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Coronary risk assessment among intermediate risk patients using a clinical and biomarker based algorithm developed
D S Cross1, C A McCarty, E Hytopoulos
1The Marshfield Clinic, Marshfield, WI, USA.
Insights
A new coronary heart disease (CHD) risk assessment model combining clinical factors and serum biomarkers accurately identifies intermediate-risk patients. This improved risk stratification can lead to better preventive care and reduced mortality.
Area of Science:
- Cardiovascular Medicine
- Biomarker Discovery
- Risk Stratification
Background:
- Many coronary heart disease (CHD) events occur in individuals classified as intermediate risk by current tools.
- A significant proportion of severe cardiac events, like myocardial infarction (MI), happen in individuals with few traditional risk factors.
- Accurate 5-year CHD risk prediction for intermediate-risk patients is an unmet clinical need.
Purpose of the Study:
- To develop a novel Coronary Heart Disease Risk Assessment (CHDRA) model.
- To enhance 5-year risk stratification for individuals categorized as intermediate risk for CHD.
Main Methods:
- Optimized assay panels for atherosclerosis-related biomarkers (inflammation, angiogenesis, etc.).
- Measured serum samples from 1084 initially CHD-free individuals.
- Developed a multivariable Cox regression model using clinical and protein variables, validated in the MESA cohort.
Main Results:
- The CHDRA algorithm includes age, sex, diabetes, family history of MI, and seven serum biomarkers (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3, sFas).
- Achieved a 42.7% net reclassification index in MESA patients recalibrated to intermediate risk (p < 0.001).
- The model independently predicted acute coronary events (HR=2.17, p < 0.001) after adjusting for Framingham risk factors.
Conclusions:
- A novel risk score integrating serum protein levels and clinical factors demonstrates clinical utility.
- The CHDRA model accurately assesses true CHD event risk in intermediate-risk patients.
- Improved cardiovascular risk classification can enhance preventive strategies and reduce CHD-related deaths.
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.
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