LDL-Cholesterol Distance to Target: A Practical Tool for Guiding Lipid-Lowering Treatment Decisions

Low-density lipoprotein cholesterol (LDL-C) is causal in atherosclerotic cardiovascular disease (ASCVD), still the leading causes of global morbidity and mortality. The 2025 update of the ESC/EAS guidelines for the management of dyslipidemia recommends increasingly stringent, risk-based LDL-C targets. Beyond achieved LDL-C targets, cumulative exposure over time has emerged as a key determinant of ASCVD risk. Accordingly, treatment strategies should evolve from a traditional stepwise approach toward a more proactive, personalized, and target-oriented model; the recognized impact of cumulative LDL-C exposure further reinforces the importance of early, intensive, and sustained lipid lowering therapies (LLT). Despite this awareness and the availability of effective therapies, LDL-C control in clinical practice remains suboptimal. This gap is largely driven by the so called “therapeutic inertia”, involving physician-related factors, patient barriers, and healthcare system constraints; accordingly, fewer than one-third of patients in secondary prevention achieve recommended LDL-C goals. A significant improvement in this situation requires structured treatment algorithms, multidisciplinary care, improved patient education, and integration of digital decision-support tools. A pragmatic framework to improve goal attainment is the estimation of “distance to target” (DtT), which enables selection of LLT based on the required percentage reduction from baseline LDL- C levels. This approach facilitates alignment between the expected efficacy of available treatments and individual patient needs. While statins remain first-line therapy, combination regimens are frequently required—particularly in very high-risk patients—including ezetimibe, bempedoic acid, PCSK9 inhibitors, and inclisiran.