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J Am Heart Assoc. 2015 Jul 6;4(7). pii: e001646. doi: 10.1161/JAHA.114.001646.

Traditional Risk Factors Versus Biomarkers for Prediction of Secondary Events in Patients With Stable Coronary Heart Disease: From the Heart and Soul Study.

Author information

1
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.) Cardiology Section, Veterans Affairs Puget Sound Health Care System, Seattle, WA (A.L.B.) Department of Medicine, University of Washington, Seattle, WA (A.L.B.).
2
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.) San Francisco General Hospital, San Francisco, CA (I.A.K., K.B.D., P.G.) Department of Cardiology, Kaiser Permanente Medical Center, San Francisco, CA (I.A.K., M.T.).
3
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.) Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA (K.B.D., M.G.S., E.V., M.A.W.) San Francisco General Hospital, San Francisco, CA (I.A.K., K.B.D., P.G.).
4
Department of Pathology, University of Maryland School of Medicine, Baltimore, MD (R.H.C.).
5
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD (C.R.D.F.).
6
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.) San Francisco General Hospital, San Francisco, CA (I.A.K., K.B.D., P.G.).
7
Nephrology Section, Veterans Affairs San Diego Healthcare System, San Diego, CA (J.H.I.) Division of Nephrology and Hypertension, Department of Medicine, University of California San Diego, San Diego, CA (J.H.I.) Division of Preventive Medicine, Department of Family and Preventive Medicine, University of California San Diego, San Diego, CA (J.H.I.).
8
Department of Preventive Medicine and Bluhm Cardiovascular Institute, Northwestern University Feinberg School of Medicine, Chicago, IL (D.L.J.) Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (D.L.J.).
9
Division of Medicine, Akershus University Hospital and University of Oslo, Lørenskog, Norway (T.O.).
10
TIMI Study Group, Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (M.S.S.) Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (M.S.S., H.S.).
11
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.).
12
Department of Medicine, University of California, San Francisco, San Francisco, CA (A.L.B., I.A.K., K.B.D., P.G., N.B.S., M.G.S., M.A.W.) Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA (K.B.D., M.G.S., E.V., M.A.W.) Section of General Internal Medicine, Veterans Affairs Medical Center, San Francisco, CA (M.G.S., M.A.W.).
13
Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (M.S.S., H.S.).
14
Department of Cardiology, Kaiser Permanente Medical Center, San Francisco, CA (I.A.K., M.T.).
15
Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA (K.B.D., M.G.S., E.V., M.A.W.).

Abstract

BACKGROUND:

Patients with stable coronary heart disease (CHD) have widely varying prognoses and treatment options. Validated models for risk stratification of patients with CHD are needed. We sought to evaluate traditional and novel risk factors as predictors of secondary cardiovascular (CV) events, and to develop a prediction model that could be used to risk stratify patients with stable CHD.

METHODS AND RESULTS:

We used independent derivation (912 participants in the Heart and Soul Study) and validation (2876 participants in the PEACE trial) cohorts of patients with stable CHD to develop a risk prediction model using Cox proportional hazards models. The outcome was CV events, defined as myocardial infarction, stroke, or CV death. The annual rate of CV events was 3.4% in the derivation cohort and 2.2% in the validation cohort. With the exception of smoking, traditional risk factors (including age, sex, body mass index, hypertension, dyslipidemia, and diabetes) did not emerge as the top predictors of secondary CV events. The top 4 predictors of secondary events were the following: N-terminal pro-type brain natriuretic peptide, high-sensitivity cardiac troponin T, urinary albumin:creatinine ratio, and current smoking. The 5-year C-index for this 4-predictor model was 0.73 in the derivation cohort and 0.65 in the validation cohort. As compared with variables in the Framingham secondary events model, the Heart and Soul risk model resulted in net reclassification improvement of 0.47 (95% CI 0.25 to 0.73) in the derivation cohort and 0.18 (95% CI 0.01 to 0.40) in the validation cohort.

CONCLUSIONS:

Novel risk factors are superior to traditional risk factors for predicting 5-year risk of secondary events in patients with stable CHD.

KEYWORDS:

coronary disease; epidemiology; prevention; risk prediction

PMID:
26150476
PMCID:
PMC4608062
DOI:
10.1161/JAHA.114.001646
[Indexed for MEDLINE]
Free PMC Article

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