Literature DB >> 18930961

Critical appraisal of CRP measurement for the prediction of coronary heart disease events: new data and systematic review of 31 prospective cohorts.

Tina Shah1, Juan P Casas, Jackie A Cooper, Ioanna Tzoulaki, Reecha Sofat, Valerie McCormack, Liam Smeeth, John E Deanfield, Gordon D Lowe, Ann Rumley, F Gerald R Fowkes, Steve E Humphries, Aroon D Hingorani.   

Abstract

BACKGROUND: Non-uniform reporting of relevant relationships and metrics hampers critical appraisal of the clinical utility of C-reactive protein (CRP) measurement for prediction of later coronary events.
METHODS: We evaluated the predictive performance of CRP in the Northwick Park Heart Study (NPHS-II) and the Edinburgh Artery Study (EAS) comparing discrimination by area under the ROC curve (AUC), calibration and reclassification. We set the findings in the context of a systematic review of published studies comparing different available and imputed measures of prediction. Risk estimates per-quantile of CRP were pooled using a random effects model to infer the shape of the CRP-coronary event relationship.
RESULTS: NPHS-II and EAS (3441 individuals, 309 coronary events): CRP alone provided modest discrimination for coronary heart disease (AUC 0.61 and 0.62 in NPHS-II and EAS, respectively) and only modest improvement in the discrimination of a Framingham-based risk score (FRS) (increment in AUC 0.04 and -0.01, respectively). Risk models based on FRS alone and FRS + CRP were both well calibrated and the net reclassification improvement (NRI) was 8.5% in NPHS-II and 8.8% in EAS with four risk categories, falling to 4.9% and 3.0% for 10-year coronary disease risk threshold of 15%. Systematic review (31 prospective studies 84 063 individuals, 11 252 coronary events): pooled inferred values for the AUC for CRP alone were 0.59 (0.57, 0.61), 0.59 (0.57, 0.61) and 0.57 (0.54, 0.61) for studies of <5, 5-10 and >10 years follow up, respectively. Evidence from 13 studies (7201 cases) indicated that CRP did not consistently improve performance of the Framingham risk score when assessed by discrimination, with AUC increments in the range 0-0.15. Evidence from six studies (2430 cases) showed that CRP provided statistically significant but quantitatively small improvement in calibration of models based on established risk factors in some but not all studies. The wide overlap of CRP values among people who later suffered events and those who did not appeared to be explained by the consistently log-normal distribution of CRP and a graded continuous increment in coronary risk across the whole range of values without a threshold, such that a large proportion of events occurred among the many individuals with near average levels of CRP.
CONCLUSIONS: CRP does not perform better than the Framingham risk equation for discrimination. The improvement in risk stratification or reclassification from addition of CRP to models based on established risk factors is small and inconsistent. Guidance on the clinical use of CRP measurement in the prediction of coronary events may require updating in light of this large comparative analysis.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18930961      PMCID: PMC2639366          DOI: 10.1093/ije/dyn217

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


  37 in total

1.  C-reactive protein and cardiovascular disease risk: still an unknown quantity?

Authors:  George Davey Smith; Nic Timpson; Debbie A Lawlor
Journal:  Ann Intern Med       Date:  2006-07-04       Impact factor: 25.391

2.  The efficacy of combining several risk factors as a screening test.

Authors:  Nicholas J Wald; Joan K Morris; Simon Rish
Journal:  J Med Screen       Date:  2005       Impact factor: 2.136

3.  Biomarkers for prediction of cardiovascular events.

Authors:  Kiran Musunuru; Roger S Blumenthal
Journal:  N Engl J Med       Date:  2007-04-05       Impact factor: 91.245

4.  Biomarkers for prediction of cardiovascular events.

Authors:  Paul M Ridker; Nancy R Cook
Journal:  N Engl J Med       Date:  2007-04-05       Impact factor: 91.245

5.  The effect of including C-reactive protein in cardiovascular risk prediction models for women.

Authors:  Nancy R Cook; Julie E Buring; Paul M Ridker
Journal:  Ann Intern Med       Date:  2006-07-04       Impact factor: 25.391

6.  Inflammatory, haemostatic, and rheological markers for incident peripheral arterial disease: Edinburgh Artery Study.

Authors:  Ioanna Tzoulaki; Gordon D Murray; Amanda J Lee; Ann Rumley; Gordon D O Lowe; F Gerald R Fowkes
Journal:  Eur Heart J       Date:  2007-01-09       Impact factor: 29.983

