Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment

Research output: Contribution to journalArticle

58 Citations (Scopus)

Abstract

Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES. Methods We assessed the effect of measures of SES (b12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index. Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7% and 3.9%, respectively, compared with observed risks of 3.2% and 5.6%. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1% and 5.2% for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1% of low-SES participants (95% CI 13.9-29.4%). Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.

Original languageEnglish (US)
Pages (from-to)988-994
Number of pages7
JournalAmerican Heart Journal
Volume157
Issue number6
DOIs
StatePublished - Jun 2009

Fingerprint

Social Class
Coronary Disease
Calibration
Nutrition Surveys
Atherosclerosis
Education

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment. / Fiscella, Kevin; Tancredi, Daniel J; Franks, Peter.

In: American Heart Journal, Vol. 157, No. 6, 06.2009, p. 988-994.

Research output: Contribution to journalArticle

@article{19349dd84dfb499b87e001bed751a170,
title = "Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment",
abstract = "Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES. Methods We assessed the effect of measures of SES (b12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index. Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7{\%} and 3.9{\%}, respectively, compared with observed risks of 3.2{\%} and 5.6{\%}. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1{\%} and 5.2{\%} for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1{\%} of low-SES participants (95{\%} CI 13.9-29.4{\%}). Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.",
author = "Kevin Fiscella and Tancredi, {Daniel J} and Peter Franks",
year = "2009",
month = "6",
doi = "10.1016/j.ahj.2009.03.019",
language = "English (US)",
volume = "157",
pages = "988--994",
journal = "American Heart Journal",
issn = "0002-8703",
publisher = "Mosby Inc.",
number = "6",

}

TY - JOUR

T1 - Adding socioeconomic status to Framingham scoring to reduce disparities in coronary risk assessment

AU - Fiscella, Kevin

AU - Tancredi, Daniel J

AU - Franks, Peter

PY - 2009/6

Y1 - 2009/6

N2 - Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES. Methods We assessed the effect of measures of SES (b12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index. Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7% and 3.9%, respectively, compared with observed risks of 3.2% and 5.6%. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1% and 5.2% for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1% of low-SES participants (95% CI 13.9-29.4%). Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.

AB - Background The purpose of the study was to examine the potential of adding socioeconomic status (SES) to Framingham Risk Scoring (FRS) to improve coronary heart disease (CHD) prediction by SES. Methods We assessed the effect of measures of SES (b12 years of education or low income) on model discrimination and calibration when added to FRS in a prospective cohort, Atherosclerosis Risk in Communities. We validated use of this model in a second cohort, the National Health and Nutritional Examination Survey linked to the National Death Index. Results Based on FRS alone, persons of higher and lower SES had a predicted CHD risk of 3.7% and 3.9%, respectively, compared with observed risks of 3.2% and 5.6%. Adding SES to a model with FRS improved calibration with predicted risk estimates of 3.1% and 5.2% for those with higher and lower SES, mitigating the discrepancy between predicted and observed CHD events for low-SES persons. Model discrimination (area under the receiver operator curve) was not significantly affected, and consistent findings were observed in the validation sample. Inclusion of SES in the model resulted in upgrading of risk classification for 15.1% of low-SES participants (95% CI 13.9-29.4%). Conclusions Standard FRS underestimates CHD risk for those at low SES; treatment decisions ignoring SES may exacerbate SES disparities. Adding SES to CHD risk assessment reduces this bias.

UR - http://www.scopus.com/inward/record.url?scp=67049132400&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=67049132400&partnerID=8YFLogxK

U2 - 10.1016/j.ahj.2009.03.019

DO - 10.1016/j.ahj.2009.03.019

M3 - Article

C2 - 19464408

AN - SCOPUS:67049132400

VL - 157

SP - 988

EP - 994

JO - American Heart Journal

JF - American Heart Journal

SN - 0002-8703

IS - 6

ER -