In this thesis we aimed to improve the prediction of clinical outcomes in cardiovascular diseases (CVD) in several ways. Motivated by an increasing attention for CVD in women, we made an overview of all available prediction models for CVD in women and investigated how well they performed.
Secondly we focused on dynamic models, that use changes in the status of the patient to get better estimates of the risk of clinical outcomes.

Additional Metadata
Keywords Prediction, Cardiovascular diseases, Dynamic Models, Women, Joint Models, Relative Survival
Promotor H. Boersma (Eric) , D. Rizopoulos (Dimitris) , I. Kardys (Isabella)
Publisher Erasmus University Rotterdam
Sponsor The research described in this thesis was supported by a grant of the Dutch Heart Foundation (2013T083)
ISBN 978-94-6323-804-5
Persistent URL hdl.handle.net/1765/119913
Note For copyright reasons there is a partial embargo for this dissertation
Citation
Baart, S.J. (2019, October 8). Predicting Clinical Outcomes in Cardiovascular Diseases : methodological advancements and applications. Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/119913