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Activity Number: 350
Type: Contributed
Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #307982
Title: A Joint Survival-Longitudinal Modelling Approach for the Dynamic Prediction of Rehospitalization in Telemonitored Chronic Heart Failure Patients
Author(s): Edmund Njeru Njagi*+ and Dimitris Rizopoulos and Geert Molenberghs and Paul Dendale and Koen Willekens
Companies: I-Biostat, Hasselt University, Belgium and Erasmus MC and Universiteit Hasselt & Katholieke Universiteit Leuven and Jessa Hospital, Heart Centre Hasselt, Belgium and Katholieke Universiteit Leuven, Faculty of Medicine, Belgium
Keywords: Area under the receiver operating characteristic curve (AUC) ; Dynamic discriminative index ; Dynamic prediction ; Joint modelling
Abstract:

Telemonitoring in chronic heart failure involves remote monitoring, by clinicians, daily patient measurements of biomarkers such as blood pressure and heart rate. As a strategy in heart failure management, the aim to use these measurements to predict rehospitalization, so that intervention decisions can be made. This is important since heart failure patients have a very high rehospitalization rate. We present a dynamic prediction approach, based on calculating dynamically-updated patient-specific conditional survival probabilities, and their confidence intervals, from a joint model for the time-to-rehospitalization and the time-varying and possibly error-contaminated biomarker. We quantify the ability of the biomarker to discriminate between patients who are and those who are not going to get rehospitalized within a given time window of interest. This approach does not only provide a sound statistical modelling approach to the substantive problem, a problem which to the best of our knowledge has not previously been addressed using a statistical modelling approach, it provides clinicians with a valuable additional tool on which to base their intervention decisions.


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