Abstract 10036: Apolipoproteins and Cardiovascular-Kidney-Metabolic-Biomarkers Each Add to Prediction of Residual Cardiovascular Disease Risk After Acute Coronary Syndrome: Insights from the ODYSSEY OUTCOMES Trial

Abstract

Background: Residual cardiovascular risk persists in acute coronary syndrome (ACS) despite intensive lipid-lowering therapy. We investigated whether extended biomarker profiling, including a 9-plex apolipoprotein panel (with apoE phenotyping) and 11 CE-marked emerging Cardiovascular-Kidney-Metabolic (CKM) parameters, improves prediction of major adverse cardiovascular events (MACE) and death beyond conventional demographic and lipid parameters in the ODYSSEY OUTCOMES trial. Methods: The trial was randomized, double-blind, and compared the PCSK9 inhibitor alirocumab to placebo in patients with recent ACS receiving optimized statin treatment. Over a median follow-up of 2.8 years, the primary MACE endpoint comprised coronary heart disease death, nonfatal myocardial infarction, fatal and nonfatal ischemic stroke, and hospitalization for unstable angina; all-cause death was a secondary endpoint. In 11,843 trial participants (placebo n=5926; alirocumab n=5917) apolipoproteins and apoE phenotype were measured by mass spectrometry and CKM parameters were measured using a Roche Cobas analyzer. CKM parameters included cystatin C, high-sensitivity troponin T (hs cTnT) , NT-proBNP, high-sensitivity C-reactive protein, small-dense low-density lipoprotein, GDF-15, sFlt, interleukin 6, insulin, homocysteine, and the NAFLD fibrosis score (Angulo et al . Hepatology . 2007;45:846-54). Incremental multivariable logistic regression models with natural cubic splines were constructed with demographics, diseases and standard lipid parameters (Model 1), apolipoprotein panel (Model 2), and CKM parameters (Model 3). Model performance was assessed using area under the curve (AUC) statistics, DeLong tests and generalized likelihood ratio tests. Due to lower event counts, penalized regression (ridge-type penalty) was applied for death analyses. Results: The baseline model yielded AUCs of 0.66 (0.64 - 0.68) for prediction of MACE and 0.71 (0.68 - 0.74) for death (Figure 1). Addition of apolipoproteins improved the AUCs to 0.69 (0.67 - 0.71) for MACE and 0.76 (0.72 - 0.79) for death. Further addition of CKM parameters improved the AUCs to 0.72 (0.70 - 0.75) and 0.82 (0.79 - 0.85), respectively. For MACE, the five strongest predictors were hs cTnT, apolipoprotein(a), NT-proBNP, diabetes, and cystatin C. For death, the five strongest predictors included NT-proBNP, sex, total cholesterol, age and small dense LDL-C. Conclusion: In statin-treated patients with recent ACS, comprehensive biomarker profiling with a multiplex apolipoprotein panel including apoE phenotypes and emerging CKM tests each provides clinically meaningful improvement in the prediction of MACE and death beyond conventional demographics, disease state and standard lipid profile. These findings support the conclusion that residual risk in ACS is multidimensional.