Lipoprotein(a) as a Predictor of Major Adverse Cardiovascular Events in Patients with Acute Coronary Syndrome

Background: Despite recent advances in reperfusion strategies, acute coronary syndrome (ACS) patients remain at high risk for recurrent major adverse cardiovascular events (MACE). This study aims to investigate the association between lipoprotein(a) (Lp(a)) and MACE in ACS patients, and to systematically evaluate its predictive performance, incremental prognostic value and clinical utility. Methods: This retrospective cohort study included 300 ACS patients with a 1-year follow-up. Serum Lp(a) levels were measured by immunoturbidimetry using fasting venous blood samples collected on the day of admission. Kaplan–Meier and Cox regression analyses were used to assess the association between Lp(a) and MACE. Subgroup and interaction analyses were performed to test the robustness of the findings. Incremental predictive value and net clinical benefit were evaluated using receiver operating characteristic (ROC) curves, the DeLong test, decision curve analysis (DCA) and the integrated discrimination improvement (IDI) index. Results: Baseline Lp(a) levels were significantly higher in the event group (p = 0.006). A significantly lower cumulative survival probability was found in patients with elevated Lp(a) (log-rank p = 0.0014). As a standalone predictor of MACE, Lp(a) yielded an AUC of 0.606 (p = 0.006). The AUC of the baseline model was 0.753 (95% CI: 0.694–0.812), which increased to 0.771 (95% CI: 0.712–0.831) after adding Lp(a). DCA showed that the Lp(a)-guided strategy provided higher net benefit than both the “treat-all” and “treat-none” strategies within a threshold probability range of 0–0.35. Conclusions: Although Lp(a) offers limited incremental value over traditional risk factors and the Gensini score in the low-to-moderate risk range (<0.35), it provides net clinical benefit as a complementary biomarker in ACS.