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Cardiovascular risk and diabetes. Are the methods of risk prediction satisfactory?

Jeffrey W Stephens1, Gareth Ambler, Patrick Vallance

  • 1Department of Diabetes & Endocrinology, UCL Hospitals, Mortimer Street, London, UK. rmhajst@ucl.ac.uk

European Journal of Cardiovascular Prevention and Rehabilitation : Official Journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology
|December 8, 2004
PubMed

Insights

Cardiovascular disease (CVD) and coronary heart disease (CHD) risk prediction tools generally underestimate future events in diabetic patients. The CardioRisk Manager (CRM) calculator demonstrated the strongest correlation between observed and predicted risk, suggesting it is the most accurate method.

Area of Science:

  • Cardiology
  • Diabetology
  • Public Health

Background:

  • Existing cardiovascular disease (CVD) and coronary heart disease (CHD) risk prediction methods include the Joint British Societies Risk Chart (JBSRC), CardioRisk Manager (CRM), PROCAM, and UKPDS risk engine.
  • Efficacy of these tools in predicting risk within a diabetic patient population requires examination.

Purpose of the Study:

  • To evaluate the accuracy of established CVD and CHD risk prediction tools in a clinic-based diabetic population.
  • To compare the performance of JBSRC, CRM, PROCAM, and UKPDS risk engine in predicting 10-year risk.

Main Methods:

  • A cohort of 798 diabetic patients was identified from baseline (1990-1991) and follow-up (2000-2001) data.
  • Ten-year CVD and CHD risk was calculated using JBSRC, CRM, PROCAM, and UKPDS.
  • Risk prediction accuracy was assessed using the Hosmer-Lemeshow test (calibration), C-index (discrimination), and Spearman correlation.

Main Results:

  • All tested risk prediction methods, except PROCAM, showed acceptable discrimination for CHD/CVD.
  • All methods tended to underestimate the risk of future cardiovascular events.
  • The CardioRisk Manager (CRM) exhibited the highest C-index for CVD (0.76) and a strong correlation (r=0.97) between observed and predicted risk.

Conclusions:

  • While all risk scores offer reasonable discrimination, they underestimate future cardiovascular events in diabetic patients.
  • The CRM calculator, particularly when adjusted for calibration, provides the most accurate risk prediction among the evaluated tools.
  • The CRM's superior performance is indicated by its strong correlation between observed and predicted risk and minimal scatter.
Abstract

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