Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of morbidity and mortality despite effective low-density lipoprotein cholesterol-targeted therapies. This review explores the crucial role of inflammation in the residual risk of ASCVD, emphasizing its impact on atherosclerosis progression and plaque stability. Evidence suggests that high-sensitivity C-reactive protein (hsCRP), and potentially other inflammatory biomarkers, can be used to identify the inflammatory residual ASCVD risk phenotype and may serve as future targets for the development of more efficacious therapeutic approaches. We review the biological basis for the association of inflammation with ASCVD, propose new therapeutic strategies for the use of inflammation-targeted treatments, and discuss current challenges in the implementation of this new treatment paradigm for ASCVD.

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death worldwide and the risk of a major cardiovascular event is highest among those with established disease. Ongoing management of these patients relies on the accurate assessment of their response to any prescribed therapy, and their residual risk, in order to optimize treatment. Recent international guidelines and position statements concur that the plasma concentration of apolipoprotein B (apoB) is the most accurate measure of lipoprotein associated ASCVD risk. This is especially true for the growing number of individuals with diabetes, obesity, or the metabolic syndrome, and those on statin therapy. Most guidelines, however, continue to promote LDL-C as the primary risk marker due to uncertainty as to whether the greater accuracy of apoB is sufficient to warrant a paradigm shift. Recommendations regarding apoB measurement vary, and the information provided on how to interpret apoB results is sometimes insufficient, particularly for non-lipid specialists. Misinformation regarding the reliability of the assays is also frequently repeated despite its equivalent or better standardization than many other diagnostic assays. Thus, demand for apoB testing is relatively low, which means there is little incentive to increase its availability or reduce its cost. In this review, we examine the results of recent clinical outcomes studies and meta-analyses on the relative values of apoB, LDL-C, and non-HDL-C as markers of ASCVD risk. Although there is seemingly minimal difference among these markers when only population-based metrics are considered, it is evident from our analysis that, from a personalized or precision medicine standpoint, many individuals would benefit, at a negligible total cost, if apoB measurement were better integrated into the diagnosis and treatment of ASCVD.

BACKGROUND: A key step in primary prevention is the assessment of atherosclerotic cardiovascular disease (ASCVD) risk. Risk enhancer tests are additional tools used to further improve ASCVD risk assessment over conventional risk markers. Our objective was to determine whether estimated small, dense low-density lipoprotein cholesterol (E-sdLDL-C) can improve risk assessment and serve as a new risk enhancer test. METHODS: We used a prospective cohort analysis of participants in the UK Biobank study with a median (interquartile range) follow-up of 10 (6.7–12.3) years. We included 271 760 individuals who were not on lipid-lowering medication at baseline and did not have incident ASCVD. The primary study outcome was the incidence of all-cause ASCVD. RESULTS: E-sdLDL-C was strongly associated with ASCVD events with a hazard ratio (HR) of 1.23 (95% CI, 1.22–1.24). After multivariable adjustment for age, sex, systolic blood pressure, hypertension, type 2 diabetes, and blood pressure medications, E-sdLDL-C and ApoB (apolipoprotein B) remained the most significant lipid risk factors (HR, 1.18 [95% CI, 1.16–1.19] and 1.17 [95% CI, 1.16–1.18] per SD, respectively). After further adjustment for ApoB, the association between low-density lipoprotein cholesterol (LDL-C) with all-cause ASCVD was completely reversed with an HR of 0.84 (95% CI, 0.81–0.86), but E-sdLDL-C continued to have a significant positive association with an HR of 1.11 (95% CI, 1.08–1.13). When E-sdLDL-C was discordantly higher than either LDL-C or ApoB, the risk for ASCVD was higher (LDL-C, 31% higher; ApoB, 17% higher). When elevated E-sdLDL-C is coupled with other risk enhancer tests, there is a greater risk for developing ASCVD. CONCLUSIONS: In a UK Biobank cohort for primary prevention, the risk of all-cause ASCVD was better captured by E-sdLDL-C than LDL-C. It was also more predictive than LDL-C and ApoB when discordant with these 2 measures. E-sdLDL-C, which can be freely and automatically calculated from a standard lipid panel, can potentially improve ASCVD risk assessment without additional laboratory testing.

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the β-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) < 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG > 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.

Background: Direct measurement of low-density lipoprotein cholesterol (LDL-C) is widely used and recommended by professional society guidelines despite its potential limitations in patients with hypertriglyceridemia and low LDL-C. This study evaluated the performance of 3 direct LDL-C (LDL-CD) assays, 2 modern LDL-C calculation methods [LDL-C Martin (LDL-CM), LDL-C modified Sampson (LDL-CS)] and the conventional Friedewald (LDL-CF) method against the reference method, beta-quantification (LDL-CBQ). Methods: A total of 181 remnant sera from patients with standard lipid panel orders or from patients with LDL-CBQ orders with triglycerides (TG) ≥ 400 mg/dL (4.5 mmol/L), or with TG ≥ 150 mg/dL (1.69 mmol/L) and LDL-C < 70 mg/dL (1.8 mmol/L) were included. LDL-CD and lipid panel data were gathered from Abbott Alinity, Roche Cobas, and Siemens Atellica platforms. Results: LDL-CD among the 3 platforms showed a median CV of 11.2%. In patients with TG <400 mg/dL, LDL-CM and LDL-CS demonstrated less bias and less misclassification at the clinical decision LDL-C levels than LDL-CF or LDL-CD. In the 400 to 800 mg/dL (9.0 mmol/L) TG group, LDL-CS was superior to LDL-CD or LDL-CM in accuracy. When TG is ≥ 800 mg/dL, LDL-CD (Roche) showed substantial bias from LDL-CBQ while LDL-CS (Roche) showed smaller but significant bias. Conclusions: In summary, LDL-CD or LDL-CF showed little advantage over the 2 modern LDL-C calculation methods. LDL-CS showed the best overall correlation with LDL-CBQ and therefore is recommended to replace LDL-CF and potentially LDL-CD when making clinical decisions in patients with low LDL-C and hypertriglyceridemia.