Risk Prediction of Cardiovascular Disease in Type 2 Diabetes

OBJECTIVE - Risk prediction models obtained in samples from the general population do mot perform well in type 2 diabetic patients. Recently, 5-year risk estimates were proposed as being more accurate than 10-year risk estimates. This study presents a diabetes-specific equation for estimation of the absolute 5-year risk of first incident fatal/nonfatal cardiovascular disease (CVD) in type 2 diabetic patients with the use of A1C and clinical characteristics. RESEARCH DESIGN AND METHODS - The study was based on 11,646 female and male patients, aged 18-70 years, from the Swedish National Diabetes Register with 1,482 first incident CVD events based on 58,342 person-years with mean follow-up) of 5.64 years. RESULTS - This risk equation incorporates A1C, as in the UK Prospective Diabetes Study risk engine, and several clinical characteristics: onset age of diabetes, diabetes duration, sex, BMI, smoking, systolic blood pressure, and antihypertensive and lipid-reducing drugs. All predictors included were associated with the Outcome (P < 0.0001, except for BMI P = 0.0016) with Cox regression analysis. Calibration was excellent when assessed by comparing observed and predicted risk. Discrimination was sufficient, with a receiver operator curve statistic of 0.70. Mean 5-year risk of CVD in all patients was 12.0 +/- 7.5%, whereas 54% of the patients had a 5-year risk >= 10%. CONCLUSIONS - This more simplified risk equation enables 5-year risk prediction of CVD based on easily available nonlaboratory predictors in clinical practice and A1C and was elaborated in a large observational study obtained from the normal patient population aged up to 70 years.