Concordance/discordance between plasma apolipoprotein B levels and the cholesterol indexes of atherosclerotic risk
Abstract
The objective of the present study was to examine concordance/discordance among 4 atherogenic indexes of cardiovascular risk: plasma total cholesterol, low-density lipoprotein (LDL) cholesterol, non-high-density lipoprotein (non-HDL) cholesterol, and apolipoprotein B-100 (apoB). Analyses were conducted in a cohort of 2,103 men without coronary artery disease (CAD) at the onset of the Quebec Cardiovascular Study. Although there were strong and highly significant correlations among the 4 risk indexes (0.78 1/3 of all subjects had discordant levels. Kappa analysis confirmed that there was only fair agreement between apoB and total or LDL cholesterol (0.38 and 0.36, respectively) and only moderate agreement between non-HDL cholesterol and apoB (0.47). Finally, a significant proportion of subjects (528 of 2,103) who had disproportionately higher apoB levels than would have been predicted based on their LDL cholesterol concentrations was more obese and manifested several features of the metabolic syndrome. They also had a significantly increased cardiovascular risk. In summary, plasma apoB and the various cholesterol indexes are complementary rather than competitive indexes of atherosclerotic risk and provide further evidence as to why measurement of apoB should be part of a standard lipoprotein assessment of CAD risk.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Elevated non-HDL cholesterol levels beyond 130 mg/dL are linked with an increased risk of cardiovascular complications.
“Elevated levels beyond this threshold are linked with an increased risk of cardiovascular complications [38].”
From Residual Cardiovascular Risk: Role of Remnants Cholesterol, Monocyte/HDL Ratio and Lipoprotein Ratios on Personalized Cardiovascular Prevention (2024) · cites this paper as [38]
Non-HDL cholesterol values are deemed optimal when they are below 130 mg/dL.
“Non-HDL cholesterol values are deemed optimal when they are below 130 mg/dL.”
From Residual Cardiovascular Risk: Role of Remnants Cholesterol, Monocyte/HDL Ratio and Lipoprotein Ratios on Personalized Cardiovascular Prevention (2024) · cites this paper as [38]
Non-HDL cholesterol has been proposed as a secondary therapeutic target for individuals with elevated triglyceride levels and has also been considered a potential surrogate marker for serum apolipoprotein B concentration.
“This specific cholesterol type has been proposed as a secondary therapeutic target for individuals with elevated triglyceride levels and has also been considered a potential surrogate marker for serum apolipoprotein B concentration.”
From Residual Cardiovascular Risk: Role of Remnants Cholesterol, Monocyte/HDL Ratio and Lipoprotein Ratios on Personalized Cardiovascular Prevention (2024) · cites this paper as [38]
Non-HDL cholesterol includes cholesterol contained in all atherogenic lipoproteins (LDL, Lp(a), VLDL, IDL, chylomicrons and their remnants).
“Worthy of mention is non-HDL cholesterol which includes cholesterol contained in all atherogenic lipoproteins (LDL, Lp(a), VLDL, IDL, chylomicrons and their remnants).”
From Residual Cardiovascular Risk: Role of Remnants Cholesterol, Monocyte/HDL Ratio and Lipoprotein Ratios on Personalized Cardiovascular Prevention (2024) · cites this paper as [38]
Discordance analysis was designed to compare the predictive accuracy of two highly correlated variables.
“Discordance analysis was designed to compare the predictive accuracy of two highly correlated variables.15”
From Discordance among apoB, non-high-density lipoprotein cholesterol, and triglycerides: implications for cardiovascular prevention (2024) · cites this paper as [15]
Cited by
Sorted by citations
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 · see citing works
Self-citationPischon, T., Girman, C. J., Sacks, F. M., Rifai, N., Stampfer, M. J., & Rimm, E. B. (2005) · Circulation · doi:10.1161/circulationaha.104.532499 · Cited by 514 · see citing works
Blonde, L., Umpierrez, G. E., Reddy, S. S., McGill, J. B., Berga, S. L., Bush, M., Chandrasekaran, S., DeFronzo, R. A., Einhorn, D., Galindo, R. J., et al. (2022) · Endocrine Practice · doi:10.1016/j.eprac.2022.08.002 · Cited by 507 · see citing works
Samson, S. L., Vellanki, P., Blonde, L., Christofides, E. A., Galindo, R. J., Hirsch, I. B., Isaacs, S. D., Izuora, K. E., Low Wang, C. C., Twining, C. L., et al. (2023) · Endocrine Practice · doi:10.1016/j.eprac.2023.02.001 · Cited by 375 · see citing works
Johannesen, C. D. L., Mortensen, M. B., Langsted, A., & Nordestgaard, B. G. (2021) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2021.01.027 · Cited by 359 · see citing works
Mora, S., Buring, J. E., & Ridker, P. M. (2014) · Circulation · doi:10.1161/circulationaha.113.005873 · Cited by 255 · see citing works
Bhanpuri, N. H., Hallberg, S. J., Williams, P. T., McKenzie, A. L., Ballard, K. D., Campbell, W. W., McCarter, J. P., Phinney, S. D., & Volek, J. S. (2018) · Cardiovascular Diabetology · doi:10.1186/s12933-018-0698-8 · Cited by 190 · see citing works
Pencina, M. J., D’Agostino, R. B., Zdrojewski, T., Williams, K., Thanassoulis, G., Furberg, C. D., Peterson, E. D., Vasan, R. S., & Sniderman, A. D. (2015) · European Journal of Preventive Cardiology · doi:10.1177/2047487315569411 · Cited by 164 · see citing works
Self-citationSniderman, A. D., Islam, S., Yusuf, S., & McQueen, M. J. (2012) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2012.08.039 · Cited by 138 · see citing works
Self-citationMora, S., Caulfield, M. P., Wohlgemuth, J., Chen, Z., Superko, H. R., Rowland, C. M., Glynn, R. J., Ridker, P. M., & Krauss, R. M. (2015) · Circulation · doi:10.1161/circulationaha.115.016857 · Cited by 126 · see citing works
Sniderman, A. D., Dufresne, L., Pencina, K. M., Bilgic, S., Thanassoulis, G., & Pencina, M. J. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae258 · Cited by 117 · see citing works
“15 Yet, discordance analysis, like other standard epidemiologic analyses, relies on estimates derived from groups whereas clinical decisions are made in individual cases to maximize individual benefit and to minimize individual risk.”
