Cargando…
Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients
PURPOSE: To distinguish clinical factors that have time-varying (as opposed to constant) impact upon patient and graft survival among pediatric liver transplant recipients. METHODS: Using national data from 2002 through 2013, we examined potential clinical and demographic covariates using Gray’s pie...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978879/ https://www.ncbi.nlm.nih.gov/pubmed/29851966 http://dx.doi.org/10.1371/journal.pone.0198132 |
_version_ | 1783327573823979520 |
---|---|
author | Bryce, Cindy L. Chang, Chung Chou H. Ren, Yi Yabes, Jonathan Zenarosa, Gabriel Iyer, Aditya Tomko, Heather Squires, Robert H. Roberts, Mark S. |
author_facet | Bryce, Cindy L. Chang, Chung Chou H. Ren, Yi Yabes, Jonathan Zenarosa, Gabriel Iyer, Aditya Tomko, Heather Squires, Robert H. Roberts, Mark S. |
author_sort | Bryce, Cindy L. |
collection | PubMed |
description | PURPOSE: To distinguish clinical factors that have time-varying (as opposed to constant) impact upon patient and graft survival among pediatric liver transplant recipients. METHODS: Using national data from 2002 through 2013, we examined potential clinical and demographic covariates using Gray’s piecewise constant time-varying coefficients (TVC) models. For both patient and graft survival, we estimated univariable and multivariable Gray’s TVC, retaining significant covariates based on backward selection. We then estimated the same specification using traditional Cox proportional hazards (PH) models and compared our findings. RESULTS: For patient survival, covariates included recipient diagnosis, age, race/ethnicity, ventilator support, encephalopathy, creatinine levels, use of living donor, and donor age. Only the effects of recipient diagnosis and donor age were constant; effects of other covariates varied over time. We retained identical covariates in the graft survival model but found several differences in their impact. CONCLUSION: The flexibility afforded by Gray’s TVC estimation methods identify several covariates that do not satisfy constant proportionality assumptions of the Cox PH model. Incorporating better survival estimates is critical for improving risk prediction tools used by the transplant community to inform organ allocation decisions. |
format | Online Article Text |
id | pubmed-5978879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59788792018-06-17 Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients Bryce, Cindy L. Chang, Chung Chou H. Ren, Yi Yabes, Jonathan Zenarosa, Gabriel Iyer, Aditya Tomko, Heather Squires, Robert H. Roberts, Mark S. PLoS One Research Article PURPOSE: To distinguish clinical factors that have time-varying (as opposed to constant) impact upon patient and graft survival among pediatric liver transplant recipients. METHODS: Using national data from 2002 through 2013, we examined potential clinical and demographic covariates using Gray’s piecewise constant time-varying coefficients (TVC) models. For both patient and graft survival, we estimated univariable and multivariable Gray’s TVC, retaining significant covariates based on backward selection. We then estimated the same specification using traditional Cox proportional hazards (PH) models and compared our findings. RESULTS: For patient survival, covariates included recipient diagnosis, age, race/ethnicity, ventilator support, encephalopathy, creatinine levels, use of living donor, and donor age. Only the effects of recipient diagnosis and donor age were constant; effects of other covariates varied over time. We retained identical covariates in the graft survival model but found several differences in their impact. CONCLUSION: The flexibility afforded by Gray’s TVC estimation methods identify several covariates that do not satisfy constant proportionality assumptions of the Cox PH model. Incorporating better survival estimates is critical for improving risk prediction tools used by the transplant community to inform organ allocation decisions. Public Library of Science 2018-05-31 /pmc/articles/PMC5978879/ /pubmed/29851966 http://dx.doi.org/10.1371/journal.pone.0198132 Text en © 2018 Bryce et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Bryce, Cindy L. Chang, Chung Chou H. Ren, Yi Yabes, Jonathan Zenarosa, Gabriel Iyer, Aditya Tomko, Heather Squires, Robert H. Roberts, Mark S. Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title | Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title_full | Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title_fullStr | Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title_full_unstemmed | Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title_short | Using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
title_sort | using time-varying models to estimate post-transplant survival in pediatric liver transplant recipients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5978879/ https://www.ncbi.nlm.nih.gov/pubmed/29851966 http://dx.doi.org/10.1371/journal.pone.0198132 |
work_keys_str_mv | AT brycecindyl usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT changchungchouh usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT renyi usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT yabesjonathan usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT zenarosagabriel usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT iyeraditya usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT tomkoheather usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT squiresroberth usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients AT robertsmarks usingtimevaryingmodelstoestimateposttransplantsurvivalinpediatriclivertransplantrecipients |