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C-Reactive Protein and Other Markers of Inflammation in the Prediction of Cardiovascular Disease in Women
Open accessAbstract
BACKGROUND: Since inflammation is believed to have a role in the pathogenesis of cardiovascular events, measurement of markers of inflammation has been proposed as a method to improve the prediction of the risk of these events. METHODS: We conducted a prospective, nested case-control study among 28,263 apparently healthy postmenopausal women over a mean follow-up period of three years to assess the risk of cardiovascular events associated with base-line levels of markers of inflammation. The markers included high-sensitivity C-reactive protein (hs-CRP), serum amyloid A, interleukin-6, and soluble intercellular adhesion molecule type 1 (sICAM-1). We also studied homocysteine and a variety of lipid and lipoprotein measurements. Cardiovascular events were defined as death from coronary heart disease, nonfatal myocardial infarction or stroke, or the need for coronary-revascularization procedures. RESULTS: Of the 12 markers measured, hs-CRP was the strongest univariate predictor of the risk of cardiovascular events; the relative risk of events for women in the highest as compared with the lowest quartile for this marker was 4.4 (95 percent confidence interval, 2.2 to 8.9). Other markers significantly associated with the risk of cardiovascular events were serum amyloid A (relative risk for the highest as compared with the lowest quartile, 3.0), sICAM-1 (2.6), interleukin-6 (2.2), homocysteine (2.0), total cholesterol (2.4), LDL cholesterol (2.4), apolipoprotein B-100 (3.4), HDL cholesterol (0.3), and the ratio of total cholesterol to HDL cholesterol (3.4). Prediction models that incorporated markers of inflammation in addition to lipids were significantly better at predicting risk than models based on lipid levels alone (P<0.001). The levels of hs-CRP and serum amyloid A were significant predictors of risk even in the subgroup of women with LDL cholesterol levels below 130 mg per deciliter (3.4 mmol per liter), the target for primary prevention established by the National Cholesterol Education Program. In multivariate analyses, the only plasma markers that independently predicted risk were hs-CRP (relative risk for the highest as compared with the lowest quartile, 1.5; 95 percent confidence interval, 1.1 to 2.1) and the ratio of total cholesterol to HDL cholesterol (relative risk, 1.4; 95 percent confidence interval, 1.1 to 1.9). CONCLUSIONS: The addition of the measurement of C-reactive protein to screening based on lipid levels may provide an improved method of identifying persons at risk for cardiovascular events.
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“Fluvastatin, pravastatin, pitavastatin, and rosuvastatin are metabolized through different CYP enzymes than the others and have less potential for interaction [507].”
From 2019 ESC/EAS guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk (2019) · cites this paper as [507]
In the citing paper
“IL-6 and IL-1 contribute to atherosclerosis and should be considered to be therapeutic targets”
From Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty (2018) · cites this paper as [158]
In the citing paper
“longitudinal studies demonstrate that high blood levels of pro-inflammatory markers, including high-sensitivity CRP assay and IL-6, predict the risk of cardiovascular disease in both middle-aged and older adults, independent of other CVD risk factors”
From Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty (2018) · cites this paper as [158]
In the citing paper
“Elevated CRP has been significantly associated with inflammation and is a high risk factor of CVD.”
From Berries: emerging impact on cardiovascular health (2010) · cites this paper as [30]
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Metadata
- Authors
- Ridker, P. M., Hennekens, C. H., Buring, J. E., & Rifai, N.
- Affiliations
- Brigham and Women's Hospital (US)
- Boston Children's Hospital (US)
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2000-03-23
- Volume
- 342
- Issue
- 12
- Pages
- 836-843
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2058610272
- Cited by
- 5,850
- References
- 30
- Citations by year
- 2026: 97 · 2025: 120 · 2024: 113 · 2023: 125 · 2022: 148 · 2021: 143 · 2020: 165 · 2019: 140 · 2018: 167 · 2017: 131 · 2016: 169 · 2015: 199 · 2014: 223 · 2013: 234 · 2012: 258
- FWCI
- 286.27
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- University Libraries (University of Maryland) (submittedVersion)
- Digital Repository at the University of Maryland (University of Maryland College Park)
- Funders
- National Institutes of Health (5r01hl043851-10)
- National Heart, Lung, and Blood Institute (R01HL058755, HL43851, HL-58755)
- National Cancer Institute (CA-47988, R01CA047988)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Keywords
- C-reactive protein, inflammatory markers, cardiovascular risk prediction, postmenopausal women, serum amyloid A, interleukin-6, sICAM-1, homocysteine, apolipoprotein B-100, LDL cholesterol, coronary artery disease, myocardial infarction, stroke, coronary revascularization, risk prediction model
- MeSH terms
- Serum Amyloid A Protein, Analysis of Variance, Apolipoproteins, C-Reactive Protein, Cardiovascular Diseases, Female, Homocysteine, Humans, Lipids, Middle Aged, Prospective Studies, Protein Precursors, Risk, Biomarkers, Interleukin-6, Case-Control Studies, Intercellular Adhesion Molecule-1
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 ›
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