Aggregate Clinical and Biomarker-Based Model Predicts Adverse Outcomes in Patients With Coronary Artery Disease

Shivang R. Desai, Devinder S. Dhindsa, Yi An Ko, Pratik B. Sandesara, Anurag Mehta, Chang Liu, Ayman S. Tahhan, Salim S. Hayek, Kiran Ejaz, Ananya Hooda, Ayman Alkhoder, Shabatun J. Islam, Steven C. Rogers, Agim Beshiri, Gillian Murtagh, Jonathan H. Kim, Peter Wilson, Zakaria Almuwaqqat, Laurence S. Sperling, Arshed A. Quyyumi

Research output: Contribution to journalArticlepeer-review

Abstract

Despite guideline-based therapy, patients with coronary artery disease (CAD) are at widely variable risk for cardiovascular events. This variability demands a more individualized risk assessment. Herein, we evaluate the prognostic value of 6 biomarkers: high-sensitivity C-reactive protein, heat shock protein-70, fibrin degradation products, soluble urokinase plasminogen activator receptor, high-sensitivity troponin I, and B-type natriuretic peptide. We then develop a multi-biomarker-based cardiovascular event prediction model for patients with stable CAD. In total, 3,115 subjects with stable CAD who underwent cardiac catheterization at Emory (mean age 62.8 years, 17% Black, 35% female, 57% obstructive CAD, 31% diabetes mellitus) were randomized into a training cohort to identify biomarker cutoff values and a validation cohort for prediction assessment. Main outcomes included (1) all-cause death and (2) a composite of cardiovascular death and nonfatal myocardial infarction (MI) within 5 years. Elevation of each biomarker level was associated with higher event rates in the training cohort. A biomarker risk score was created using optimal cutoffs, ranging from 0 to 6 for each biomarker exceeding its cutoff. In the validation cohort, each unit increase in the biomarker risk score was independently associated with all-cause death (hazard ratio 1.62, 95% confidence interval [CI] 1.45 to 1.80) and cardiovascular death/MI (hazard ratio 1.52, 95% CI 1.35 to 1.71). A biomarker risk prediction model for cardiovascular death/MI improved the c-statistic (∆ 6.4%, 95% CI 3.9 to 8.8) and net reclassification index by 31.1% (95% CI 24 to 37), compared with clinical risk factors alone. Integrating multiple biomarkers with clinical variables refines cardiovascular risk assessment in patients with CAD.

Original languageEnglish (US)
Pages (from-to)315-324
Number of pages10
JournalAmerican Journal of Cardiology
Volume203
DOIs
StatePublished - Sep 15 2023
Externally publishedYes

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Fingerprint

Dive into the research topics of 'Aggregate Clinical and Biomarker-Based Model Predicts Adverse Outcomes in Patients With Coronary Artery Disease'. Together they form a unique fingerprint.

Cite this