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Effect of correcting for long-term variation in major coronary heart disease risk factors: relative hazard estimation and risk prediction in the Atherosclerosis Risk in Communities Study.

TitleEffect of correcting for long-term variation in major coronary heart disease risk factors: relative hazard estimation and risk prediction in the Atherosclerosis Risk in Communities Study.
Publication TypeJournal Article
Year of Publication2012
AuthorsPaynter NP, Crainiceanu CM, Sharrett ARichey, Chambless LE
Secondary AuthorsCoresh JJ
JournalAnn Epidemiol
Volume22
Issue3
Pagination191-7
Date Published2012 Mar
ISSN1873-2585
KeywordsAtherosclerosis, Blood Pressure, Cholesterol, Cholesterol, HDL, Female, Humans, Male, Middle Aged, Proportional Hazards Models, Prospective Studies, Regression Analysis, Risk Factors, ROC Curve, United States
Abstract

PURPOSE: To examine the effect of correcting coronary heart disease (CHD) risk factors for long-term within-person variation on CHD risk.

METHODS: By using 5533 men and 7301 women from the Atherosclerosis Risk in Communities (ARIC) study, we compared models incorporating risk factors measured at a single visit and models incorporating additional measurements for systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol taken 3 years before baseline.

RESULTS: The largest change away from null was observed for systolic blood pressure, ie, hazard ratio (HR) 1.38 to 1.69 (+81%) in women and HR 1.26 to 1.41 (+56%) in men. HRs also decreased for age (-32% in women, -9% in men), race (-67% in women), the presence of diabetes (-13% in men and women), and medication use for hypertension (-27% in women, -26% in men) and cholesterol (-97% in women, HR 1.06-0.93 in men). The area under the ROC curve did not improve significantly in men or women, whereas reclassification was only significant in women (net reclassification improvement 5.4%, p = 0.016).

CONCLUSIONS: Modeling long-term variation in CHD risk factors had a substantial impact on HR estimates, with new effect estimates further from the null for some risk factors and closer for others including age and medication use, but only improved risk classification in women.

DOI10.1016/j.annepidem.2011.12.001
Alternate JournalAnn Epidemiol
PubMed ID22221585
PubMed Central IDPMC3288692
Grant ListN01 HC055022 / HC / NHLBI NIH HHS / United States
T32 HL007024-33 / HL / NHLBI NIH HHS / United States
N01-NC-55019 / / PHS HHS / United States
N01-NC-55016 / / PHS HHS / United States
T32 HL007024-31 / HL / NHLBI NIH HHS / United States
T32 HL007024-29 / HL / NHLBI NIH HHS / United States
N01 HC055018 / HC / NHLBI NIH HHS / United States
T32 HL007024 / HL / NHLBI NIH HHS / United States
T32 HL007024-32 / HL / NHLBI NIH HHS / United States
N01-NC-55022 / / PHS HHS / United States
N01 HC055019 / HC / NHLBI NIH HHS / United States
T32 HL007024-28 / HL / NHLBI NIH HHS / United States
N01 HC055015 / HC / NHLBI NIH HHS / United States
N01 HC055021 / HC / NHLBI NIH HHS / United States
N01-NC-55021 / / PHS HHS / United States
N01 HC055020 / HC / NHLBI NIH HHS / United States
T32HL07024 / HL / NHLBI NIH HHS / United States
T32 HL007024-30 / HL / NHLBI NIH HHS / United States
N01-NC-55018 / / PHS HHS / United States
N01-NC-55020 / / PHS HHS / United States
N01 HC055016 / HC / NHLBI NIH HHS / United States
N01-NC-55015 / / PHS HHS / United States