A stochastic joint model for longitudinal and survival data with cure patients
Many medical investigations generate both repeatedly-measured (longitudinal) biomarker and survival data. One of complex issues 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 survi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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CESER Publications
2009
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| Online Access: | http://psasir.upm.edu.my/id/eprint/12867/ http://psasir.upm.edu.my/id/eprint/12867/1/A%20stochastic%20joint%20model%20for%20longitudinal%20and%20survival%20data%20with%20cure%20patients.pdf |
| _version_ | 1848841953400061952 |
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| author | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim |
| author_facet | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim |
| author_sort | Abu Bakar, Mohd Rizam |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Many medical investigations generate both repeatedly-measured (longitudinal) biomarker and survival data. One of complex issues 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 be presented. 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.
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| first_indexed | 2025-11-15T07:51:25Z |
| format | Article |
| id | upm-12867 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T07:51:25Z |
| publishDate | 2009 |
| publisher | CESER Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-128672015-12-01T07:07:27Z http://psasir.upm.edu.my/id/eprint/12867/ A stochastic joint model for longitudinal and survival data with cure patients 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 issues 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 be presented. 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. CESER Publications 2009 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/12867/1/A%20stochastic%20joint%20model%20for%20longitudinal%20and%20survival%20data%20with%20cure%20patients.pdf Abu Bakar, Mohd Rizam and A. Salah, Khalid and Ibrahim, Noor Akma and Haron, Kassim (2009) A stochastic joint model for longitudinal and survival data with cure patients. International Journal of Tomography & Statistics, 11 (W09). pp. 48-67. ISSN 0972-9976; ESSN: 0973-7294 |
| spellingShingle | Abu Bakar, Mohd Rizam A. Salah, Khalid Ibrahim, Noor Akma Haron, Kassim A stochastic joint model for longitudinal and survival data with cure patients |
| title | A stochastic joint model for longitudinal and survival data with cure patients |
| title_full | A stochastic joint model for longitudinal and survival data with cure patients |
| title_fullStr | A stochastic joint model for longitudinal and survival data with cure patients |
| title_full_unstemmed | A stochastic joint model for longitudinal and survival data with cure patients |
| title_short | A stochastic joint model for longitudinal and survival data with cure patients |
| title_sort | stochastic joint model for longitudinal and survival data with cure patients |
| url | http://psasir.upm.edu.my/id/eprint/12867/ http://psasir.upm.edu.my/id/eprint/12867/1/A%20stochastic%20joint%20model%20for%20longitudinal%20and%20survival%20data%20with%20cure%20patients.pdf |