External validation of the UK Prospective Diabetes Study (UKPDS) risk engine in patients with type 2 diabetes

Aims/hypothesis Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engine for predicting cardiovascular risk in patients with type 2 diabetes, although validation studies showed moderate performance. The methods used in these validation studies were diverse, however, and s...

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Veröffentlicht in:Diabetologia 2011-02, Vol.54 (2), p.264-270
Hauptverfasser: van Dieren, S., Peelen, L. M., Nöthlings, U., van der Schouw, Y. T., Rutten, G. E. H. M., Spijkerman, A. M. W., van der A, D. L., Sluik, D., Boeing, H., Moons, K. G. M., Beulens, J. W. J.
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Sprache:eng
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Zusammenfassung:Aims/hypothesis Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engine for predicting cardiovascular risk in patients with type 2 diabetes, although validation studies showed moderate performance. The methods used in these validation studies were diverse, however, and sometimes insufficient. Hence, we assessed the discrimination and calibration of the UKPDS risk engine to predict 4, 5, 6 and 8 year cardiovascular risk in patients with type 2 diabetes. Methods The cohort included 1,622 patients with type 2 diabetes. During a mean follow-up of 8 years, patients were followed for incidence of CHD and cardiovascular disease (CVD). Discrimination and calibration were assessed for 4, 5, 6 and 8 year risk. Discrimination was examined using the c -statistic and calibration by visually inspecting calibration plots and calculating the Hosmer–Lemeshow χ 2 statistic. Results The UKPDS risk engine showed moderate to poor discrimination for both CHD and CVD ( c -statistic of 0.66 for both 5 year CHD and CVD risks), and an overestimation of the risk (224% and 112%). The calibration of the UKPDS risk engine was slightly better for patients with type 2 diabetes who had been diagnosed with diabetes more than 10 years ago compared with patients diagnosed more recently, particularly for 4 and 5 year predicted CVD and CHD risks. Discrimination for these periods was still moderate to poor. Conclusions/interpretation We observed that the UKPDS risk engine overestimates CHD and CVD risk. The discriminative ability of this model is moderate, irrespective of various subgroup analyses. To enhance the prediction of CVD in patients with type 2 diabetes, this model should be updated.
ISSN:0012-186X
1432-0428
DOI:10.1007/s00125-010-1960-0