Prediction of mortality and macrovascular complications in type 2 diabetes: validation of the UKPDS Outcomes Model in the Casale Monferrato Survey, Italy

Abstract

Aims/hypothesis The United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model can be used to estimate the lifetime occurrence of major diabetes-related complications in order to calculate health economic outcomes. The aim of the study was to assess the performance of the model by comparing the predicted and observed mortality and the incidence of macrovascular complications in an Italian population-based cohort with type 2 diabetes. Methods We used data from the Casale Monferrato Survey, a cohort enrolled in 1988 and surveyed in 1991 (n=1,967) to assess the prevalence of cardiovascular risk factors. In 2000, a new survey included all the members of the original cohort who were still alive (n=860), and in addition all individuals identified with a new diagnosis of type 2 diabetes since 1993 (n=2,389). We compared the mortality predicted by the model for the 1991 survey over the subsequent 17-year period with the observed risk. The following outcomes were analysed in the 2000 survey: myocardial infarction (MI), other ischaemic heart disease, stroke, congestive heart failure (CHF) and amputation. Results For all-cause mortality, the predictions from the model at 5 and 10 years (23% and 47%, respectively) were identical to the observed risks. At 15 years, the risk of death was slightly overestimated (an estimate of 67% vs 64% observed, 95% CI 61%, 66%). The performance of the model was best for patients with a recent history of disease (duration <6 years). Among the complications, the predicted cumulative incidences of MI and CHF were very close to those observed. Conclusions/interpretation External validation is essential to assess the accuracy of simulation models. The UKPDS Outcomes Model satisfactorily predicted a set of actual incidences of mortality and complications in an Italian diabetes cohort up to a duration of approximately 12 years. The longer term performance of such models should be carefully evaluated.

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