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Nancy R. Cook

Researcher at Brigham and Women's Hospital

Publications -  521
Citations -  74853

Nancy R. Cook is an academic researcher from Brigham and Women's Hospital. The author has contributed to research in topics: Risk factor & Randomized controlled trial. The author has an hindex of 124, co-authored 487 publications receiving 67049 citations. Previous affiliations of Nancy R. Cook include University of Leicester & St. Vincent's Health System.

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Assessing the performance of prediction models: a framework for traditional and novel measures.

TL;DR: It is suggested that reporting discrimination and calibration will always be important for a prediction model and decision-analytic measures should be reported if the predictive model is to be used for clinical decisions.
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Comparison of C-Reactive Protein and Low-Density Lipoprotein Cholesterol Levels in the Prediction of First Cardiovascular Events

TL;DR: The data suggest that the C-reactive protein level is a stronger predictor of cardiovascular events than the LDL cholesterol level and that it adds prognostic information to that conveyed by the Framingham risk score.
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Lack of effect of long-term supplementation with beta carotene on the incidence of malignant neoplasms and cardiovascular disease.

TL;DR: In this trial among healthy men, 12 years of supplementation with beta carotene produced neither benefit nor harm in terms of the incidence of malignant neoplasms, cardiovascular disease, or death from all causes.
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C-Reactive Protein, the Metabolic Syndrome, and Risk of Incident Cardiovascular Events An 8-Year Follow-Up of 14 719 Initially Healthy American Women

TL;DR: These prospective data suggest that measurement of CRP adds clinically important prognostic information to the metabolic syndrome and is associated with increased levels of C-reactive protein (CRP).
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Use and Misuse of the Receiver Operating Characteristic Curve in Risk Prediction

TL;DR: The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories.