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Diabetologia. 2004 Oct;47(10):1747-59. Epub 2004 Oct 27.

A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68).

Author information

1
Health Economics Research Centre, Department of Public Health, University of Oxford, Headington, Oxford, UK. Philip.clarke@dphpc.ox.ac.uk

Abstract

AIMS/HYPOTHESIS:

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.

METHODS:

Equations 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). 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.

RESULTS:

The model's forecasts fell within the 95% confidence interval for the occurrence of observed events during the UKPDS follow-up period. 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).

CONCLUSIONS/INTERPRETATIONS:

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. Its validity in estimating outcomes in other groups of patients, however, remains to be evaluated. 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.

PMID:
15517152
DOI:
10.1007/s00125-004-1527-z
[Indexed for MEDLINE]

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