Lipoprotein(a) and Major Adverse Cardiovascular Events in Patients With or Without Baseline Atherosclerotic Cardiovascular Disease.


Central Illustration

Abstract

Background

Lipoprotein(a) [Lp(a)] is associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). However, whether the optimal Lp(a) threshold for risk assessment should differ based on baseline ASCVD status is unknown.

Objectives

The purpose of this study was to assess the association between Lp(a) and major adverse cardiovascular events (MACE) among patients with and without baseline ASCVD.

Methods

We studied a retrospective cohort of patients with Lp(a) measured at 2 medical centers in Boston, Massachusetts, from 2000 to 2019. To assess the association of Lp(a) with incident MACE (nonfatal myocardial infarction [MI], nonfatal stroke, coronary revascularization, or cardiovascular mortality), Lp(a) percentile groups were generated with the reference group set at the first to 50th Lp(a) percentiles. Cox proportional hazards modeling was used to assess the association of Lp(a) percentile group with MACE.

Results

Overall, 16,419 individuals were analyzed with a median follow-up of 11.9 years. Among the 10,181 (62%) patients with baseline ASCVD, individuals in the 71st to 90th percentile group had a 21% increased hazard of MACE (adjusted HR: 1.21; P < 0.001), which was similar to that of individuals in the 91st to 100th group (adjusted HR: 1.26; P < 0.001). Among the 6,238 individuals without established ASCVD, there was a continuously higher hazard of MACE with increasing Lp(a), and individuals in the 91st to 100th Lp(a) percentile group had the highest relative risk with an adjusted HR of 1.93 (P < 0.001).

Conclusions

In a large, contemporary U.S. cohort, elevated Lp(a) is independently associated with long-term MACE among individuals with and without baseline ASCVD. Our results suggest that the threshold for risk assessment may be different in primary vs secondary prevention cohorts.

Lipoprotein(a) Is Markedly More Atherogenic Than LDL: An Apolipoprotein B-Based Genetic Analysis


Central Illustration

Abstract

Background

Lipoprotein(a) (Lp(a)) is recognized as a causal factor for coronary heart disease (CHD) but its atherogenicity relative to that of low-density lipoprotein (LDL) on a per-particle basis is indeterminate.

Objectives

The authors addressed this issue in a genetic analysis based on the fact that Lp(a) and LDL both contain 1 apolipoprotein B (apoB) per particle.

Methods

Genome-wide association studies using the UK Biobank population identified 2 clusters of single nucleotide polymorphisms: one comprising 107 variants linked to Lp(a) mass concentration, the other with 143 variants linked to LDL concentration. In these Lp(a) and LDL clusters, the relationship of genetically predicted variation in apoB with CHD risk was assessed.

Results

The Mendelian randomization-derived OR for CHD for a 50 nmol/L higher Lp(a)-apoB was 1.28 (95% CI: 1.24-1.33) compared with 1.04 (95% CI: 1.03-1.05) for the same increment in LDL-apoB. Likewise, use of polygenic scores to rank subjects according to difference in Lp(a)-apoB vs difference in LDL-apoB revealed a greater HR for CHD per 50 nmol/L apoB for the Lp(a) cluster (1.47; 95% CI: 1.36-1.58) compared with the LDL cluster (1.04; 95% CI: 1.02-1.05). From these data, we estimate that the atherogenicity of Lp(a) is approximately 6-fold (point estimate of 6.6; 95% CI: 5.1-8.8) greater than that of LDL on a per-particle basis.

Conclusions

We conclude that the atherogenicity of Lp(a) (CHD risk quotient per unit increase in particle number) is substantially greater than that of LDL. Therefore, Lp(a) represents a key target for drug-based intervention in a significant proportion of the at-risk population.

Effect of Pelacarsen on Lipoprotein(a) Cholesterol and Corrected Low-Density Lipoprotein Cholesterol


Abstract

Background

Laboratory methods that report low-density lipoprotein cholesterol (LDL-C) include both LDL-C and lipoprotein(a) cholesterol [Lp(a)-C] content.

Objectives

The purpose of this study was to assess the effect of pelacarsen on directly measured Lp(a)-C and LDL-C corrected for its Lp(a)-C content.

