Document Information Content Entity Continuant Continuant Abstract Entity Entity Generically Dependent Continuant 2025-06-25T13:54:41 RDF description of Multi-marker prediction of coronary heart disease risk: the Women’s Health Initiative [abstract] - http://repository.healthpartners.com/individual/document-rn34080 2023-09-30T20:36:00.593-05:00 public Biomarkers document-rn34080 120 <p>Context: The utility of newer biomarkers remains uncertain when added to predictive models using only traditional risk factors for coronary heart disease (CHD) risk assessment. <br>Objective: To investigate whether multiple biomarkers contribute to improved CHD risk prediction in postmenopausal women compared to assessment with traditional risk factors only. <br>Design, Setting, Participants: The Women’s Health Initiative Hormone Trials (WHI-HT) enrolled 27,347 postmenopausal women aged 50 �79. Associations of traditional risk factors and 18 newer biomarkers were assessed in a nested case-control study including 321 CHD cases and 743 controls. We compared four prediction equations for 5-year CHD risk: Framingham Risk Score (FRS) models with original and newly-estimated coefficients; traditional risk factor (TRF) model which included statin treatment, hormone treatment, and previous cardiovascular disease history as well as the FRS covariates; additional biomarker (ABM) model which additionally included interleukin-6, D-dimer, coagulation Factor VIII, von Willebrand factor, and homocysteine (significant associations after adjusting for other variables). <br>Main Outcome Measures: Nonfatal myocardial infarction, CHD death, and incident silent myocardial infarction. Statistical evaluation included measures of accuracy, discrimination, and reclassification. <br>Results: The TRF model showed improved C-statistic (0.729 vs. 0.699, p= 0.001), significant integrated discrimination improvement (IDI, 0.011, p<0.001) and net reclassification improvement (NRI, 15.6%) when compared to the model with FRS covariates only. The ABM model showed improved discrimination (C-statistic=0.751, p=0.001; IDI=0.016, p<0.001) and reclassification (NRI=15.6%) compared to the TRF model. Predicted CHD risks in a continuous scale showed a high agreement between TRF and ABM models (Cronbach’s = 0. 899). Among newer factors, C-reactive protein level did not significantly improve CHD prediction either alone or in combination with other biomarkers. <br>Conclusion: We found very modest improvement in CHD risk prediction when a group of 18 newer biomarkers were added to predictive models using traditional risk factors in postmenopausal women.<p> Randomized Controlled Trials 21652 37184 Circulation Risk Factors abstract Heart Diseases Multi-marker prediction of coronary heart disease risk: the Women’s Health Initiative [abstract] Forecasting Models 18 Suppl Cardiovascular Diseases