Apolipoprotein B, non-HDL cholesterol and LDL cholesterol for identifying individuals at increased cardiovascular risk.
Open accessAbstract
Abstract. Holewijn S, den Heijer M, Swinkels DW, Stalenhoef AFH, de Graaf J. (Address: Division of Vascular Medicine, Department of General Internal Medicine; Department of Epidemiology and Biostatistics; Department of Endocrinology; and Department of Laboratory Medicine; Laboratory of Clinical Chemistry, all at the Radboud University, Nijmegen Medical Centre, Nijmegen, The Netherlands) Apolipoprotein B, non‐HDL cholesterol and LDL cholesterol for identifying individuals at increased cardiovascular risk. J Intern Med 2010; 268: 567–577. Background. To compare apolipoprotein B (apoB), nonhigh‐density lipoprotein‐cholesterol (non‐HDL‐c) and low‐density lipoprotein‐cholesterol (LDL‐c) for identifying individuals with a deteriorated cardiovascular (CV) risk profile, including a panel of subclinical atherosclerosis measurements and prevalent cardiovascular disease (CVD) in a Dutch population‐based cohort. Methods. Clinical and biochemical measurements and a panel of noninvasive parameters of subclinical atherosclerosis were determined in 1517 individuals, aged 50–70 years. Results. Both men and women with increasing levels of apoB and non‐HDL‐c were more obese, had higher blood pressure and fasting glucose levels, and a more atherogenic lipid profile. Furthermore, compared to the reference group (composed of those with apoB, non‐HDL‐c and LDL‐c levels in the bottom quartiles), participants with high apoB and high non‐HDL‐c levels had a lower ankle–brachial index at rest (−3.5% and −3.1%, respectively) and after exercise (−6.3% and −4.7%, respectively), a thicker near wall (+4.8% and +4.2%, respectively), far wall (both +6.2%), and mean intima–media thickness (+5.7% and +5.3%, respectively) and more plaques (+54.2% and +54.3%, respectively). In addition, they also showed increased stiffness parameters (e.g. pulse wave velocity both +3.6%). Less clear differences in CV risk profile and subclinical atherosclerosis parameters were observed when participants were stratified by LDL‐c level. Furthermore, apoB but not LDL‐c detected prevalent CVD, and non‐HDL‐c only detected prevalent CVD in men. The discriminatory power for prevalent CVD expressed as area under the receiver operating characteristic curve was 0.60 (P < 0.001) for apoB, 0.57 (P = 0.001) for non‐HDL‐c and 0.54 (P = 0.108) for LDL‐c. Conclusion. Our data support the use of first apoB and secondly non‐HDL‐c above LDL‐c for identifying individuals from the general population with a compromised CV phenotype.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Measurement of apoB is superior to measurement of LDL or even non-HDL cholesterol as an indicator of global CVD risk.
“Several reports also show that measurement of apoB is superior to measurement of LDL or even non-HDL cholesterol as an indicator of global CVD risk (40,41).”
