CIMT does little to augment Framingham risk score

Although current cardiovascular risk equations perform reasonably well in predicting disease, improvement is still needed.  One way to do this would be to include a measure of preclinical atherosclerosis in risk prediction algorithms.  Measurement of common carotid initima-media thickness (CIMT) could be of use in this regard, but evidence that it can aid existing risk scores in prediction of the absolute risk of cardiovascular events has been inconsistent.

In this meta-analysis, the authors’ aim was to determine whether common CIMT could improve the 10-year risk prediction of first-time myocardial infarction and stroke above that of the Framingham risk score.  Relevant studies performed between 1950 and 2012 were selected, where patients had had a baseline CIMT performed and were then followed up for a first cardiovascular event.  Individual data were combined into one data set and an individual participant data meta-analysis was performed on individuals without existing cardiovascular disease.

14 population-based cohorts were analysed, contributing data for 45,828 individuals.  Over a median follow-up of 11 years, 4007 first-time myocardial infarctions or strokes occurred.  The authors looked at the accuracy of the Framingham risk score with and without the incorporation of CIMT.  The C statistic of both models was similar, and the net reclassification improvement with the addition of common CIMT was small (0.8%). Looking specifically at those at intermediate risk, the net reclassification improvement was 3.6% in all individuals, with no differences noted between men and women.


Adding common CIMT measurements to the Framingham Risk Score was associated with a small improvement in 10-year risk prediction of first-time myocardial infarction or stroke.  However, it is unlikely that such a small improvement will be of clinical importance.

•   Den Ruijter HM, Peters SAE, Anderson TJ et al.  Common Carotid Intima-Media Thickness Measurements in Cardiovascular Risk Prediction.  A Meta-analysis.  JAMA 2012;308:796-803.

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