
- Institute for Public Health and Nursing Research-IPP, Health Sciences Bremen, University of Bremen, Bremen, Germany.,Research Group for Evidence-Based Public Health, Leibniz Institute for Prevention Research and Epidemiology-BIPS, Bremen, Germany
| | - Andrea Icks
- Institute for Health Services Research and Health Economics, German Diabetes Center (DDZ), Leibniz Center for Diabetes Research at Heinrich Heine University, Auf'm Hennekamp 65, 40225, Düsseldorf, Germany.,Institute for Health Services Research and Health Economics, Centre for Health and Society, Faculty of Medicine, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Neuherberg, Germany
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Henriksson M, Jindal R, Sternhufvud C, Bergenheim K, Sörstadius E, Willis M. A Systematic Review of Cost-Effectiveness Models in Type 1 Diabetes Mellitus. PHARMACOECONOMICS 2016; 34:569-585. [PMID: 26792792 DOI: 10.1007/s40273-015-0374-8] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
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.
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Affiliation(s)
- Martin Henriksson
- PAREXEL International, Stockholm, Sweden
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | | | - Catarina Sternhufvud
- Global Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden.
| | - Klas Bergenheim
- Global Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden
| | - Elisabeth Sörstadius
- Global Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden
| | - Michael Willis
- The Swedish Institute for Health Economics, IHE, Lund, Sweden
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Kirsch F. A systematic review of Markov models evaluating multicomponent disease management programs in diabetes. Expert Rev Pharmacoecon Outcomes Res 2015; 15:961-84. [DOI: 10.1586/14737167.2015.1108191] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Kirsch F. A systematic review of quality and cost–effectiveness derived from Markov models evaluating smoking cessation interventions in patients with chronic obstructive pulmonary disease. Expert Rev Pharmacoecon Outcomes Res 2015; 15:301-16. [DOI: 10.1586/14737167.2015.1001976] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Hatz MHM, Leidl R, Yates NA, Stollenwerk B. A systematic review of the quality of economic models comparing thrombosis inhibitors in patients with acute coronary syndrome undergoing percutaneous coronary intervention. PHARMACOECONOMICS 2014; 32:377-393. [PMID: 24504849 DOI: 10.1007/s40273-013-0128-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
BACKGROUND Thrombosis inhibitors can be used to treat acute coronary syndromes (ACS). However, there are various alternative treatment strategies, of which some have been compared using health economic decision models. OBJECTIVE To assess the quality of health economic decision models comparing thrombosis inhibitors in patients with ACS undergoing percutaneous coronary intervention, and to identify areas for quality improvement. DATA SOURCES The literature databases MEDLINE, EMBASE, EconLit, National Health Service Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA). STUDY APPRAISAL AND SYNTHESIS METHODS A review of the quality of health economic decision models was conducted by two independent reviewers, using the Philips checklist. RESULTS Twenty-one relevant studies were identified. Differences were apparent regarding the model type (six decision trees, four Markov models, eight combinations, three undefined models), the model structure (types of events, Markov states) and the incorporation of data (efficacy, cost and utility data). Critical issues were the absence of particular events (e.g. thrombocytopenia, stroke) and questionable usage of utility values within some studies. LIMITATIONS As we restricted our search to health economic decision models comparing thrombosis inhibitors, interesting aspects related to the quality of studies of adjacent medical areas that compared stents or procedures could have been missed. CONCLUSIONS This review identified areas where recommendations are indicated regarding the quality of future ACS decision models. For example, all critical events and relevant treatment options should be included. Models also need to allow for changing event probabilities to correctly reflect ACS and to incorporate appropriate, age-specific utility values and decrements when conducting cost-utility analyses.
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Affiliation(s)
- Maximilian H M Hatz
- Hamburg Center for Health Economics, University of Hamburg, 20354, Hamburg, Germany,
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Shenoy AU, Aljutaili M, Stollenwerk B. Limited economic evidence of carotid artery stenosis diagnosis and treatment: a systematic review. Eur J Vasc Endovasc Surg 2012; 44:505-13. [PMID: 22995752 DOI: 10.1016/j.ejvs.2012.08.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2012] [Accepted: 08/26/2012] [Indexed: 10/27/2022]
Abstract
UNLABELLED The objective of this article is to assess the availability and validity of economic evaluations of carotid artery stenosis (CS) diagnosis and treatment. DESIGN Systematic review of economic evaluations of the diagnosis and treatment of CS. METHODS Systematic review of full economic evaluations published in Medline and Google Scholar up until 28 February 2012. Based on economic checklists (Evers and Philips), the identified studies were classified as high, medium, or low quality. RESULTS Twenty-three evaluations were identified. The study quality ranged from 26% to 84% of all achievable points (Evers). Seven studies were of high, eight of medium and eight of low quality. No comparison was made between carotid angioplasty and stenting (CAS) and best medical treatment (BMT). For subjects with severe stenosis, comparisons of carotid endarterectomy (CEA) and BMT were also missing. Three of five studies dealing with pre-operative imaging found that duplex Doppler ultrasound (US) was cost-effective compared with carotid angiogram (AG). CONCLUSIONS There is a huge lack of high-quality studies and of studies that confirm published results. Also, for a given study quality, the most cost-effective treatment strategy is still unknown in some cases ('CAS' vs. 'BMT', 'US combined with magnetic resonance angiography supplemented with AG' vs. 'US combined with computer tomography angiography').
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Affiliation(s)
- A U Shenoy
- Helmholtz Zentrum München, Institute of Health Economics and Health Care Management, Neuherberg, Germany
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