Abstract
ObjectivePredicting the risk of future events is an essential part of health economic simulation models. In pursuit of this goal, the current study aims to predict the risk of developing first and second acute myocardial infarction, heart failure, non-acute ischaemic heart disease, and stroke after diagnosis in patients with type 2 diabetes, using data from the Swedish National Diabetes Register.Material and MethodsRegister data on 29,034 patients with type 2 diabetes were analysed over five years of follow up (baseline 2003). To develop and validate the risk equations, the sample was randomly divided into training (75%) and test (25%) subsamples. The Weibull proportional hazard model was used to estimate the coefficients of the risk equations, and these were validated in both the training and the test samples.ResultsIn total, 4,547 first and 2,418 second events were observed during the five years of follow up. Experiencing a first event substantially elevated the risk of subsequent events. There were heterogeneities in the effects of covariates within as well as between events; for example, while for females the hazard ratio of having a first acute myocardial infarction was 0.79 (0.70–0.90), the hazard ratio of a second was 1.21 (0.98–1.48). The hazards of second events decreased as the time since first events elapsed. The equations showed adequate calibration and discrimination (C statistics range: 0.70–0.84 in test samples).ConclusionThe accuracy of health economic simulation models of type 2 diabetes can be improved by ensuring that they account for the heterogeneous effects of covariates on the risk of first and second cardiovascular events. Thus it is important to extend such models by including risk equations for second cardiovascular events.
Highlights
Health economic simulation models (HESMs) are used to assist resource allocation decisions in different medical fields including diabetes [1,2,3,4,5]
The accuracy of health economic simulation models of type 2 diabetes can be improved by ensuring that they account for the heterogeneous effects of covariates on the risk of first and second cardiovascular events
One essential task of an HESM is to predict the risk of developing future events based on the demographic and clinical characteristics of patients, which in turn determine the expected costs and quality of life associated with different health states
Summary
Health economic simulation models (HESMs) are used to assist resource allocation decisions in different medical fields including diabetes [1,2,3,4,5]. These models are built on a combination of mathematical equations and computer software, and reflect key aspects of disease progression [6]. They are used to quantify the lifetime benefits and costs of alternative technologies and interventions [7]. A recent systematic review [8] showed that HESMs of diabetes usually use results from the Framingham cohort study [9], the UK Prospective Diabetes Study (UKPDS) [10] and the Diabetes Control and Complications Trial (DCCT) [11]
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