Cardiovascular disease risk prediction in type 1 diabetes: Accounting for the differences☆
Introduction
Cardiovascular disease is the leading cause of death for people with diabetes [1]. Because many of the risk factors for heart disease are modifiable, predicting an individual's risk for a coronary heart disease event at some point in the future provides an opportunity for targeting interventions. Prediction models already exist for this purpose. The most commonly used for the general population is from the Framingham Heart Study (in which only 4% of the study population had diabetes) [2] and the UKPDS Risk Engine specifically for type 2 diabetes [3]. Both of these models significantly underestimate the risk of coronary heart disease (CHD) in patients with type 1 diabetes (T1D) [4].
The limitation of these models is particularly concerning since people with T1D suffer a disproportionate burden of CHD exhibiting at least a 10-fold increased risk compared to those similarly aged in the general population [5], [6] Although prediction by the Framingham and UKPDS risk functions in this population is significantly inaccurate [4], the specific factors related to this inaccuracy are not well understood. Therefore our objective was to determine if specific risk factors account for this significant underestimation of events using data from an epidemiologically representative cohort of T1D subjects.
Section snippets
Methods
These analyses used data from the Epidemiology of Diabetes Complications Study, which includes subjects with childhood (<17 years old) onset T1D diagnosed between 1950 and 1980. All subjects were seen within 1 year of diagnosis at Children's Hospital of Pittsburgh. Although this population is clinic based, it has been shown to be epidemiologically representative of type 1 diabetes cases in Allegheny County, Pennsylvania [7]. The 658 subjects participating in baseline exams were followed
Definitions
The CHD outcome of interest was defined by a fatal CAD or non-fatal myocardial infarction (MI) confirmed by medical records, or Q-waves according to Minnesota codes 1.1 or 1.2 [8]. This endpoint is the same used in the Framingham model [2].
At the baseline exam, information was collected by questionnaire concerning demographic characteristics, medical history, and health care behaviors. Both a standardized medical history and clinical examination were performed by a trained internist to document
Results
Of the 552 eligible subjects, 49% were male, 98% were Caucasian, mean age at entry into the study was 27 years old, and duration of diabetes prior to study entry was 18 years. There were 42 (7%) subjects who had their first hard CHD event by the end of their 10th year of follow-up. Those that had an event were older (32.4 years versus 25.8 years; p < 0.0001) and had longer diabetes duration (24.4 years versus 17.3 years; p < 0.0001). Race, gender and age at onset of diabetes were not significantly
Discussion
This study sought to determine factors associated with the underestimation of CHD events when using the Framingham model in T1D subjects. These results are important as the Framingham risk score is commonly used in clinical practices for all T1D. Using this model to provide risk information to patients with type 1 diabetes may not only underestimate risk, but may mis-specify the importance of various risk factors and the potential effects of risk factor modification. In the analysis of males in
Conflict of interest
There are no conflicts of interest.
Acknowledgements
This study was funded by National Institutes of Health DK34818, DK070725, and the American Diabetes Association Junior Faculty Award 1-05-JF-59. The authors have no conflicts of interest and had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
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This was presented as a poster at the Society for Medical Decision Making Meeting, San Francisco, CA, in October 2005.