Two-stage model for multivariate longitudinal and survival data with application to nephrology research
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10216/111797 |
Resumo: | In many follow‐up studies different types of outcomes are collected including longitudinal measurements and time‐to‐event outcomes. Commonly, it is of interest to study the association between them. Joint modeling approaches of a single longitudinal outcome and survival process have recently gained increasing attention from both frequentist and Bayesian perspective. However, in many studies several longitudinal biomarkers are of interest and instead of selecting one single biomarker, the relationships between all these outcomes and their association with survival needs to be investigated. Our motivating study comes from Peritoneal Dialysis Programme in Nephrology research from Nephrology Unit, CHP (Hospital de Santo António), Porto, Portugal in which the interest relies on the possible association between various biomarkers (calcium, phosphate, parathormone, and creatinine) and the patients' survival. To this aim, we propose a two‐stage model‐based approach for multivariate longitudinal and survival data that allowed us to study such complex association structure. The multivariate model suggested in this paper provided new insights in the area of nephrology research showing valid results in comparison with those models studying each longitudinal biomarker with survival separately. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Two-stage model for multivariate longitudinal and survival data with application to nephrology researchMultivariate longitudinal dataNephrology peritoneal dialysisIn many follow‐up studies different types of outcomes are collected including longitudinal measurements and time‐to‐event outcomes. Commonly, it is of interest to study the association between them. Joint modeling approaches of a single longitudinal outcome and survival process have recently gained increasing attention from both frequentist and Bayesian perspective. However, in many studies several longitudinal biomarkers are of interest and instead of selecting one single biomarker, the relationships between all these outcomes and their association with survival needs to be investigated. Our motivating study comes from Peritoneal Dialysis Programme in Nephrology research from Nephrology Unit, CHP (Hospital de Santo António), Porto, Portugal in which the interest relies on the possible association between various biomarkers (calcium, phosphate, parathormone, and creatinine) and the patients' survival. To this aim, we propose a two‐stage model‐based approach for multivariate longitudinal and survival data that allowed us to study such complex association structure. The multivariate model suggested in this paper provided new insights in the area of nephrology research showing valid results in comparison with those models studying each longitudinal biomarker with survival separately.Wiley20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10216/111797eng10.1002/bimj.201600244Guler, IFaes, CCadarso-Suárez, CTeixeira, LRodrigues, AMendonça, Dinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T13:40:26Zoai:repositorio-aberto.up.pt:10216/111797Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:45:22.118402Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
title |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
spellingShingle |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research Guler, I Multivariate longitudinal data Nephrology peritoneal dialysis |
title_short |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
title_full |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
title_fullStr |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
title_full_unstemmed |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
title_sort |
Two-stage model for multivariate longitudinal and survival data with application to nephrology research |
author |
Guler, I |
author_facet |
Guler, I Faes, C Cadarso-Suárez, C Teixeira, L Rodrigues, A Mendonça, D |
author_role |
author |
author2 |
Faes, C Cadarso-Suárez, C Teixeira, L Rodrigues, A Mendonça, D |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Guler, I Faes, C Cadarso-Suárez, C Teixeira, L Rodrigues, A Mendonça, D |
dc.subject.por.fl_str_mv |
Multivariate longitudinal data Nephrology peritoneal dialysis |
topic |
Multivariate longitudinal data Nephrology peritoneal dialysis |
description |
In many follow‐up studies different types of outcomes are collected including longitudinal measurements and time‐to‐event outcomes. Commonly, it is of interest to study the association between them. Joint modeling approaches of a single longitudinal outcome and survival process have recently gained increasing attention from both frequentist and Bayesian perspective. However, in many studies several longitudinal biomarkers are of interest and instead of selecting one single biomarker, the relationships between all these outcomes and their association with survival needs to be investigated. Our motivating study comes from Peritoneal Dialysis Programme in Nephrology research from Nephrology Unit, CHP (Hospital de Santo António), Porto, Portugal in which the interest relies on the possible association between various biomarkers (calcium, phosphate, parathormone, and creatinine) and the patients' survival. To this aim, we propose a two‐stage model‐based approach for multivariate longitudinal and survival data that allowed us to study such complex association structure. The multivariate model suggested in this paper provided new insights in the area of nephrology research showing valid results in comparison with those models studying each longitudinal biomarker with survival separately. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017 2017-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10216/111797 |
url |
http://hdl.handle.net/10216/111797 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1002/bimj.201600244 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799135770531856384 |