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A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction

Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the surviva...

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Main Authors: Abu Bakar, Mohd Rizam, A. Salah, Khalid, Ibrahim, Noor Akma, Haron, Kassim
Format: Article
Language:English
English
Published: EuroJournals Publishing Inc. 2007
Online Access:http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf
http://psasir.upm.edu.my/id/eprint/7671/
http://www.eurojournals.com/ejsr.htm
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spelling my.upm.eprints.76712015-12-08T09:02:38Z http://psasir.upm.edu.my/id/eprint/7671/ A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the survival function S(t) after sufficient follow-up. Thus, usual Cox proportional hazard model Cox (1972) is not applicable since the proportional hazard assumption is violated. An alternative is to consider survival models incorporating a cure fraction. In this paper we present a new class of joint model for univariate longitudinal and survival data in presence of cure fraction. For the longitudinal model, a stochastic Integrated Ornstein-Uhlenbeck process will present, and for the survival model a semiparametric survival function will be considered which accommodate both zero and non-zero cure fractions of the dynamic disease progression. Moreover, we consider a Bayesian approach which is motivated by the complexity of the model. Posterior and prior specification needs to accommodate parameter constraints due to the nonnegativity of the survival function. A simulation study is presented to evaluate the performance of this joint model. EuroJournals Publishing Inc. 2007 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf Abu Bakar, Mohd Rizam and A. Salah, Khalid and Ibrahim, Noor Akma and Haron, Kassim (2007) A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction. European Journal of Scientific Research, 18 (4). pp. 707-729. ISSN 1450-216X http://www.eurojournals.com/ejsr.htm English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Many medical investigations generate both repeatedly-measured (longitudinal)biomarker and survival data. One of complex issue arises when investigating the association between longitudinal and time-to-event data when there are cured patients in the population, which leads to a plateau in the survival function S(t) after sufficient follow-up. Thus, usual Cox proportional hazard model Cox (1972) is not applicable since the proportional hazard assumption is violated. An alternative is to consider survival models incorporating a cure fraction. In this paper we present a new class of joint model for univariate longitudinal and survival data in presence of cure fraction. For the longitudinal model, a stochastic Integrated Ornstein-Uhlenbeck process will present, and for the survival model a semiparametric survival function will be considered which accommodate both zero and non-zero cure fractions of the dynamic disease progression. Moreover, we consider a Bayesian approach which is motivated by the complexity of the model. Posterior and prior specification needs to accommodate parameter constraints due to the nonnegativity of the survival function. A simulation study is presented to evaluate the performance of this joint model.
format Article
author Abu Bakar, Mohd Rizam
A. Salah, Khalid
Ibrahim, Noor Akma
Haron, Kassim
spellingShingle Abu Bakar, Mohd Rizam
A. Salah, Khalid
Ibrahim, Noor Akma
Haron, Kassim
A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
author_facet Abu Bakar, Mohd Rizam
A. Salah, Khalid
Ibrahim, Noor Akma
Haron, Kassim
author_sort Abu Bakar, Mohd Rizam
title A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
title_short A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
title_full A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
title_fullStr A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
title_full_unstemmed A Semiparametric Joint Model for Longitudinal and Time-to- Event Univariate Data in Presence of Cure Fraction
title_sort semiparametric joint model for longitudinal and time-to- event univariate data in presence of cure fraction
publisher EuroJournals Publishing Inc.
publishDate 2007
url http://psasir.upm.edu.my/id/eprint/7671/1/A%20Semiparametric%20Joint%20Model%20for%20Longitudinal%20and%20Time.pdf
http://psasir.upm.edu.my/id/eprint/7671/
http://www.eurojournals.com/ejsr.htm
_version_ 1643823792764485632
score 13.211869

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