Methods

The authors evaluated subjects with a history of cardiovascular disease and elevated Lp(a) randomized to 5 groups of cumulative monthly doses of 20-80 mg pelacarsen vs placebo. Direct Lp(a)-C was measured on isolated Lp(a) using LPA4-magnetic beads directed to apolipoprotein(a). LDL-C was reported as: 1) LDL-C as reported by the clinical laboratory; 2) LDL-Ccorr = laboratory-reported LDL-C − direct Lp(a)-C; and 3) LDL-CcorrDahlén = laboratory LDL-C − [Lp(a) mass × 0.30] estimated by the Dahlén formula.

Results

The baseline median Lp(a)-C values in the groups ranged from 11.9 to 15.6 mg/dL. Compared with placebo, pelacarsen resulted in dose-dependent decreases in Lp(a)-C (2% vs −29% to −67%; P = 0.001-<0.0001). Baseline laboratory-reported mean LDL-C ranged from 68.5 to 89.5 mg/dL, whereas LDL-Ccorr ranged from 55 to 74 mg/dL. Pelacarsen resulted in mean percent/absolute changes of −2% to −19%/−0.7 to −8.0 mg/dL (P = 0.95-0.05) in LDL-Ccorr, −7% to −26%/−5.4 to −9.4 mg/dL (P = 0.44-<0.0001) in laboratory-reported LDL-C, and 3.1% to 28.3%/0.1 to 9.5 mg/dL (P = 0.006-0.50) increases in LDL-CcorrDahlén. Total apoB declined by 3%-16% (P = 0.40-<0.0001), but non-Lp(a) apoB was not significantly changed.

Conclusions

Pelacarsen significantly lowers direct Lp(a)-C and has neutral to mild lowering of LDL-Ccorr. In patients with elevated Lp(a), LDL-Ccorr provides a more accurate reflection of changes in LDL-C than either laboratory-reported LDL-C or the Dahlén formula.

Discussion

The current study demonstrates several novel findings derived from the recent phase 2 study of pelacarsen. First, it demonstrates that pelacarsen produced a robust, dose-dependent reduction in directly measured Lp(a)-C that is consistent with its effect on Lp(a) molar concentration. Second, it shows that in patients with elevated Lp(a), corrected LDL-C is 13 to 16 mg/dL lower than laboratory-reported LDL-C (Central Illustration). This observation should be further evaluated for clinical significance in differentiating major adverse cardiovascular events (MACE) driven by Lp(a)-C vs LDL-C vs both combined.24 Third, it confirms that the Dahlén formula, which uses a fixed 30% correction of Lp(a) mass to estimate Lp(a)-C for every individual, significantly overestimates the Lp(a)-C and underestimates the LDL-C in subjects with elevated Lp(a) and its use should be discontinued. The clinical implications of each finding are discussed in the following text.

Central Illustration
Download FigureDownload PowerPointCentral IllustrationLipoprotein(a) Cholesterol and Corrected Low-Density Lipoprotein Cholesterol Before and After Pelacarsen TherapyA hypothetical patient is presented with a lipoprotein(a) molar concentration of 250 nmol/L treated with pelacarsen 80 mg cumulative monthly. The baseline laboratory-reported low-density lipoprotein cholesterol is 76 mg/dL. However, following direct measurement of the lipoprotein(a) cholesterol component of “low-density lipoprotein cholesterol,” the lipoprotein(a) cholesterol is 14 mg/dL and the corrected low-density lipoprotein cholesterol is 62 mg/dL. Following treatment with pelacarsen, a 67% reduction in lipoprotein(a) cholesterol and 11% reduction on lipoprotein(a) cholesterol is noted, achieving final concentrations of 54 mg/dL and 4.6 mg/L, respectively. LDL-C = low-density lipoprotein cholesterol; LDL-Ccorr = low-density lipoprotein cholesterol estimated by measuring Lp(a)-C directly; Lp(a)-C = lipoprotein(a) cholesterol.

