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 language | English (US) |
|---|---|
| Pages (from-to) | 988-994 |
| Number of pages | 7 |
| Journal | American Heart Journal |
| Volume | 157 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2009 |
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ASJC Scopus subject areas
- Cardiology and Cardiovascular Medicine
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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 journal › Article
}
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.
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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 -