The Determination of Diabetes Utilities, Costs, and Effects Model : A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation
Copyright © 2024. Published by Elsevier Inc..
OBJECTIVES: To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes.
METHODS: The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error.
RESULTS: The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios.
CONCLUSIONS: The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:27 |
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| Enthalten in: |
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research - 27(2024), 4 vom: 23. Apr., Seite 500-507 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Szafranski, Kirk [VerfasserIn] |
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| Links: |
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| Themen: |
Blood Glucose |
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| Anmerkungen: |
Date Completed 05.04.2024 Date Revised 25.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jval.2024.01.010 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM367967669 |
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| 245 | 1 | 4 | |a The Determination of Diabetes Utilities, Costs, and Effects Model |b A Cost-Utility Tool Using Patient-Level Microsimulation to Evaluate Sensor-Based Glucose Monitoring Systems in Type 1 and Type 2 Diabetes: Comparative Validation |
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| 500 | |a Date Revised 25.04.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024. Published by Elsevier Inc. | ||
| 520 | |a OBJECTIVES: To assess the accuracy and validity of the Determination of Diabetes Utilities, Costs, and Effects (DEDUCE) model, a Microsoft-Excel-based tool for evaluating diabetes interventions for type 1 and type 2 diabetes | ||
| 520 | |a METHODS: The DEDUCE model is a patient-level microsimulation, with complications predicted based on the Sheffield and Risk Equations for Complications Of type 2 diabetes models for type 1 and type 2 diabetes, respectively. For this tool to be useful, it must be validated to ensure that its complication predictions are accurate. Internal, external, and cross-validation was assessed by populating the DEDUCE model with the baseline characteristics and treatment effects reported in clinical trials used in the Fourth, Fifth, and Ninth Mount Hood Diabetes Challenges. Results from the DEDUCE model were evaluated against clinical results and previously validated models via mean absolute percentage error or percentage error | ||
| 520 | |a RESULTS: The DEDUCE model performed favorably, predicting key outcomes, including cardiovascular disease in type 1 diabetes and all-cause mortality in type 2 diabetes. The model performed well against other models. In the Mount Hood 9 Challenge comparison, error was below the mean reported from comparator models for several outcomes, particularly for hazard ratios | ||
| 520 | |a CONCLUSIONS: The DEDUCE model predicts diabetes-related complications from trials and studies well when compared with previously validated models. The model may serve as a useful tool for evaluating the cost-effectiveness of diabetes technologies | ||
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| 700 | 1 | |a Jendle, Johan |e verfasserin |4 aut | |
| 700 | 1 | |a Shaw, Jonathan E |e verfasserin |4 aut | |
| 700 | 1 | |a Castro, JeanPierre Coaquira |e verfasserin |4 aut | |
| 700 | 1 | |a Poon, Yeesha |e verfasserin |4 aut | |
| 700 | 1 | |a Levrat-Guillen, Fleur |e verfasserin |4 aut | |
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