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

Diabetes Res Clin Pract. 2000 Nov;50 Suppl 3:S57-64. doi: 10.1016/s0168-8227(00)00217-5.

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.

Publication types

  • Comparative Study

MeSH terms

  • Albuminuria / epidemiology
  • Amputation / statistics & numerical data
  • Blood Pressure
  • Computer Simulation*
  • Diabetes Mellitus, Type 2 / mortality
  • Diabetes Mellitus, Type 2 / physiopathology*
  • Diabetes Mellitus, Type 2 / therapy*
  • Diabetic Retinopathy / epidemiology
  • Humans
  • Markov Chains
  • Models, Statistical
  • Monte Carlo Method
  • Myocardial Infarction / epidemiology
  • Prognosis
  • Proteinuria / epidemiology
  • Survival Rate
  • Treatment Outcome