Literature DB >> 15659467

Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation.

Marco Ferrario1, Paolo Chiodini, Lloyd E Chambless, Giancarlo Cesana, Diego Vanuzzo, Salvatore Panico, Roberto Sega, Lorenza Pilotto, Luigi Palmieri, Simona Giampaoli.   

Abstract

BACKGROUND: The aims of this paper are to derive a 10-year coronary risk predictive equation for adult Italian men, and to assess its accuracy in comparison with the Framingham Heart Study (FHS) and PROCAM study equations.
METHODS: The CUORE study is a prospective fixed-cohort study. Eleven cohorts, from the north and the centre-south of Italy, had been investigated at baseline between 1982 and 1996, adopting MONICA methods to measure risk factors. Among this sample of 6865 men, aged 35-69 years and free of coronary heart disease (CHD) at baseline, 312 first fatal and non-fatal major coronary events occurred in 9.1 years median follow-up. Calibration, as the difference between 10-year predicted and actual risk, and discrimination, as the ability of the risk functions to separate high-risk from low-risk subjects, have been assessed to compare accuracy of the FHS, the PROCAM, and the CUORE study equations.
RESULTS: The best CUORE equation includes age, total cholesterol, systolic blood pressure, cigarette smoking, HDL-cholesterol, diabetes mellitus, hypertension drug treatment, and family history of CHD (area under the ROC curve = 0.75). The uncalibrated estimates of the 10-year risk in this CUORE follow-up data were 0.093 and 0.109 higher (P < 0.05) from the Framingham and PROCAM risk scores, respectively, than the Kaplan-Meier estimate for CUORE, indicating risk overestimates for both equations. Standard recalibration techniques improved accuracy of the FHS equation only. PROCAM overestimates were prominent in the higher risk deciles. With an alternative method for recalibration better risk estimates were obtained, but a cohort study was needed to obtain a properly calibrated risk equation.
CONCLUSIONS: The CUORE Project predictive equation showed better accuracy of the FHS and PROCAM equations, overcoming frequently reported risk overestimates. The CUORE equation may be adopted to identify men with high coronary risk in Italy.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15659467     DOI: 10.1093/ije/dyh405

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


  54 in total

1.  Impact of seropositivity to Chlamydia pneumoniae and anti-hHSP60 on cardiovascular events in hemodialysis patients.

Authors:  Pasquale Esposito; Carmine Tinelli; Carmelo Libetta; Elisa Gabanti; Teresa Rampino; Antonio Dal Canton
Journal:  Cell Stress Chaperones       Date:  2010-10-05       Impact factor: 3.667

Review 2.  The epidemiological concept of residual risk.

Authors:  Diego Vanuzzo
Journal:  Intern Emerg Med       Date:  2011-10       Impact factor: 3.397

3.  Can we learn more about the etiology of cardiovascular disease?

Authors:  Lewis H Kuller
Journal:  Eur J Epidemiol       Date:  2007-02-28       Impact factor: 8.082

4.  Can non-physician health-care workers assess and manage cardiovascular risk in primary care?

Authors:  Dele O Abegunde; Bakuti Shengelia; Anne Luyten; Alexandra Cameron; Francesca Celletti; Sania Nishtar; Vasu Pandurangi; Shanthi Mendis
Journal:  Bull World Health Organ       Date:  2007-06       Impact factor: 9.408

5.  The relative merits of population-based and targeted prevention strategies.

Authors:  Donna M Zulman; Sandeep Vijan; Gilbert S Omenn; Rodney A Hayward
Journal:  Milbank Q       Date:  2008-12       Impact factor: 4.911

6.  Development of appropriate coronary heart disease risk prediction models in HIV-infected patients.

Authors:  Morris Schambelan; Peter W F Wilson; Kevin E Yarasheski; W Todd Cade; Victor G Dávila-Román; Ralph B D'Agostino; Tarek A Helmy; Matthew Law; Kristin E Mondy; Sharon Nachman; Linda R Peterson; Signe W Worm
Journal:  Circulation       Date:  2008-06-19       Impact factor: 29.690

7.  Cardiovascular risk tables.

Authors:  Thierry Christiaens
Journal:  BMJ       Date:  2008-06-23

Review 8.  Cardiovascular risk assessment: a global perspective.

Authors:  Dong Zhao; Jing Liu; Wuxiang Xie; Yue Qi
Journal:  Nat Rev Cardiol       Date:  2015-03-10       Impact factor: 32.419

9.  Screening score for early detection of cardio-metabolic risk in Indian adults.

Authors:  Deepa Pandit-Agrawal; Anuradha Khadilkar; Shashi Chiplonkar; Vaman Khadilkar; Vivek Patwardhan
Journal:  Int J Public Health       Date:  2017-06-21       Impact factor: 3.380

10.  Laboratory-based versus non-laboratory-based method for assessment of cardiovascular disease risk: the NHANES I Follow-up Study cohort.

Authors:  Thomas A Gaziano; Cynthia R Young; Garrett Fitzmaurice; Sidney Atwood; J Michael Gaziano
Journal:  Lancet       Date:  2008-03-15       Impact factor: 79.321

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.