The robust, dose-dependent reduction in Lp(a)-C is a novel observation and mirrored the reduction in Lp(a) molar concentration, but was of slightly lower magnitude. The reduction in Lp(a)-C is not unexpected, because all patients had elevated Lp(a) levels and pelacarsen has been shown to potently lower Lp(a) with no nonresponders identified to date.12,25 The correlations between the baseline and primary endpoint of Lp(a)-C and Lp(a) molar concentration were strong and statistically significant but not near unity. This is consistent with recent observations that Lp(a) particles in subjects with highly elevated Lp(a) are heterogeneous in their cholesterol content, ranging from 6% to 57% in an inverse and curvilinear fashion as recently shown.20 More research is required to identify the factors that lead to such heterogeneity, but besides the LPA gene, possibilities include the APOE, CETP, and APOH genes, which influence Lp(a) levels as recently described from the UK Biobank.26 Such variables may mediate fluxes of triglyceride-rich lipoproteins and cholesterol esters, as well as oxidized phospholipids, between Lp(a) and other lipoproteins or tissues.

We observed that baseline LDL-Ccorr levels were ∼13 to 16 mg/dL lower than the laboratory-reported LDL-C, a clinically significant difference based on the CTT meta-analysis.27 Additionally, we recently showed in a meta-analysis of landmark statin trials including 18,043 patients, 5,390 events, and 4.7 years median follow-up that mathematically removing Lp(a)-C from the laboratory-reported LDL-C in a bracket of 20% to 45% of Lp(a) mass resulted in corrected LDL-C no longer being predictive of MACE.24 The current study, as best as can be estimated with the limitations of converting Lp(a) molar concertation to Lp(a) mass, suggests that many patients have <20% Lp(a)-C of Lp(a) mass as cholesterol. Future studies using the quantitative method described here will be needed to validate the findings of the previously mentioned meta-analysis. With the emergence of Lp(a)-lowering therapeutics,9 the ability to differentiate a more accurate LDL-C from Lp(a)-C may allow the ability to assess which pool of cholesterol will be responsive to LDL-targeted vs Lp(a)-targeted therapies and to choose the most appropriate types and dosage of concomitant therapies.

The trends in changes in LDL-Ccorr are largely reflected in the laboratory LDL-C, but with a attenuation of the effect size leading to lack of statistical significance in all but 1 treatment group. This suggests that the laboratory-reported LDL-C mildly overestimates the LDL-C–lowering effect of pelacarsen, likely because it includes the Lp(a)-C, which was reduced in significantly greater proportion than true LDL-C. We believe the current technique of directly measuring Lp(a)-C and deriving the LDL-Ccorr most closely estimates the most accurate LDL-C changes caused by pelacarsen and that both laboratory-reported LDL-C and the Dahlén formula are less accurate. If the Lp(a) HORIZON trial ( NCT04023552) shows a reduction in MACE, it will allow an opportunity to examine the relative contributions of the reductions in laboratory-reported LDL-C, LDL-Ccorr, Lp(a), and oxidized phospholipids in response to pelacarsen.

It was also demonstrated here that the Dahlén formula, by assuming that Lp(a)-C is universally a fixed 30% of Lp(a) mass, overestimates Lp(a)-C and underestimates true LDL-C in patients with elevated Lp(a), where it is most crucial to differentiate the proportions of each. The original description of this formula was reported in textbook format18,19 and appears to have been studied in a small number of subjects without subsequent rigorous biochemical or clinical validation. Although Lp(a)-C measured using an indirect method in 55 Japanese individuals suggested an average Lp(a)-C mg/dL to Lp(a) mg/dL ratio of 0.3, significant interindividual variation existed.28 Lp(a) mass assays (mg/dL) measure apo(a) immunologically and not total particle mass and use calibrators not traceable to any validated primary standard; thus, the denominator of this equation is a source of error. Based on the current findings, we recommend that the Dahlén formula be discontinued as an estimate corrected LDL-C. We also discourage the reporting of Lp(a)-C as a percentage of Lp(a) mass. Instead, when an Lp(a)-C mass is needed, a directly measured Lp(a)-C should be used to allow determination of Lp(a)-C and LDL-C.

