Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16470
Title: A joint survival-longitudinal modelling approach for the dynamic prediction of rehospitalization in telemonitored chronic heart failure patients.
Authors: Njagi, Edmund Njeru 
Rizopoulos, Dimitri
Molenberghs, Geert 
Dendale, Paul 
Willekens, Koen
Issue Date: 2013
Source: Statistical modelling, 13 (3), p. 179-198
Abstract: Telemonitoring in chronic heart failure involves remote monitoring, by clinicians, of daily patient measurements of biomarkers, such as, blood pressure and heart rate. As a strategy in heart failure management, the aim is for clinicians to use these measurements to predict rehospitalization,so that intervention decisions can be made. This is important for clinical practice 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 errorcontaminated 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 also provides clinicians with a valuable additional tool on which to base their intervention decisions, and thus provides immense contribution to heart failure management.
Keywords: area under the receiver operating characteristic curve (AUC); dynamic discriminative index; dynamic prediction; joint modelling
Document URI: http://hdl.handle.net/1942/16470
ISSN: 1471-082X
e-ISSN: 1477-0342
DOI: 10.1177/1471082X13478880
ISI #: 000320228900001
Rights: © 2013 SAGE Publications.
Category: A1
Type: Journal Contribution
Validations: ecoom 2014
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
A joint survival-longitudinal modelling approach ... - main document.pdfPeer-reviewed author version206.97 kBAdobe PDFView/Open
A joint survival-longitudinal modelling approach ... - web appendix.pdfSupplementary Material50.23 kBAdobe PDFView/Open
njagi2013.pdf
  Restricted Access
Published version268.76 kBAdobe PDFView/Open    Request a copy
Show full item record

SCOPUSTM   
Citations

15
checked on Sep 2, 2020

WEB OF SCIENCETM
Citations

17
checked on May 13, 2022

Page view(s)

46
checked on May 13, 2022

Download(s)

174
checked on May 13, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.