From Evaluation and Treatment of Hypertriglyceridemia: An Endocrine Society Clinical Practice Guideline (2012) · cites this paper as [41]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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 · see citing works
Walldius, G., Jungner, I., Holme, I., AASTVEIT, A. H., Kolar, W., & Steiner, E. (2001) · The Lancet · doi:10.1016/s0140-6736(01)07098-2 · Cited by 1,227 · see citing works
Inflammation in Atherosclerosis: From Vascular Biology to Biomarker Discovery and Risk Prediction
Packard, R. R. S., & Libby, P. (2008) · Clinical Chemistry · doi:10.1373/clinchem.2007.097360 · Cited by 925 · see citing works
Pischon, 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
Apolipoproteins versus lipids as indices of coronary risk and as targets for statin treatment
Sniderman, A. D., Furberg, C. D., KEECH, A. C., van Lennep, J. R., Frohlich, J., Jungner, I., & Walldius, G. (2003) · The Lancet · doi:10.1016/s0140-6736(03)12663-3 · Cited by 457 · see citing works
Nauck, M., Warnick, G. R., & Rifai, N. (2002) · Clinical Chemistry · doi:10.1093/clinchem/48.2.236 · Cited by 442 · see citing works
Contois, J. H., McConnell, J. P., Sethi, A. A., Csako, G., Devaraj, S., Hoefner, D. M., & Warnick, G. R. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2008.118356 · Cited by 326 · see citing works
Arterial stiffness and cardiovascular risk factors in a population-based study
Amar, J., Ruidavets, J. B., Chamontin, B., Drouet, L. O., & Ferrières, J. (2001) · Journal of Hypertension · doi:10.1097/00004872-200103000-00005 · Cited by 273 · see citing works
Hoogendoorn, E. H., Hermus, A. R., de Vegt, F., Ross, H. A., Verbeek, A. L., Kiemeney, L. A., Swinkels, D. W., Sweep, F. C., & den Heijer, M. (2006) · Clinical Chemistry · doi:10.1373/clinchem.2005.055194 · Cited by 255 · see citing works
Self-citationSniderman, A. D., St-Pierre, A. C., Cantin, B., Dagenais, G. R., Després, J.-P., & Lamarche, B. (2003) · The American Journal of Cardiology · doi:10.1016/s0002-9149(03)00262-5 · Cited by 224 · see citing works
Benn, M., Nordestgaard, B. G., Jensen, G. B., & Tybjærg‐Hansen, A. (2006) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/01.atv.0000255580.73689.8e · Cited by 152 · see citing works
Chien, K.-L., Hsu, H.-C., Su, T.-C., Chen, M.-F., Lee, Y.-T., & Hu, F. B. (2007) · Journal of Lipid Research · doi:10.1194/jlr.m700213-jlr200 · Cited by 109 · see citing works
A diagnostic algorithm for the atherogenic apolipoprotein B dyslipoproteinemias.
de Graaf, J., Couture, P., & Sniderman, A. (2008) · Nature Clinical Practice Endocrinology & Metabolism · doi:10.1038/ncpendmet0982 · Cited by 80 · see citing works
Self-citationThe Metabolic Syndrome and Its Traits as Risk Factors for Subclinical Atherosclerosis
Holewijn, S., den Heijer, M., Swinkels, D. W., Stalenhoef, A. F. H., & Graaf, J. D. (2009) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2009-0084 · Cited by 62 · see citing works
Self-citationGrewal, J., Anand, S. S., Islam, S., & Lonn, E. (2007) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2007.06.020 · Cited by 55 · see citing works
Farwell, W. R., Sesso, H. D., Buring, J. E., & Gaziano, J. M. (2005) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2005.06.044 · Cited by 53 · see citing works
Keulen, E. T. P., Kruijshoop, M., Schaper, N. C., Hoeks, A. P. G., & de Bruin, T. W. (2002) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/hq0202.104100 · Cited by 51 · see citing works
Simon, A. C., Chironi, G. N., Gariépy, J., Pino, M. D., & Levenson, J. A. (2004) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2004.10.017 · Cited by 49 · see citing works
Schott, L. L., Wildman, R. P., Brockwell, S. E., Simkin‐Silverman, L. R., Kuller, L. H., & Sutton‐Tyrrell, K. (2004) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/01.atv.0000141119.02205.6b · Cited by 41 · see citing works
ApoB/ApoA1 ratio and subclinical atherosclerosis.
Panayiotou, A. G., Griffin, M., Georgiou, N., et al. (2008) · PubMed · Cited by 38 · see citing works
Schmidt, C. B., Fagerberg, B., Wikstrand, J., & Hulthe, J. (2005) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2005.11.031 · Cited by 34 · see citing works
Apolipoproteins: correlation with carotid intimamedia thickness and coronary artery disease.
