Literature DB >> 21450664

Prediction of coronary heart disease risk by Framingham and SCORE risk assessments varies by socioeconomic position: results from a study in British men.

Sheena E Ramsay1, Richard W Morris, Peter H Whincup, A Olia Papacosta, Mary C Thomas, S Goya Wannamethee.   

Abstract

AIM: Evidence is limited on performance of the Framingham risk score (FRS) in different socioeconomic groups; similar limitations apply to the Systematic Coronary Risk Evaluation (SCORE). We examined the performance of coronary risk prediction systems in different socioeconomic groups in British men. METHODS AND
RESULTS: In a socially and geographically representative cohort of British men aged 40-59 between 1978 and 1980, predicted 10-year coronary heart disease (CHD) (fatal and non-fatal) risk was calculated using FRS, and CHD mortality using SCORE. Prevalent cardiovascular disease cases were excluded. Occupational social class ranged from I (professionals) to V (unskilled workers), and was summarized as non-manual (I, II, III non-manual) and manual (III manual, IV, V). Both FRS and SCORE over-estimated 10-year CHD risk; over-prediction by both was particularly marked in high social classes. With FRS, predicted/observed risk fell progressively from 2.30 in social class I to 1.19 in social class V. Sensitivity of FRS at a ≥20% threshold (27% of men) fell from 53% to 37% from social class I to V; specificity varied similarly. With SCORE, predicted/observed CHD mortality fell from 1.53 to 1.26 from social class I to V; sensitivity at a ≥5% threshold (29% of men) fell between non-manual (61%) and manual (57%) groups, as did specificity. However, including social class in FRS barely improved risk prediction (net reclassification improvement = 0.18%).
CONCLUSIONS: Framingham and SCORE predictions varied between socioeconomic groups and are more likely to identify those at greater CHD risk in higher socioeconomic groups. To ensure equitable primary prevention, strategies to adequately estimate risk in lower socioeconomic groups (at increased CHD risk) should be developed.

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Year:  2011        PMID: 21450664     DOI: 10.1177/1741826710389394

Source DB:  PubMed          Journal:  Eur J Cardiovasc Prev Rehabil        ISSN: 1741-8267


  11 in total

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Journal:  Circulation       Date:  2022-06-24       Impact factor: 39.918

2.  Recalibration of the SCORE risk chart for the Russian population.

Authors:  Dmitri A Jdanov; Alexander D Deev; Domantas Jasilionis; Svetlana A Shalnova; Maria A Shkolnikova; Vladimir M Shkolnikov
Journal:  Eur J Epidemiol       Date:  2014-09-02       Impact factor: 8.082

3.  The use of machine learning for the identification of peripheral artery disease and future mortality risk.

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4.  Associations of socioeconomic and psychosocial factors with urinary measures of cortisol and catecholamines in the Multi-Ethnic Study of Atherosclerosis (MESA).

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5.  Predictors of the quality of cardiovascular prevention--a multilevel cross-sectional study.

Authors:  Davorina Petek; Anuska Ferligoj; Rok Platinovsek; Janko Kersnik
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6.  Are there any differences in education levels and changes of cardiovascular risk factors among urban and rural population: Isfahan Healthy Heart Program.

Authors:  Mojgan Gharipour; Ahmad Bahonar; Nizal Sarrafzadegan; Alireza Khosravi; Arsalan Khaledifar
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7.  Does inclusion of education and marital status improve SCORE performance in central and eastern europe and former soviet union? findings from MONICA and HAPIEE cohorts.

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Journal:  PLoS One       Date:  2014-04-08       Impact factor: 3.240

8.  Performance of the Atherosclerotic Cardiovascular Disease Pooled Cohort Risk Equations by Social Deprivation Status.

Authors:  Lisandro D Colantonio; Joshua S Richman; April P Carson; Donald M Lloyd-Jones; George Howard; Luqin Deng; Virginia J Howard; Monika M Safford; Paul Muntner; David C Goff
Journal:  J Am Heart Assoc       Date:  2017-03-17       Impact factor: 5.501

9.  Inequality in mortality by occupation related to economic crisis from 1980 to 2010 among working-age Japanese males.

Authors:  Koji Wada; Stuart Gilmour
Journal:  Sci Rep       Date:  2016-03-03       Impact factor: 4.379

10.  Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study.

Authors:  Taavi Tillmann; Kristi Läll; Oliver Dukes; Giovanni Veronesi; Hynek Pikhart; Anne Peasey; Ruzena Kubinova; Magdalena Kozela; Andrzej Pajak; Yuri Nikitin; Sofia Malyutina; Andres Metspalu; Tõnu Esko; Krista Fischer; Mika Kivimäki; Martin Bobak
Journal:  Eur Heart J       Date:  2020-09-14       Impact factor: 29.983

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