Lipoprotein(a) adds no predictive value for coronary disease beyond traditional risk factors

Background Elevated lipoprotein(a) [Lp(a)] is considered a causal cardiovascular risk factor, yet its independent contribution to coronary artery disease (CAD) in contemporary clinical practice remains uncertain. Determining whether Lp(a) adds predictive value beyond established risk factors is essential for risk stratification and treatment decisions. Purpose To assess whether Lp(a) independently predicts CAD after adjustment for traditional cardiovascular risk factors and lipid parameters, including LDL-C and remnant cholesterol (REMN-C). Methods We evaluated 1,342 consecutive patients from the PMMHRI-Lp(a) Registry referred for cardiovascular assessment. CAD was defined clinically. Logistic regression assessed the association between Lp(a) (analyzed as a continuous variable) and CAD, adjusted for age, sex, diabetes, hypertension, LDL-C, and REMN-C. Model performance is reported using odds ratios (ORs) with 95% confidence intervals (CIs). Results Lp(a) levels did not differ significantly between CAD and non-CAD groups (p=0.087) (Figure 1). Lp(a) was not an independent predictor of CAD (OR 1.00 per 1 mg/dL; 95% CI 0.998–1.007; p = 0.34). Strong predictors included age (OR 1.05 per year; 95% CI 1.03–1.07), male sex (OR 1.77; 95% CI 1.14–2.74), and hypertension (OR 4.46; 95% CI 2.71–7.58). LDL-C was inversely associated with CAD (OR 0.99; p < 0.001), likely reflecting more intensive lipid-lowering therapy in patients with established disease. REMN-C was not associated with CAD (Figure 2). The model demonstrated good discrimination and internal consistency. Conclusions In this large clinical cohort, Lp(a) did not independently predict CAD after adjustment for traditional risk factors and LDL-C. These results suggest the clinical impact of Lp(a) may depend on additional modifiers and may be attenuated in populations receiving intensive lipid-lowering therapy. Prospective studies are needed to determine whether Lp(a)-lowering interventions significantly improve cardiovascular outcomes.