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Development and Validation of PREDICT-DM: A New Microsimulation Model to Project and Evaluate Complications and Treatments of Type 2 Diabetes Mellitus.
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- Author(s): Kazemian P;Kazemian P;Kazemian P;Kazemian P; Wexler DJ; Wexler DJ; Wexler DJ; Fields NF; Fields NF; Parker RA; Parker RA; Parker RA; Parker RA; Zheng A; Zheng A; Walensky RP; Walensky RP; Walensky RP; Walensky RP; Walensky RP
- Source:
Diabetes technology & therapeutics [Diabetes Technol Ther] 2019 Jun; Vol. 21 (6), pp. 344-355.- Publication Type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Validation Study- Language:
English - Source:
- Additional Information
- Source: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 100889084 Publication Model: Print Cited Medium: Internet ISSN: 1557-8593 (Electronic) Linking ISSN: 15209156 NLM ISO Abbreviation: Diabetes Technol Ther Subsets: MEDLINE
- Publication Information: Original Publication: Larchmont, NY : Mary Ann Liebert, Inc., c1999-
- Subject Terms: Diabetes Mellitus, Type 2* ; Models, Statistical*; Computer Simulation/*standards ; Forecasting/*methods ; Outcome Assessment, Health Care/*standards; Cohort Studies ; Humans ; Outcome Assessment, Health Care/methods ; Randomized Controlled Trials as Topic ; Reproducibility of Results ; Risk Factors ; United States
- Abstract: Background: Type 2 diabetes mellitus (T2DM) affects ∼30 million people in the United States and ∼400 million people worldwide, numbers likely to increase due to the rising prevalence of obesity. We sought to design, develop, and validate PREDICT-DM (PRojection and Evaluation of Disease Interventions, Complications, and Treatments-Diabetes Mellitus), a state-transition microsimulation model of T2DM, incorporating recent data. Methods: PREDICT-DM is populated with natural history, risk factor, and outcome data from large-scale cohort studies and randomized clinical trials. The model projects diabetes-relevant outcomes, including cardiovascular and renal disease outcomes, and 5/10-year survival. We assessed the model validity against 62 endpoints from ACCORD (Action to Control Cardiovascular Risk in Diabetes), VADT (Veterans Affairs Diabetes Trial), and Look AHEAD trials via several comparative statistical methods, including mean absolute percentage error (MAPE), Bland-Altman graphs, and Kaplan-Meier curves. Results: For the comparison between simulated and observed outcomes of the intervention/control arms of the trial, the MAPE was 19%/25% (ACCORD), 29%/20% (VADT), and 42%/10% (Look AHEAD). The Bland-Altman's 95% limit of agreement was 0.02 (ACCORD), 0.03 (VADT), and 0.01 (Look AHEAD), and the mean difference (95% confidence interval) for the comparison between PREDICT-DM and trial endpoints was 0.0025 (-0.0018 to 0.0070) for ACCORD, -0.0067 (-0.0137 to 0.0002) for VADT, and -0.0033 (-0.0067 to 0.00002) for Look AHEAD, indicating an adequate model fit to the data. The model-driven Kaplan-Meier curves were similarly close to those previously published. Conclusions: PREDICT-DM can reasonably predict clinical outcomes from ACCORD and other clinical trials of U.S. patients with T2DM. This model may be leveraged to inform clinical strategy questions related to the management and care of T2DM in the United States.
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- Contributed Indexing: Keywords: Diabetes; Model; PREDICT-DM; Prediction; Simulation; Validation
- Publication Date: Date Created: 20190604 Date Completed: 20200410 Latest Revision: 20200601
- Publication Date: 20240628
- Accession Number: PMC6551972
- Accession Number: 10.1089/dia.2018.0393
- Accession Number: 31157568
- Source:
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