#Ukpds risk engine calculator download trial#
In particular, it placed considerable reliance on data from a Type 1 diabetes trial and on cardiovascular risk estimates derived from the Framingham cohort study, despite there being only 337 people with Type 2 diabetes in the Framingham study and consequent doubts concerning its predictive accuracy for such patients.
While that model represented a landmark in the use of computer simulation to model the progression of the disease, it had several limitations. For example, the first model of the progression of Type 2 diabetes had separate modules for cardiovascular disease, retinopathy, nephropathy and neuropathy, and used a probabilistic Monte-Carlo analysis to simulate event histories over the remaining lifetimes of newly diagnosed patients with Type 2 diabetes.
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Įxisting simulation models have synthesised data from a variety of sources into a series of modules that are used to estimate occurrence of different complications. Currently, there are at least five simulation models being used in these ways. They can also be used to estimate future healthcare costs of patients with Type 2 diabetes, but their main purpose is to estimate the cost-effectiveness of different disease management strategies, especially when evidence of the impact of interventions on surrogate endpoints is limited, or where evidence from clinical trials has to be extrapolated over patients’ lifetimes. These models estimate the future occurrence of diabetes-related complications and quantify outcomes in terms of mean life expectancy or mean quality-adjusted life expectancy. The model allows simulation of a range of long-term outcomes, which should assist in informing future economic evaluations of interventions in Type 2 diabetes.Ĭomputer simulation models are being used increasingly both to model the progression of Type 2 diabetes and to estimate lifetime outcomes associated with different disease management strategies. Its validity in estimating outcomes in other groups of patients, however, remains to be evaluated. The UKPDS Outcomes Model is able to simulate event histories that closely match observed outcomes in the UKPDS and that can be extrapolated over patients’ lifetimes. When the model was used to simulate event history over patients’ lifetimes, those treated with a regimen of conventional glucose control could expect 16.35 undiscounted quality-adjusted life years, and those receiving treatment with intensive glucose control could expect 16.62 quality-adjusted life years, a difference of 0.27 (95% CI: −0.48 to 1.03). The model’s forecasts fell within the 95% confidence interval for the occurrence of observed events during the UKPDS follow-up period.
After examining the internal validity, the UKPDS Outcomes Model was used to simulate the mean difference in expected quality-adjusted life years between the UKPDS regimens of intensive and conventional blood glucose control. MethodsĮquations for forecasting the occurrence of seven diabetes-related complications and death were estimated using data on 3642 patients from the United Kingdom Prospective Diabetes Study (UKPDS). The aim of this study was to develop a simulation model for Type 2 diabetes that can be used to estimate the likely occurrence of major diabetes-related complications over a lifetime, in order to calculate health economic outcomes such as quality-adjusted life expectancy.
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