The observation that the significant reduction in total apoB levels appeared to be driven by reduction in Lp(a)-apoB implies enhanced apoB plasma clearance, because pelacarsen is not known to affect APOB mRNA levels.15 It is known that clearance of Lp(a) particles is slower than LDL particles,29-31 likely caused by weaker recognition of Lp(a)-apoB by LDL receptors. Pelacarsen inhibits hepatic apo(a) synthesis and Lp(a) release from the liver, effectively diverting apo(a) from complexing with apoB. This would imply the same amount of apoB is secreted from the liver but in a higher proportion of LDL than Lp(a), which would have faster removal from plasma compared with the same apoB as part of an Lp(a). Other potential mechanisms for the reduction in plasma apoB include a change in the competition for hepatic LDL receptors with a decreasing plasma Lp(a) favoring higher LDL-apoB clearance. It has also been suggested by some but not all kinetic studies that apo(a) may disassociate and reassociate at least once with another apoB-100 particle during its plasma residence,29 which would favor faster clearance of LDL-apoB particles not encumbered by covalently attached apo(a). Finally, the modest divergence of true LDL-C from non-Lp(a) apoB may also imply changes in CETP activity32 or apoE function33 in the pelacarsen groups, both of which can affect LDL-C and Lp(a) levels. Additional studies, including kinetic studies with and without pelacarsen with methodologies recently described studying Lp(a) catabolism with PCSK9 inhibitors,34 will be required to define the underlying mechanisms.

Clinical implications

As therapies to lower Lp(a) are developed, understanding the relative contribution of Lp(a)-C to the laboratory-reported LDL-C in patients with elevated Lp(a) may affect clinical decision making, both in terms of aggressiveness as well as choice in therapy. For example, as shown here in patients with elevated Lp(a), the laboratory-reported LDL-C is incorrectly reported as significantly higher than the corrected LDL-C. Although guidelines for targets of therapy are based on laboratory-reported LDL-C, for subjects with elevated Lp(a), it does not fully capture the risk of the respective components of “LDL-C.” Furthermore, because statins tend to increase Lp(a) levels, only the true LDL-C portion responds to statins.35 Therefore, if the proportion of true LDL-C is lower than realized,36 increasing the dose or adding additional LDL-C–lowering agents may not necessarily treat all of the underlying risk. Persistently elevated LDL-C despite maximal therapy, ie, statin resistance, may also alert clinicians to the hidden presence of elevated Lp(a).17 Ultimately, reporting both LDL-C and Lp(a) molar concentration, or Lp(a)-C, may allow a more personalized approach to addressing residual risk. One may also measure apoB-100 levels; however, they do not easily discriminate what portion is on LDL particles vs other particles, and therefore, it reflects a different measurement.

The current method to quantitate Lp(a)-C may be useful in clinical research studies to understand changes in lipid components affecting both Lp(a)-C and LDL-C. For example, we recently showed in a meta-analysis that included several doses of different statins that most statins increase Lp(a) 8%-24%.35 In those studies, Lp(a)-C was not measured, but it would be interesting to assess if Lp(a)-C also increases with increases in Lp(a) or is unchanged or decreases. Because statins affect cholesterol composition of LDL particles, it would be difficult to predict the effect and any clinical relevance of the increase in Lp(a) without a direct measure of the true LDL-C.

Conclusions

Direct Lp(a)-C assessment in subjects with elevated Lp(a) shows that the LDL-Ccorr is significantly lower than can be appreciated by the clinical laboratory. Pelacarsen significantly decreases in Lp(a)-C with neutral to modest effects on corrected LDL-C. Determining LDL-Ccorr by directly quantitating Lp(a)-C and subtracting it for the laboratory LDL-C provides a more accurate reflection of the baseline and change in LDL-C following pelacarsen in patients with elevated Lp(a).

Source: JACC

Independent Association of Lipoprotein(a) and Coronary Artery Calcification With Atherosclerotic Cardiovascular Risk


Central Illustration

Abstract

Background

Elevated lipoprotein(a) [Lp(a)] and coronary artery calcium (CAC) score are individually associated with increased atherosclerotic cardiovascular disease (ASCVD) risk but have not been studied in combination.

Objectives

This study sought to investigate the independent and joint association of Lp(a) and CAC with ASCVD risk.

Methods

Plasma Lp(a) and CAC were measured at enrollment among asymptomatic participants of the MESA (Multi-Ethnic Study of Atherosclerosis) (n = 4,512) and DHS (Dallas Heart Study) (n = 2,078) cohorts. Elevated Lp(a) was defined as the highest race-specific quintile, and 3 CAC score categories were studied (0, 1-99, and ≥100). Associations of Lp(a) and CAC with ASCVD risk were evaluated using risk factor–adjusted Cox regression models.

