Evaluation of multiple biomarkers of cardiovascular stress for risk prediction and guiding medical therapy in patients with stable coronary disease.

BACKGROUND

Circulating biomarkers can offer insight into subclinical cardiovascular stress and thus have the potential to aid in risk stratification and tailoring of therapy.

METHODS AND

RESULTS

We measured plasma levels of 4 cardiovascular biomarkers, midregional pro-atrial natriuretic peptide (MR-proANP), midregional pro-adrenomedullin (MR-proADM), C-terminal pro-endothelin-1 (CT-proET-1), and copeptin, in 3717 patients with stable coronary artery disease and preserved left ventricular ejection fraction who were randomized to trandolapril or placebo as part of the Prevention of Events With Angiotensin Converting Enzyme (PEACE) trial. After adjustment for clinical cardiovascular risk predictors and left ventricular ejection fraction, elevated levels of MR-proANP, MR-proADM, and CT-proET-1 were independently associated with the risk of cardiovascular death or heart failure (hazard ratios per 1-SD increase in log-transformed biomarker levels of 1.97, 1.48, and 1.47, respectively; P≤0.002 for each biomarker). These 3 biomarkers also significantly improved metrics of discrimination when added to a clinical model. Trandolapril significantly reduced the risk of cardiovascular death or heart failure in patients who had elevated levels of ≥2 biomarkers (hazard ratio, 0.53; 95% confidence interval, 0.36-0.80), whereas there was no benefit in patients with elevated levels of 0 or 1 biomarker (hazard ratio, 1.09; 95% confidence interval, 0.74-1.59; P(interaction)=0.012).

CONCLUSIONS

In patients with stable coronary artery disease and preserved left ventricular ejection fraction, our results suggest that elevated levels of novel biomarkers of cardiovascular stress may help identify patients who are at higher risk of cardiovascular death and heart failure and may be useful to select patients who derive significant benefit from angiotensin-converting enzyme inhibitor therapy.