7.  Multiple biomarkers for the prediction of first major cardiovascular events and death.

Authors:  Thomas J Wang; Philimon Gona; Martin G Larson; Geoffrey H Tofler; Daniel Levy; Christopher Newton-Cheh; Paul F Jacques; Nader Rifai; Jacob Selhub; Sander J Robins; Emelia J Benjamin; Ralph B D'Agostino; Ramachandran S Vasan
Journal:  N Engl J Med       Date:  2006-12-21       Impact factor: 91.245

8.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

Review 9.  C-reactive protein comes of age.

Authors:  Subodh Verma; Paul E Szmitko; Paul M Ridker
Journal:  Nat Clin Pract Cardiovasc Med       Date:  2005-01

10.  Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score.

Authors:  Paul M Ridker; Julie E Buring; Nader Rifai; Nancy R Cook
Journal:  JAMA       Date:  2007-02-14       Impact factor: 56.272

View more
  65 in total

Review 1.  Clinical usefulness of novel prognostic biomarkers in patients on hemodialysis.

Authors:  Alberto Ortiz; Ziad A Massy; Danilo Fliser; Bengt Lindholm; Andrzej Wiecek; Alberto Martínez-Castelao; Adrian Covic; David Goldsmith; Gültekin Süleymanlar; Gérard M London; Carmine Zoccali
Journal:  Nat Rev Nephrol       Date:  2011-11-01       Impact factor: 28.314

2.  Drug therapies for the primary prevention of cardiovascular events: trials and errors: 2009 Ancel Keys Memorial Lecture.

Authors:  Bruce M Psaty
Journal:  Circulation       Date:  2010-02-23       Impact factor: 29.690

3.  Commentary: C-reactive protein and risk prediction--moving beyond associations to assessing predictive utility and clinical usefulness.

Authors:  Ramachandran S Vasan
Journal:  Int J Epidemiol       Date:  2009-01-07       Impact factor: 7.196

4.  Which risk engines are best to assess CVD risk in diabetes?

Authors:  Parinya Chamnan; Rebecca K Simmons; Simon J Griffin
Journal:  Nat Rev Endocrinol       Date:  2010-02       Impact factor: 43.330

Review 5.  The role of C-reactive protein as a risk predictor of coronary atherosclerosis: implications from the JUPITER trial.

Authors:  Thura T Abd; Danny J Eapen; Ambareesh Bajpai; Abhinav Goyal; Allen Dollar; Laurence Sperling
Journal:  Curr Atheroscler Rep       Date:  2011-04       Impact factor: 5.113

Review 6.  Can haemostatic factors predict atherothrombosis?

Authors:  Gordon Lowe
Journal:  Intern Emerg Med       Date:  2011-02-15       Impact factor: 3.397

7.  The SHAPE guideline: ahead of its time or just in time?

Authors:  Erling Falk; Prediman K Shah
Journal:  Curr Atheroscler Rep       Date:  2011-10       Impact factor: 5.113

8.  A prospective study of inflammation markers and endometrial cancer risk in postmenopausal hormone nonusers.

Authors:  Tao Wang; Thomas E Rohan; Marc J Gunter; Xiaonan Xue; Jean Wactawski-Wende; Swapnil N Rajpathak; Mary Cushman; Howard D Strickler; Robert C Kaplan; Sylvia Wassertheil-Smoller; Philipp E Scherer; Gloria Y F Ho
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-03-17       Impact factor: 4.254

9.  C-reactive protein and substance use disorders in adolescence and early adulthood: a prospective analysis.

Authors:  E Jane Costello; William E Copeland; Lilly Shanahan; Carol M Worthman; Adrian Angold
Journal:  Drug Alcohol Depend       Date:  2013-09-10       Impact factor: 4.492

10.  Human C-reactive protein does not promote atherosclerosis in transgenic rabbits.

Authors:  Tomonari Koike; Shuji Kitajima; Ying Yu; Kazutoshi Nishijima; Jifeng Zhang; Yukio Ozaki; Masatoshi Morimoto; Teruo Watanabe; Sucharit Bhakdi; Yujiro Asada; Y Eugene Chen; Jianglin Fan
Journal:  Circulation       Date:  2009-11-09       Impact factor: 29.690

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.