Computer Modeling of Diabetes and Its Complications

Abstract

Computer simulation models are mathematical equations combined in a structured framework to represent some real or hypothetical system. One of their uses is to allow the projection of short-term data from clinical trials to evaluate clinical outcomes and costs over a long-term period. This technology is becoming increasingly important to assist decision making in modern medicine in situations where there is a paucity of long-term clinical trial data, as recently acknowledged in the American Diabetes Association Consensus Panel Guidelines for Computer Modeling of Diabetes and its Complications. The Mount Hood Challenge Meetings provide a forum for computer modelers of diabetes to discuss and compare models and identify key areas of future development to advance the field. The Fourth Mount Hood Challenge in 2004 was the first meeting of its kind to ask modelers to perform simulations of outcomes for patients in published clinical trials, allowing comparison against “real life” data. Eight modeling groups participated in the challenge. Each group was given three of the following challenges: to simulate a trial of type 2 diabetes (CARDS [Collaborative Atorvastatin Diabetes Study]); to simulate a trial of type 1 diabetes (DCCT [Diabetes Control and Complications Trial]); and to calculate outcomes for a hypothetical, precisely specified patient (cross-model validation). The results of the models varied from each other and for methodological reasons, in some cases, from the published trial data in important ways. This approach of performing systematic comparisons and validation exercises has enabled the identification of key differences among the models, as well as their possible causes and directions for improvement in the future.

Assessing the economic value of maintained improvements in Type 1 diabetes management, in terms of HbA1c, weight and hypoglycaemic event incidence

“…Subsequently, this model represents a plausible approach to assess the value of improving glycaemic control, hypoglycaemia incidence and body weight in populations not reflective of the DCCT/EDIC study cohort, such as those over 60 years of age, or with a long duration of Type 1 diabetes. Furthermore, the impact of weight, hypoglycaemia and HbA 1c on predicted QALYs in this study are consistent with published analyses using the Cardiff Type 2 Diabetes Model 25; and the structure and performance of both Cardiff models have undergone rigorous scrutiny at several Mount Hood Diabetes Challenge Meetings 33, 34, 35.…”

Predicting Changes in Cardiovascular Risk Factors in Type 2 Diabetes in the Post-UKPDS Era: Longitudinal Analysis of the Swedish National Diabetes Register

“…One or more of these risk factors have also been shown to play a role in predicting the occurrence of other types of complications including amputation, renal impairment, and eye-related complications [12, 13]. These risk factors are commonly used in clinical risk equations [14, 15] as well as health economic simulation models [16]. …”

Impact and Feasibility of Personalized Decision Support for Older Patients with Diabetes: A Pilot Randomized Trial

“…8 We used this model because of its widespread use, public availability, and prior external validation. 29 Future versions of this intervention will need to incorporate updates to the UKPDS model and more recent clinical trial findings. 30,31 Our pilot study was underpowered and was primarily designed to address feasibility issues and to gather data in preparation for a larger trial.…”