Risk prediction models are widely used in primary care to identify and initiate therapy in those at risk for future cardiovascular events. While conventional risk factors such as smoking and hypertension are reliably and robustly represented in these models, the value of newer emerging biomarkers such as C-reactive protein (CRP) and fibrinogen are of uncertain value. In this very large meta-analysis of data from 52 prospective studies, including 246,669 participants being evaluated for primary prevention, the value of adding CRP or fibrinogen levels to conventional risk factors was studied with the clinical implications being modelled on the initiation of statin therapy after reclassification of individuals on biomarker levels. Classifying additional gain by the C-index, a measure of risk discrimination, the addition of CRP or fibrinogen increased the C-index by 0.0039 and 0.0027, respectively (P<0.001), and yielded a net reclassification improvement of 1.52% and 0.83%, respectively, for the predicted 10-year risk categories of “low” (<10%), “intermediate” (10% to <20%), and “high” (≥20%) (P<0.02 for both comparisons). Interestingly, the addition of both CRP and fibrinogen to models did little to improve prediction over a single biomarker alone. Using these data and estimating the risk for a cohort of 100,000 adults 40 years of age or older, the addition of CRP or fibrinogen to standard risk models, leading to statin initiation, would help prevent approximately 30 additional cardiovascular events over the course of 10 years.

Conclusions:

In this study, the addition of CRP or fibrinogen measurements to standard risk prediction models could help prevent one additional event over a period of 10 years for every 400 to 500 people screened. However, the cost-effectiveness of such a strategy remains to be explored.

• Kaptoge S, Di Angelantonio E, Pennells L, et al. C-reactive protein, fibrinogen, and cardiovascular disease prediction. N Engl J Med. 2012 Oct 4;367(14):1310-20.