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Quantifying Atherogenic Lipoproteins: Current and Future Challenges in the Era of Personalized Medicine and Very Low Concentrations of LDL Cholesterol. A Consensus Statement from EAS and EFLM
Open accessAbstract
BACKGROUND: The European Atherosclerosis Society–European Federation of Clinical Chemistry and Laboratory Medicine Consensus Panel aims to provide recommendations to optimize atherogenic lipoprotein quantification for cardiovascular risk management. CONTENT: We critically examined LDL cholesterol, non-HDL cholesterol, apolipoprotein B (apoB), and LDL particle number assays based on key criteria for medical application of biomarkers. (a) Analytical performance: Discordant LDL cholesterol quantification occurs when LDL cholesterol is measured or calculated with different assays, especially in patients with hypertriglyceridemia >175 mg/dL (2 mmol/L) and low LDL cholesterol concentrations <70 mg/dL (1.8 mmol/L). Increased lipoprotein(a) should be excluded in patients not achieving LDL cholesterol goals with treatment. Non-HDL cholesterol includes the atherogenic risk component of remnant cholesterol and can be calculated in a standard nonfasting lipid panel without additional expense. ApoB more accurately reflects LDL particle number. (b) Clinical performance: LDL cholesterol, non-HDL cholesterol, and apoB are comparable predictors of cardiovascular events in prospective population studies and clinical trials; however, discordance analysis of the markers improves risk prediction by adding remnant cholesterol (included in non-HDL cholesterol) and LDL particle number (with apoB) risk components to LDL cholesterol testing. (c) Clinical and cost-effectiveness: There is no consistent evidence yet that non-HDL cholesterol-, apoB-, or LDL particle-targeted treatment reduces the number of cardiovascular events and healthcare-related costs than treatment targeted to LDL cholesterol. SUMMARY: Follow-up of pre- and on-treatment (measured or calculated) LDL cholesterol concentration in a patient should ideally be performed with the same documented test method. Non-HDL cholesterol (or apoB) should be the secondary treatment target in patients with mild to moderate hypertriglyceridemia, in whom LDL cholesterol measurement or calculation is less accurate and often less predictive of cardiovascular risk. Laboratories should report non-HDL cholesterol in all standard lipid panels.
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“Calculated by subtracting HDLC from TC, non-HDLC represents the cholesterol in all particles causing cardiovascular disease, that is, LDL, VLDL, IDL, and Lp(a); in the nonfasting state this additionally includes the cholesterol in chylomicrons and their remnant particles [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“It should be noted that most clinical trials demonstrating the evidence base for clinical benefit of LDLC lowering have used Friedewald cLDLC; thus it cannot be excluded that dLDLC rather than cLDLC is the method that misclassifies risk [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Although apoB demonstrates competitive clinical performance compared with non-HDLC, there is no evidence yet of significant population healtheconomic benefit of intensifying pharmacological intervention aiming to further reduce apoB at very low concentrations of LDLC [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This may compensate for the under-or overestimation of LDLC in terms of clinical decision making, given the uncertainty of dLDLC measurements or the Friedewald calculation in dyslipidemic samples when LDLC lowering approaches 1.4 mmol/L, and non-HDLC can be used at high TG ≥ 4.5 mmol/l.”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“For the present purposes, the combination of non-HDLC with Martin-Hopkins cLDLC may be considered as an appropriate strategy to guide therapy and they can be calculated from the standard lipid profile [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Taken together with the evidence that apoB can be measured more accurately, more precisely, and more selectively than LDL-C or non-HDL-C,1,29–31”
From Discordance among apoB, non-high-density lipoprotein cholesterol, and triglycerides: implications for cardiovascular prevention (2024) · cites this paper as [29]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“RemnantC, measured or calculated, differs from non-HDLC in that non-HDLC contains RemnantC plus LDLC and does not differentiate between these two causal risk factors [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
The cited source says what the claim attributes to it.
In the citing paper
“Direct LDLC measurement should preferably be used in the calculation of RemnantC; otherwise RemnantC simply equals TG/2.2 (in mmol/L) when Friedewald-calculated LDLC is used, i.e.TC -HDLC -(TC -HDLC -TG/2.2),and it does not add clinical information beyond TG concentration [1]”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
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In the citing paper
“Not uncommonly, changes in a patient's LDLC test result over time are within the range of uncertainty of laboratory method variation and may not be due to therapeutic intervention [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
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“Guideline-recommended therapeutic goals for non-HDLC are arbitrarily set typically at 0.8 mmol/L (30 mg/dL) higher than LDLC goals (Table 6); this value is based on the assumption that the”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
The cited source says what the claim attributes to it.
In the citing paper
“Thus, even when cross-reactivity of immunoassays to apoB48 occurs in nonfasting measurements, apoB quantification is essentially an estimate of LDL particle number if TG and Lp(a) concentrations are low [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
The cited source says what the claim attributes to it.
In the citing paper
“Guideline-based non-HDLC thresholds have been arbitrarily defined by consensus of expert groups, based on the assumption that a normal VLDLC concentration exists when TG are < 1.7 mmol/L, which is < 0.8 mmol/L as estimated by the Friedewald formula [1,2].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
The cited source says what the claim attributes to it.
In the citing paper
“Given the uncertainty of measurements and calculations of LDLC across different methods and laboratories, in hypertriglyceridemic patients the decision thresholds may not always be assumed to be universally applicable [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
The cited source says what the claim attributes to it.
In the citing paper
“However, the compromised accuracy of dHDLC assays in samples with hypertriglyceridemia reduces the benefit in reporting non-HDLC in some individuals in whom an apoB or LDLP measurement may be clinically useful [1].”
From Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM (2020) · cites this paper as [1]
In the citing paper
“Non-fasting TG is equivalent, if not superior, to fasting TG in assessing potential ASCVD risk.78,79”
In the citing paper
“However, this study [77] and another based on the Heart Protection Study 2-Treatment of HDL to Reduce the Incidence of Vascular Events (HPS2-THRIVE) trial [78] have shown that large absolute changes in Lp(a) may be needed to produce a clinically meaningful reduction in the risk of ASCVD events.”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [78]
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Citations
Cites
Friedewald, W. T., Levy, R. I., & Fredrickson, D. S. (1972) · Clinical Chemistry · doi:10.1093/clinchem/18.6.499 · Cited by 32,423
Stone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Circulation · doi:10.1161/01.cir.0000437738.63853.7a · Cited by 7,081
Cholesterol Treatment Trialists' (CTT) Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)61350-5 · Cited by 6,550
Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease
Sabatine, M. S., Giugliano, R. P., Keech, A. C., Honarpour, N., Wiviott, S. D., Murphy, S. A., Kuder, J. F., Wang, H., Liu, T., Wasserman, S. M., et al. (2017) · New England Journal of Medicine · doi:10.1056/nejmoa1615664 · Cited by 6,138
Ference, B. A., Ginsberg, H. N., Graham, I., Ray, K. K., Packard, C. J., Bruckert, E., Hegele, R. A., Krauss, R. M., Raal, F. J., Schunkert, H., et al. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx144 · Cited by 3,962
Self-citationStone, N. J., Robinson, J. G., Lichtenstein, A. H., Bairey Merz, C. N., Blum, C. B., Eckel, R. H., Goldberg, A. C., Gordon, D., Levy, D., Lloyd-Jones, D. M., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.002 · Cited by 3,845
Major lipids, apolipoproteins, and risk of vascular disease
The Emerging Risk Factors Collaboration* (2009) · JAMA · doi:10.1001/jama.2009.1619 · Cited by 2,731
Efficacy and Safety of Alirocumab in Reducing Lipids and Cardiovascular Events
Robinson, J. G., Farnier, M., Krempf, M., Bergeron, J., Luc, G., Averna, M., Stroes, E. S., Langslet, G., Raal, F. J., El Shahawy, M., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1501031 · Cited by 2,296
Triglycerides and Cardiovascular Disease: A Scientific Statement From the American Heart Association
Miller, M., Stone, N. J., Ballantyne, C., Bittner, V., Criqui, M. H., Ginsberg, H. N., Goldberg, A. C., Howard, W. J., Jacobson, M. S., Kris-Etherton, P. M., et al. (2011) · Circulation · doi:10.1161/cir.0b013e3182160726 · Cited by 1,871
Lipoprotein(a) as a cardiovascular risk factor: current status