Results

Among MESA participants (61.9 years of age, 52.5% women, 36.8% White, 29.3% Black, 22.2% Hispanic, and 11.7% Chinese), 476 incident ASCVD events were observed during 13.2 years of follow-up. Elevated Lp(a) and CAC score (1-99 and ≥100) were independently associated with ASCVD risk (HR: 1.29; 95% CI: 1.04-1.61; HR: 1.68; 95% CI: 1.30-2.16; and HR: 2.66; 95% CI: 2.07-3.43, respectively), and Lp(a)-by-CAC interaction was not noted. Compared with participants with nonelevated Lp(a) and CAC = 0, those with elevated Lp(a) and CAC ≥100 were at the highest risk (HR: 4.71; 95% CI: 3.01-7.40), and those with elevated Lp(a) and CAC = 0 were at a similar risk (HR: 1.31; 95% CI: 0.73-2.35). Similar findings were observed when guideline-recommended Lp(a) and CAC thresholds were considered, and findings were replicated in the DHS.

Conclusions

Lp(a) and CAC are independently associated with ASCVD risk and may be useful concurrently for guiding primary prevention therapy decisions.

Repeat Measures of Lipoprotein(a) Molar Concentration and Cardiovascular Risk


Abstract

Background

When indicated, guidelines recommend measurement of lipoprotein(a) for cardiovascular risk assessment. However, temporal variability in lipoprotein(a) is not well understood, and it is unclear if repeat testing may help refine risk prediction of coronary artery disease (CAD).

Objectives

The authors examined the stability of repeat lipoprotein(a) measurements and the association between instability in lipoprotein(a) molar concentration with incident CAD.

Methods

The authors assessed the correlation between baseline and first follow-up measurements of lipoprotein(a) in the UK Biobank (n = 16,017 unrelated individuals). The association between change in lipoprotein(a) molar concentration and incident CAD was assessed among 15,432 participants using Cox proportional hazards models.

Results

Baseline and follow-up lipoprotein(a) molar concentration were significantly correlated over a median of 4.42 years (IQR: 3.69-4.93 years; Spearman rho = 0.96; P < 0.0001). The correlation between baseline and follow-up lipoprotein(a) molar concentration were stable across time between measurements of ❤ (rho = 0.96), 3-4 (rho = 0.97), 4-5 (rho = 0.96), and >5 years (rho = 0.96). Although there were negligible-to-modest associations between statin use and changes in lipoprotein(a) molar concentration, statin usage was associated with a significant increase in lipoprotein(a) among individuals with baseline levels ≥70 nmol/L. Follow-up lipoprotein(a) molar concentration was significantly associated with risk of incident CAD (HR per 120 nmol/L: 1.32 [95% CI: 1.16-1.50]; P = 0.0002). However, the delta between follow-up and baseline lipoprotein(a) molar concentration was not significantly associated with incident CAD independent of follow-up lipoprotein(a) (P = 0.98).

Conclusions

These findings suggest that, in the absence of therapies substantially altering lipoprotein(a), a single accurate measurement of lipoprotein(a) molar concentration is an efficient method to inform CAD risk.

Lp(a) Levels May Modulate CV Benefits of Evolocumab: FOURIER


Patients treated with the proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor evolocumab (Repatha, Amgen) may experience a greater reduction in cardiovascular events if they have higher baseline levels of lipoprotein(a) [Lp(a)], US investigators have shown.

The results are from a preplanned analysis of the Further Cardiovascular Outcomes Research With PCSK9 Inhibition in Subjects With Elevated Risk (FOURIER) trial, published in March 2017 in the New England Journal of Medicine.

As reported by theheart.org | Medscape Cardiology at that time, main FOURIER results showed that evolocumab was associated with a 15% reduced risk for a composite of myocardial infarction (MI), stroke, cardiovascular disease (CVD), coronary revascularization, and unstable angina hospitalization at 22 months compared with placebo (P < .001).

Moreover, treatment was associated with a 20% reduction in a composite of CVD, MI, and stroke vs placebo (P < .001), which occurred in tandem with large reductions in low-density lipoprotein (LDL) cholesterol levels.

