Evaluating the Prognostic Value of New Cardiovascular Biomarkers
Author(s) -
Angela Wood,
Philip Greenland
Publication year - 2009
Publication title -
disease markers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 66
eISSN - 1875-8630
pISSN - 0278-0240
DOI - 10.1155/2009/412947
Subject(s) - context (archaeology) , predictive value , medicine , modalities , intensive care medicine , predictive modelling , clinical practice , risk assessment , biomarker , test (biology) , risk analysis (engineering) , computer science , machine learning , physical therapy , paleontology , social science , biochemistry , chemistry , computer security , sociology , biology
New predictors of cardiovascular outcomes are widely sought in research settings, and predictive tests are commonly recommended for routine use in cardiovascular clinical care. A number of multivariable scoring systems are in use around the world for assessment of a patient’s risk. While such scoring systems are often recommended for clinical use in medical practice guidelines, their actual use in medical care falls short of recommendations. Limitations in the predictive capacity of existing predictive models are recognized, including lack of predictive accuracy, lack of ability to separate those who develop events from those who do not, and risks and costs of the testing modalities. Biomarker research is actively developing new testing strategies trying to improve upon current approaches, but it is often unclear how to assess the incremental prognostic information that a new test provides. In this report, we discuss the statistical approaches that can be used to evaluate additive predictive value of new tests. We also consider clinical research examples to put this information into a practical context.
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