BackgroundSelf-citationApolipoproteins as markers and managers of coronary risk
Chan, D. C. (2006) · QJM · doi:10.1093/qjmed/hcl027 · Cited by 117 · see citing works
Gjuladin-Hellon, T., Davies, I. G., Penson, P., & Amiri Baghbadorani, R. (2019) · Nutrition Reviews · doi:10.1093/nutrit/nuy049 · Cited by 108 · see citing works
Holewijn, S., Den Heijer, M., Swinkels, D. W., H Stalenhoef, A. F., & De Graaf, J. (2010) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2010.02277.x · Cited by 64 · see citing works
Mehta, R., Reyes-Rodríguez, E., Yaxmehen Bello-Chavolla, O., Guerrero-Díaz, A. C., Vargas-Vázquez, A., Cruz-Bautista, I., & A. Aguilar-Salinas, C. (2018) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2018.06.868 · Cited by 52 · see citing works
Update on the laboratory investigation of dyslipidemias
Ramasamy, I. (2018) · Clinica Chimica Acta · doi:10.1016/j.cca.2018.01.015 · Cited by 50 · see citing works
Lorenzatti, A. J., Monsalvo, M. L., López, J. A. G., Wang, H., & Rosenson, R. S. (2021) · Cardiovascular Diabetology · doi:10.1186/s12933-021-01287-6 · Cited by 34 · see citing works
ApoB, LDL-C, and non-HDL-C as markers of cardiovascular risk
Sehayek, D., Cole, J., Björnson, E., Wilkins, J. T., Mortensen, M. B., Dufresne, L., Pencina, K. M., Pencina, M. J., Thanassoulis, G., & Sniderman, A. D. (2025) · Journal of Clinical Lipidology · doi:10.1016/j.jacl.2025.05.024 · Cited by 20 · see citing works
Self-citationSucato, V., Comparato, F., Ortello, A., Galassi, A. R., & Novo, G. (2024) · Journal of Personalized Medicine · doi:10.3390/jpm14050460 · Cited by 12 · see citing works
“Non-HDL cholesterol values are deemed optimal when they are below 130 mg/dL. Elevated levels beyond this threshold are linked with an increased risk of cardiovascular complications [38].”
Background
- Authors
- Sniderman, A. D., St-Pierre, A. C., Cantin, B., Dagenais, G. R., Després, J.-P., & Lamarche, B.
- Affiliations
- McGill University Health Centre (CA)
- Venue
- The American Journal of Cardiology
- Publisher
- Elsevier BV
- Published
- 2003-05
- Volume
- 91
- Issue
- 10
- Pages
- 1173-1177
- ISSN
- 0002-9149 (ISSN-L)
- OpenAlex
- W2090796532
- Cited by
- 224
- References
- 0
- Citations by year
- 2026: 6 · 2025: 5 · 2024: 12 · 2023: 9 · 2022: 10 · 2021: 9 · 2020: 8 · 2019: 10 · 2018: 9 · 2017: 2 · 2016: 6 · 2015: 13 · 2014: 8 · 2013: 12 · 2012: 9
- FWCI
- 13.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Journal of Cardiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Surgery › Cholesterol and Lipid Metabolism
- Keywords
- apolipoprotein B, LDL cholesterol, non-HDL cholesterol, total cholesterol, atherosclerotic cardiovascular risk, coronary artery disease risk, metabolic syndrome, obesity
- MeSH terms
- Aged, Apolipoproteins B, Arteriosclerosis, Cholesterol, Follow-Up Studies, Humans, Cholesterol, HDL, Cholesterol, LDL, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Quebec, Risk Factors, Severity of Illness Index, Body Mass Index
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