The current analysis, presented here at the European Atherosclerosis Society (EAS) 2018 meeting, shows evolocumab also achieves significant reductions in Lp(a) levels of more than 25%.

The researchers found that the greatest effect of the drug compared with placebo on the risk for cardiovascular death, MI, and stroke was in patients with higher baseline Lp(a) levels, at 24% vs 15% in those with lower levels, at a twofold increase in the absolute risk reduction.

Study presenter Michelle L. O’Donoghue, MD, Brigham and Women’s Hospital, Boston, Massachusetts, told theheart.org | Medscape Cardiology that whether or not the benefits offered by Lp(a) reduction are “above and beyond” the LDL reduction is an area of ongoing study.

“But I think it’s worthwhile that we were able to see that baseline Lp(a) concentration appears to help identify individuals who derive greater benefit from treatment with evolocumab,” she added.

“So if those individuals have a larger magnitude of benefit and a smaller number needed to treat, then that’s perfect, as we’re trying to think about different high-risk features that might help to identify individuals who get the greatest benefit from the drug in a cost-effective manner.”

For O’Donoghue, one of the key aspects of their results is that they suggest that evolocumab affects both Lp(a) and LDL separately to lower the risk for cardiovascular outcomes. This was underlined by data showing that the greatest benefit was seen in individuals who achieved both their Lp(a) and LDL cholesterol target.

“With a drug like evolocumab, you’ve got multiple effects, and it becomes almost like a pleiotropic effect, because you’ve got LDL lowering, which is obviously very compelling, in addition to the effects on Lp(a),” she said.

“I think there’s a lot of work to be done to figure out whether or not the Lp(a) reduction on its own offers as much, or greater, or less benefit than LDL reduction on its own,” she added. “It’s interesting to see, though, that those who achieved the dual targets of lower levels of both are those who do best.”

Evolocumab and Lp(a)

The FOURIER trial involved 27,564 patients with stable atherosclerotic CVD and LDL cholesterol levels of 1.8 mmol/L (70 mg/dL) or higher who were receiving statin therapy and were randomly assigned to evolocumab, 140-mg injections every other week or 420-mg injections monthly, or to placebo.

After a mean follow-up of 2.2 years, evolocumab treatment was associated with a 59% relative reduction (P < .00001), or a 56-mg/dL absolute reduction, in LDL levels down to a median of 30 mg/dL, alongside the observed clinical benefits.

Previous Mendelian randomization data suggested that Lp(a) plays a causal role in the risk for coronary heart disease (CHD), and PCSK9 inhibitors have been shown to significantly reduce Lp(a) levels, so the team examined the impact of evolocumab on Lp(a) in FOURIER.

As part of the trial, Lp(a) levels were measured at baseline and weeks 12 and 58, with results available for 25,096 participants. The median Lp(a) level was 37 nmol/L (interquartile range [IQR], 13 – 165 nmol/L).

Individuals in the highest quartile of Lp(a) levels were, compared with those in the lower quartiles, significantly less likely to be male, to have ischemic stroke and diabetes mellitus, and to currently use tobacco (P < .001 for trend).

In contrast, individuals in the highest quartile were significantly more likely to have had a MI, to have peripheral artery disease, and to have higher baseline LDL cholesterol levels than those in the lower quartiles (P < .001 for trend).

As expected, higher baseline Lp(a) levels were associated in the placebo group with a significantly higher risk for CHD death or MI, cardiovascular death, MI or stroke, and MI and coronary death individually on multivariate analyses taking into account a range of potential confounding factors.

For example, the adjusted hazard ratio of CHD death or MI in participants with an Lp(a) in quartile 4 vs those in quartile 1 was 1.26 (95% CI, 1.02 – 1.56).

Among 11,864 participants given evolocumab, treatment was associated with a mean absolute change in Lp(a) levels at week 48 of –11 nmol/L (IQR, –31 nmol/L to –1 nmol/L), or a median percentage change of –26.9% (IQR, –46.7% to –6.2%).

The correlation between percentage change in Lp(a) and change in LDL cholesterol at 48 weeks in treated patients was r = 0.37 (P < .001), while that for absolute change was r = 0.21.