Jadhav, U., & Kadam, N. N. (2004) · PubMed · Cited by 27 · see citing works
ter Avest, E., Holewijn, S., Bredie, S. J. H., Stalenhoef, A. F. H., & Graaf, J. D. (2006) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2006.03.025 · Cited by 25 · see citing works
Self-citationAdvanced Lipoprotein Testing: Recommendations Based on Current Evidence
Lau, J. F., & Smith, D. A. (2009) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2008.11.008 · Cited by 19 · see citing works
Ebetjen, M., egura, B., Videenik, V., & Keber, I. (2005) · Coronary Artery Disease · doi:10.1097/00019501-200505000-00007 · Cited by 17 · see citing works
Carotid atherosclerosis in familial combined hyperlipidemia associated with the APOB/APOA-I ratio
Junyent, M., Zambón, D., Gilabert, R., Cofán, M., Núñez, I., & Ros, E. (2007) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2007.07.008 · Cited by 14 · see citing works
Johansson, L. O. M., & Schmidt, C. B. (2008) · Angiology · doi:10.1177/0003319708324925 · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Evaluation and Treatment of Hypertriglyceridemia: An Endocrine Society Clinical Practice Guideline
Berglund, L., Brunzell, J. D., Goldberg, A. C., Goldberg, I. J., Sacks, F., Murad, M. H., & Stalenhoef, A. F. H. (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2011-3213 · Cited by 887 · see citing works
“Several reports also show that measurement of apoB is superior to measurement of LDL or even non-HDL cholesterol as an indicator of global CVD risk (40, 41).”
Self-citationKelley, G. A., Kelley, K. S., Roberts, S., & Haskell, W. (2012) · Clinical Nutrition · doi:10.1016/j.clnu.2011.11.011 · Cited by 125 · see citing works
Monitoring of lipids, enzymes, and creatine kinase in patients on lipid-lowering drug therapy
Wiklund, O., Pirazzi, C., & Romeo, S. (2013) · Current Cardiology Reports · doi:10.1007/s11886-013-0397-8 · Cited by 45 · see citing works
van den Berg, M. J., van der Graaf, Y., de Borst, G. J., Kappelle, L. J., Nathoe, H. M., Visseren, F. L. J., van Petersen, R., van Dinther, B. G. F., Algra, A., van der Graaf, Y., et al. (2016) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2016.06.048 · Cited by 39 · see citing works
- Authors
- Holewijn, S., Den Heijer, M., Swinkels, D. W., H Stalenhoef, A. F., & De Graaf, J.
- Affiliations
- Radboud University Medical Center (NL)
- Corresponding author
- Holewijn, S.
- Venue
- Journal of Internal Medicine
- Publisher
- Wiley
- Published
- 2010-11-22
- Volume
- 268
- Issue
- 6
- Pages
- 567-577
- ISSN
- 0954-6820 (ISSN-L)
- 1365-2796
- OpenAlex
- W1920570639
- Cited by
- 64
- References
- 27
- Citations by year
- 2026: 1 · 2024: 3 · 2023: 8 · 2022: 1 · 2021: 6 · 2020: 8 · 2019: 2 · 2018: 3 · 2017: 6 · 2016: 3 · 2015: 1 · 2014: 1 · 2013: 5 · 2012: 7
- FWCI
- 7.08
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion)
- 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, non-HDL cholesterol, LDL cholesterol, cardiovascular risk, subclinical atherosclerosis, ankle-brachial index, carotid intima-media thickness, carotid plaque, pulse wave velocity, arterial stiffness, atherogenic lipid profile, cardiovascular risk prediction, middle-aged adults, obesity, blood pressure, fasting blood glucose
- MeSH terms
- Aged, Apolipoproteins B, Blood Glucose, Blood Pressure, Cardiovascular Diseases, Cholesterol, Female, Humans, Cholesterol, HDL, Cholesterol, LDL, Male, Middle Aged, Biomarkers, Atherosclerosis
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