Nordestgaard, B. G., Chapman, M. J., Ray, K., Borén, J., Andreotti, F., Watts, G. F., Ginsberg, H., Amarenco, P., Catapano, A., Descamps, O. S., et al. (2010) · European Heart Journal · doi:10.1093/eurheartj/ehq386 · Cited by 1,807
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Mach, F., Baigent, C., Catapano, A. L., Koskinas, K. C., Casula, M., Badimon, L., Chapman, M. J., De Backer, G. G., Delgado, V., Ference, B. A., et al. (2019) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2019.08.014 · Cited by 4,854
Self-citationGinsberg, H. N., Packard, C. J., Chapman, M. J., Borén, J., Aguilar-Salinas, C. A., Averna, M., Ference, B. A., Gaudet, D., Hegele, R. A., Kersten, S., et al. (2021) · European Heart Journal · doi:10.1093/eurheartj/ehab551 · Cited by 979
Self-citationPearson, G. J., Thanassoulis, G., Anderson, T. J., Barry, A. R., Couture, P., Dayan, N., Francis, G. A., Genest, J. J., Grégoire, J. C., Grover, S. A., et al. (2021) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2021.03.016 · Cited by 900
Apolipoprotein B Particles and Cardiovascular Disease: A Narrative Review
Sniderman, A. D., Thanassoulis, G., Glavinovic, T., Navar, A. M., Pencina, M., Catapano, A., & Ference, B. A. (2019) · JAMA Cardiology · doi:10.1001/jamacardio.2019.3780 · Cited by 593
Self-citationSampson, M. L., Ling, C., Sun, Q., Harb, R., Ashmaig, M., Warnick, R., Sethi, A. A., Fleming, J. K., Otvos, J. D., Meeusen, J. W., et al. (2020) · JAMA Cardiology · doi:10.1001/jamacardio.2020.0013 · Cited by 593
Self-citation
Metadata
- Authors
- Langlois, M. R., Chapman, M. J., Cobbaert, C., Mora, S., Remaley, A. T., Ros, E., Watts, G. F., Borén, J., Baum, H., Bruckert, E., Catapano, A., Descamps, O. S., von Eckardstein, A., Kamstrup, P. R., Kolovou, G., Kronenberg, F., Langsted, A., Pulkki, K., Rifai, N., Sypniewska, G., Wiklund, O., Nordestgaard, B. G., & for the European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Joint Consensus Initiative
- Affiliations
- Ghent University (BE)
- Inserm (FR)
- Leiden University Medical Center (NL)
- Brigham and Women's Hospital (US)
- National Institutes of Health (US)
- Instituto de Salud Carlos III (ES)
- The University of Western Australia (AU)
- Sahlgrenska University Hospital (SE)
- Klinikum Ludwigsburg (DE)
- Pitié-Salpetriere University Hospital, Paris, France
- University of Milan (IT)
- Hôpital de Jolimont (BE)
- Institute for Clinical Chemistry, University Hospital Zurich, Zurich, Switzerland
- University of Copenhagen (DK)
- Onassis Cardiac Surgery Center (GR)
- Innsbruck Medical University (AT)
- University of Turku (FI)
- Boston Children's Hospital (US)
- Department of Laboratory Medicine, Collegium Medicum, NC University, Bydgoszcz, Poland
- Corresponding author
- Langlois, Michel R
- ORCID
- Venue
- Clinical Chemistry
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-07-01
- Volume
- 64
- Issue
- 7
- Pages
- 1006-1033
- ISSN
- 0009-9147 (ISSN-L)
- 1530-8561
- OpenAlex
- W2800713945
- Cited by
- 260
- References
- 146
- Citations by year
- 2026: 18 · 2025: 22 · 2024: 28 · 2023: 32 · 2022: 27 · 2021: 49 · 2020: 43 · 2019: 32 · 2018: 9
- FWCI
- 34.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Clinical Chemistry (publishedVersion)
- UWA Profiles and Research Repository (UWA) (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- HAL (submittedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- Leiden Repository (Leiden University) (submittedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
- Keywords
- atherogenic lipoproteins, LDL cholesterol, non-HDL cholesterol, apolipoprotein B, LDL particle number, remnant cholesterol, lipoprotein(a), hypertriglyceridemia, cardiovascular risk prediction, treatment goals, cost-effectiveness, personalized medicine
- MeSH terms
- Humans, Cholesterol, LDL, Consensus, Atherosclerosis, Precision Medicine
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