When the team divided the patients into those whose baseline Lp(a) level was above the median and those whose level was at or below the median, they found a difference in the impact of evolocumab on cardiovascular outcomes vs placebo.

Specifically, patients with a baseline Lp(a) level above the median had a hazard ratio of cardiovascular death, MI, or stroke with evolocumab vs placebo of 0.76 (95% CI, 0.66 – 0.86), or an absolute risk reduction of 2.8% and a number needed to treat of 36.

This compares with a hazard ratio for evolocumab vs placebo among patients with a baseline Lp(a) level at or below the median of 0.85 (95% CI, 0.73 – 0.97), or an absolute risk reduction of 1.28% and a number needed to treat of 79.

Next, the team looked at Lp(a) and LDL cholesterol together in terms of the impact of evolocumab treatment on the risk for combined cardiovascular events after week 12.

The risk was lower in patients who achieved a reduction of Lp(a) and LDL cholesterol to at or below the median at baseline (6.57%) than in those who achieved that milestone only with Lp(a) (7.88%), those who got there only with LDL cholesterol (8.45%), and those who achieved that for neither measure (9.43%) (P < .001 overall).

Concluding her presentation, O’Donoghue said their findings show that evolocumab significantly reduces Lp(a) levels and that “patients starting with higher Lp(a) levels appear to derive greater absolute benefit.”

Moreover, individuals “who achieve lower levels of both LDL cholesterol and Lp(a) have the lowest subsequent risk of CV events.”

Speaking after the session in an interview, she said that this latter finding is particularly interesting when one thinks of the individuals who have a reduction in Lp(a) levels “but a rise in LDL cholesterol levels at the same time.”

“What are those genetic predictors that help to identify those individuals? It’s not completely clear,” she said.

Completely Different Story

Commenting on the findings, Alberico L. Catapano, MD, PhD, professor of pharmacology at the University of Milan, Italy, and past president of the EAS, told theheart.org | Medscape Cardiology that “it’s a completely different story” between Lp(a) and LDL cholesterol.

He explained that with LDL cholesterol, the greater the reduction in plasma levels, the greater the benefit, while with Lp(a), “there’s always been a struggle” to demonstrate a similar relationship.

“Lp(a) is related to cardiovascular disease, but the strongest relationship is with calcification of the aortic wall, or aortic stenosis,” he said.

However, Catapano noted that the “exact mechanism is still not completely clear,” unlike the situation with LDL.

“Of course, we’ll never know everything for sure but we have robust evidence with LDL,” he said. “With Lp(a), it’s not clear whether it’s coagulation, whether it’s atherosclerosis and the buildup of cholesterol, or both together.”

“Having said that,” he added, “there is clearly a relationship that is not linear but sort-of hyperbolic, so that above a certain level, the correlation gets stronger and the risk becomes higher.”

Catapano pointed out, however, that the median Lp(a) levels seen in the FOURIER trial were lower than those seen in the general population and lower than the 50 mg/dL that has been linked to a substantially increased cardiovascular risk, “so you would not expect a huge benefit” with Lp(a) reduction in this population.

“The second point is they saw a benefit that was larger in absolute terms according to the levels of Lp(a), [which] is entirely in line with what we know,” he said. “We know that Lp(a) contributes to the risk and we know that we have a higher risk if we have higher Lp(a), and that reducing LDL cholesterol for sure reduces the risk.”

“Whether the contribution of Lp(a) to that reduction of risk is important, we do not know; it would be almost impossible to disentangle from the data,” he said. “That’s my personal view.”

However, Catapano believes, these answers may be provided  with the results of ongoing studies into antisense nucleotides, which target Lp(a) specifically.

FOURIER was funded by Amgen. O’ Donoghue reports receiving research grant support from GlaxoSmithKline, Eisai, Merck & Co, Janssen, Amgen, The Medicines Company, and AstraZeneca. Catapano reports being a consultant for and receiving honoraria from Pfizer, Sanofi, Genzyme, Merck, Akcea, and Amgen; receiving honoraria from Kowa, Mediolanum, Farmaceuti, Menarini, Bayer, Eli Lilly, Recordati, and Genzyme; and receiving research grants from Pfizer, Merck, Sanofi, Menarini, Regeneron, Mediolanum, and Farmaceutici.

 

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