Prediction models for the risk of cardiovascular disease in patients with type 2 diabetes: A systematic review

Context: A recent overview of all CVD models applicable to diabetes patients is not available. Objective: To review the primary prevention studies that focused on the development, validation and impact assessment of a cardiovascular risk model, scores or rules that can be applied to patients with type 2 diabetes. Design: Systematic review. Data sources: Medline was searched from 1966 to 1 April 2011. Study selection: A study was eligible when it described the development, validation or impact assessment of a model that was constructed to predict the occurrence of cardiovascular disease in people with type 2 diabetes, or when the model was designed for use in the general population but included diabetes as a predictor. Data extraction: A standardized form was sued to extract all data of the CVD models. Results: 45 prediction models were identified, of which 12 were specifically developed for patients with type 2 diabetes. Only 31% of the risk scores has been externally validated in a diabetes population, with an area under the curve ranging from 0.61 to 0.86 and 0.59 to 0.80 for models developed in a diabetes population and in the general population, respectively. Only one risk score has been studied for its effect on patient management and outcomes. 10% of the risk scores are advocated in national diabetes guidelines. Conclusion: Many cardiovascular risk scores are available that can be applied to patients with type 2 diabetes. A minority of these risk scores has been validated and tested for its predictive accuracy, with only a few showing a discriminative value of ≥0.80. The impact of applying these risk scores in clinical practice is almost completely unknown, but their use is recommended in various national guidelines.