Background:Many coronary heart disease (CHD) events occur in individuals classified as intermediate risk by commonly used assessment tools. Over half the individuals presenting with a severe cardiac event, such as myocardial infarction (MI), have at most one risk factor as included in the widely used Framingham risk assessment. Individuals classified as intermediate risk, who are actually at high risk, may not receive guideline recommended treatments. A clinically useful method for accurately predicting 5-year CHD risk among intermediate risk patients remains an unmet medical need. Objective:This study sought to develop a CHD Risk Assessment (CHDRA) model that improves 5-year risk stratification among intermediate risk individuals. Methods:Assay panels for biomarkers associated with atherosclerosis biology (inflammation, angiogenesis, apoptosis, chemotaxis, etc.) were optimized for measuring baseline serum samples from 1084 initially CHD-free Marshfield Clinic Personalized Medicine Research Project (PMRP) individuals. A multivariable Cox regression model was fit using the most powerful risk predictors within the clinical and protein variables identified by repeated cross-validation. The resulting CHDRA algorithm was validated in a Multiple-Ethnic Study of Atherosclerosis (MESA) case-cohort sample. Results:A CHDRA algorithm of age, sex, diabetes, and family history of MI, combined with serum levels of seven biomarkers (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3, and sFas) yielded a clinical net reclassification index of 42.7% (p<0.001) for MESA patients with a recalibrated Framingham 5-year intermediate risk level. Across all patients, the model predicted acute coronary events (hazard ratio=2.17, p<0.001), and remained an independent predictor after Framingham risk factor adjustments. Limitations:These include the slightly different event definition with the MESA samples and inability to include PMRP fatal CHD events. Conclusions:A novel risk score of serum protein levels plus clinical risk factors, developed and validated in independent cohorts, demonstrated clinical utility for assessing the true risk of CHD events in intermediate risk patients. Improved accuracy in cardiovascular risk classification could lead to improved preventive care and fewer deaths.
Bibliographical noteFunding Information:
Funding for the study was provided by Aviir Inc., Irvine, CA, USA; R.T. is supported by grants and contracts: NO1 HC55222, NO1 HC95166, R01 HL093081, U01 HL084904, P50 ES015915, RO1 HL071862, U01 AI068641, R01 HL094555, and N01-AG62106. R.M. is supported by grants: NHLBI-HC-95159, R01 HL088451, R01 HL080015, R01HL098433, and HHSN275200800015C. P.S.T. is supported by an Established Investigator Award (0840172N) from the American Heart Association. This research was supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute. The PMRP infrastructure was supported by grant U54TR000021 Clinical and Translational Science Award from the National Center for Advancing Translational Sciences.
- Clinical validation
- Coronary heart disease
- Myocardial infarction
- Risk assessment