Literature DB >> 11080563

The Mt. Hood challenge: cross-testing two diabetes simulation models.

J B Brown1, A J Palmer, P Bisgaard, W Chan, K Pedula, A Russell.   

Abstract

Starting from identical patients with type 2 diabetes, we compared the 20-year predictions of two computer simulation models, a 1998 version of the IMIB model and version 2.17 of the Global Diabetes Model (GDM). Primary measures of outcome were 20-year cumulative rates of: survival, first (incident) acute myocardial infarction (AMI), first stroke, proliferative diabetic retinopathy (PDR), macro-albuminuria (gross proteinuria, or GPR), and amputation. Standardized test patients were newly diagnosed males aged 45 or 75, with high and low levels of glycated hemoglobin (HbA(1c)), systolic blood pressure (SBP), and serum lipids. Both models generated realistic results and appropriate responses to changes in risk factors. Compared with the GDM, the IMIB model predicted much higher rates of mortality and AMI, and fewer strokes. These differences can be explained by differences in model architecture (Markov vs. microsimulation), different evidence bases for cardiovascular prediction (Framingham Heart Study cohort vs. Kaiser Permanente patients), and isolated versus interdependent prediction of cardiovascular events. Compared with IMIB, GDM predicted much higher lifetime costs, because of lower mortality and the use of a different costing method. It is feasible to cross-validate and explicate dissimilar diabetes simulation models using standardized patients. The wide differences in the model results that we observed demonstrate the need for cross-validation. We propose to hold a second 'Mt Hood Challenge' in 2001 and invite all diabetes modelers to attend.

Entities:  

Mesh:

Year:  2000        PMID: 11080563     DOI: 10.1016/s0168-8227(00)00217-5

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  17 in total

1.  A guideline for the use of pharmacoeconomic models of diabetes treatment in the US managed-care environment.

Authors:  David L Veenstra; Scott D Ramsey; Sean D Sullivan
Journal:  Pharmacoeconomics       Date:  2002       Impact factor: 4.981

2.  Crossing the evidence chasm: building evidence bridges from process changes to clinical outcomes.

Authors:  David C Kendrick; Davis Bu; Eric Pan; Blackford Middleton
Journal:  J Am Med Inform Assoc       Date:  2007-02-28       Impact factor: 4.497

3.  Screening for and treatment of osteoporosis: construction and validation of a state-transition microsimulation cost-effectiveness model.

Authors:  L Si; T M Winzenberg; Q Jiang; A J Palmer
Journal:  Osteoporos Int       Date:  2015-01-08       Impact factor: 4.507

Review 4.  Dynamic microsimulation models for health outcomes: a review.

Authors:  Carolyn M Rutter; Alan M Zaslavsky; Eric J Feuer
Journal:  Med Decis Making       Date:  2010-05-18       Impact factor: 2.583

5.  Economic evaluation of pioglitazone hydrochloride in the management of type 2 diabetes mellitus in Canada.

Authors:  Douglas Coyle; Andrew J Palmer; Robert Tam
Journal:  Pharmacoeconomics       Date:  2002       Impact factor: 4.981

Review 6.  The role of models within economic analysis: focus on type 2 diabetes mellitus.

Authors:  Douglas Coyle; Karen M Lee; Bernie J O'Brien
Journal:  Pharmacoeconomics       Date:  2002       Impact factor: 4.981

7.  Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

Authors:  Michael Willis; Pierre Johansen; Andreas Nilsson; Christian Asseburg
Journal:  Pharmacoeconomics       Date:  2017-03       Impact factor: 4.981

8.  Macrovascular Risk Equations Based on the CANVAS Program.

Authors:  Michael Willis; Christian Asseburg; April Slee; Andreas Nilsson; Cheryl Neslusan
Journal:  Pharmacoeconomics       Date:  2021-02-13       Impact factor: 4.981

Review 9.  Cost effectiveness of combination therapy with pioglitazone for type 2 diabetes mellitus from a german statutory healthcare perspective.

Authors:  Kurt Neeser; Georg Lübben; Uwe Siebert; Wendelin Schramm
Journal:  Pharmacoeconomics       Date:  2004       Impact factor: 4.981

10.  Validation of the UKPDS 82 risk equations within the Cardiff Diabetes Model.

Authors:  Philip McEwan; Thomas Ward; Hayley Bennett; Klas Bergenheim
Journal:  Cost Eff Resour Alloc       Date:  2015-08-04
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.