Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods

Harnessing repeated measurements of predictor variables for clinical risk prediction: a review of existing methods

Abstract Background Clinical prediction models (CPMs) predict the risk of health outcomes for individual patients. The majority of existing CPMs only harness cross-sectional patient information. Incorporating repeated measurements, such as those stored in electronic health records, into CPMs may pro...

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Bibliographic Details
Main Authors: Lucy M. Bull, Mark Lunt, Glen P. Martin, Kimme Hyrich, Jamie C. Sergeant
Format: Article
Language:English
Published: BMC 2020-07-01
Series:Diagnostic and Prognostic Research
Subjects:
Longitudinal data
Clinical risk prediction
Dynamic prediction
Prediction models
Survival analysis
Repeated observations
Online Access:http://link.springer.com/article/10.1186/s41512-020-00078-z

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http://link.springer.com/article/10.1186/s41512-020-00078-z

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