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PMID: 18997194 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men.

Circulation ·Vol. 118 ·No. 22 ·2008-11-25 ·Pages 2243-51, 4p following 2251

Ridker PM, Paynter NP, Rifai N, Gaziano JM, Cook NR

Abstract

High-sensitivity C-reactive protein and family history are independently associated with future cardiovascular events and have been incorporated into risk prediction models for women (the Reynolds Risk Score for women); however, no cardiovascular risk prediction algorithm incorporating these variables currently exists for men. Among 10 724 initially healthy American nondiabetic men who were followed up prospectively over a median period of 10.8 years, we compared the test characteristics of global model fit, discrimination, calibration, and reclassification in 2 prediction models for incident cardiovascular events, one based on age, blood pressure, smoking status, total cholesterol, and high-density lipoprotein cholesterol (traditional model) and the other based on these risk factors plus high-sensitivity C-reactive protein and parental history of myocardial infarction before age 60 years (Reynolds Risk Score for men). A total of 1294 cardiovascular events accrued during study follow-up. Compared with the traditional model, the Reynolds Risk Score had better global fit (likelihood ratio test P<0.001), a superior (lower) Bayes information criterion, and a larger C-index (P<0.001). For the end point of all cardiovascular events, the Reynolds Risk Score for men reclassified 17.8% (1904/10 724) of the study population (and 20.2% [1392/6884] of those at 5% to 20% 10-year risk) into higher- or lower-risk categories, with markedly improved accuracy among those reclassified. For this model comparison, the net reclassification index was 5.3%, and the clinical net reclassification index was 14.2% (both P<0.001). In models based on the Adult Treatment Panel III preferred end point of coronary heart disease and limited to men not taking lipid-lowering therapy, 16.7% of the study population (and 20.1% of those at 5% to 20% 10-year risk) were reclassified to higher- or lower-risk groups, again with significantly improved global fit, larger C-index (P<0.001), and markedly improved accuracy among those reclassified. For this model, the net reclassification index was 8.4% and the clinical net reclassification index was 15.8% (both P<0.001). As previously shown in women, a prediction model in men that incorporates high-sensitivity C-reactive protein and parental history significantly improves global cardiovascular risk prediction.

MeSH Terms
Biomarkers/blood C-Reactive Protein/metabolism Cardiovascular Diseases/blood,epidemiology,genetics Female Follow-Up Studies Humans Inflammation/blood,physiopathology Life Style Likelihood Functions Male Predictive Value of Tests Prospective Studies Risk Assessment Sex Characteristics
Chemicals
Biomarkers C-Reactive Protein
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Ridker Paul M
Donald W. Reynolds Center for Cardiovascular Research, Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA. pridker@partners.org
Paynter Nina P
Rifai Nader
Gaziano J Michael
Cook Nancy R
References (18)
18 references, click to expand
  1. Canadian Cardiovascular Society position statement--recommendations for the diagnosis and treatment of dyslipidemia and prevention of cardiovascular disease.
    Can J Cardiol. 2006 Sep;22(11):913-27 PMID: 16971976
  2. The effect of including C-reactive protein in cardiovascular risk prediction models for women.
    Ann Intern Med. 2006 Jul 4;145(1):21-9 PMID: 16818925
  3. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score.
    JAMA. 2007 Feb 14;297(6):611-9 PMID: 17299196
  4. Use and misuse of the receiver operating characteristic curve in risk prediction.
    Circulation. 2007 Feb 20;115(7):928-35 PMID: 17309939
  5. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.
    BMJ. 2007 Jul 21;335(7611):136 PMID: 17615182
  6. Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve.
    Clin Chem. 2008 Jan;54(1):17-23 PMID: 18024533
  7. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.
    Stat Med. 2008 Jan 30;27(2):157-72; discussion 207-12 PMID: 17569110
  8. General cardiovascular risk profile for use in primary care: the Framingham Heart Study.
    Circulation. 2008 Feb 12;117(6):743-53 PMID: 18212285
  9. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes.
    N Engl J Med. 2008 May 15;358(20):2107-16 PMID: 18480203
  10. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC).
    Heart. 2007 Feb;93(2):172-6 PMID: 17090561
  11. Design of Physicians' Health Study II--a randomized trial of beta-carotene, vitamins E and C, and multivitamins, in prevention of cancer, cardiovascular disease, and eye disease, and review of results of completed trials.
    Ann Epidemiol. 2000 Feb;10(2):125-34 PMID: 10691066
  12. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III).
    JAMA. 2001 May 16;285(19):2486-97 PMID: 11368702
  13. Development of predictive models for long-term cardiovascular risk associated with systolic and diastolic blood pressure.
    Hypertension. 2002 Jan;39(1):105-10 PMID: 11799087
  14. Rosuvastatin in the primary prevention of cardiovascular disease among patients with low levels of low-density lipoprotein cholesterol and elevated high-sensitivity C-reactive protein: rationale and design of the JUPITER trial.
    Circulation. 2003 Nov 11;108(19):2292-7 PMID: 14609996
  15. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines.
    Circulation. 2004 Jul 13;110(2):227-39 PMID: 15249516
  16. A prospective study of nutritional factors and hypertension among US men.
    Circulation. 1992 Nov;86(5):1475-84 PMID: 1330360
  17. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.
    Stat Med. 1996 Feb 28;15(4):361-87 PMID: 8668867
  18. Prevention of coronary heart disease in clinical practice: recommendations of the Second Joint Task Force of European and other Societies on Coronary Prevention.
    Atherosclerosis. 1998 Oct;140(2):199-270 PMID: 9862269
Article Info
Journal
Circulation
Abbr.
Circulation
ISSN
1524-4539
Published
2008-11-25
Epub
2008-00-09
Pages
2243-51, 4p following 2251
Language
English
Region
United States
NLM ID
0147763
PMCID
PMC2752381
Subset
IM
Grants
NCI NIH HHS · R01 CA097193-01 · United States
NCI NIH HHS · R01 CA097193-02 · United States
NCI NIH HHS · R01 CA097193-08 · United States
NCI NIH HHS · R01 CA097193-03 · United States
NCI NIH HHS · R01 CA097193-07 · United States
NCI NIH HHS · R01 CA097193-04 · United States
NCI NIH HHS · R01 CA097193-06A1 · United States
NCI NIH HHS · R01 CA097193 · United States
NCI NIH HHS · R01 CA097193-05 · United States
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