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SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data
The survival path mapping approach has been proposed for dynamic prognostication of cancer patients using time-series survival data. The SurvivalPath R package was developed to facilitate building personalized survival path models. The package contains functions to convert time-series data into time...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851545/ https://www.ncbi.nlm.nih.gov/pubmed/36608157 http://dx.doi.org/10.1371/journal.pcbi.1010830 |
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author | Shen, Lujun Mo, Jinqing Yang, Changsheng Jiang, Yiquan Ke, Liangru Hou, Dan Yan, Jingdong Zhang, Tao Fan, Weijun |
author_facet | Shen, Lujun Mo, Jinqing Yang, Changsheng Jiang, Yiquan Ke, Liangru Hou, Dan Yan, Jingdong Zhang, Tao Fan, Weijun |
author_sort | Shen, Lujun |
collection | PubMed |
description | The survival path mapping approach has been proposed for dynamic prognostication of cancer patients using time-series survival data. The SurvivalPath R package was developed to facilitate building personalized survival path models. The package contains functions to convert time-series data into time-slices data by fixed interval based on time information of input medical records. After the pre-processing of data, under a user-defined parameters on covariates, significance level, minimum bifurcation sample size and number of time slices for analysis, survival paths can be computed using the main function, which can be visualized as a tree diagram, with important parameters annotated. The package also includes function for analyzing the connections between exposure/treatment and node transitions, and function for screening patient subgroup with specific features, which can be used for further exploration analysis. In this study, we demonstrate the application of this package in a large dataset of patients with hepatocellular carcinoma, which is embedded in the package. The SurvivalPath R package is freely available from CRAN, with source code and documentation hosted at https://github.com/zhangt369/SurvivalPath. |
format | Online Article Text |
id | pubmed-9851545 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98515452023-01-20 SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data Shen, Lujun Mo, Jinqing Yang, Changsheng Jiang, Yiquan Ke, Liangru Hou, Dan Yan, Jingdong Zhang, Tao Fan, Weijun PLoS Comput Biol Research Article The survival path mapping approach has been proposed for dynamic prognostication of cancer patients using time-series survival data. The SurvivalPath R package was developed to facilitate building personalized survival path models. The package contains functions to convert time-series data into time-slices data by fixed interval based on time information of input medical records. After the pre-processing of data, under a user-defined parameters on covariates, significance level, minimum bifurcation sample size and number of time slices for analysis, survival paths can be computed using the main function, which can be visualized as a tree diagram, with important parameters annotated. The package also includes function for analyzing the connections between exposure/treatment and node transitions, and function for screening patient subgroup with specific features, which can be used for further exploration analysis. In this study, we demonstrate the application of this package in a large dataset of patients with hepatocellular carcinoma, which is embedded in the package. The SurvivalPath R package is freely available from CRAN, with source code and documentation hosted at https://github.com/zhangt369/SurvivalPath. Public Library of Science 2023-01-06 /pmc/articles/PMC9851545/ /pubmed/36608157 http://dx.doi.org/10.1371/journal.pcbi.1010830 Text en © 2023 Shen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Shen, Lujun Mo, Jinqing Yang, Changsheng Jiang, Yiquan Ke, Liangru Hou, Dan Yan, Jingdong Zhang, Tao Fan, Weijun SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title | SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title_full | SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title_fullStr | SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title_full_unstemmed | SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title_short | SurvivalPath:A R package for conducting personalized survival path mapping based on time-series survival data |
title_sort | survivalpath:a r package for conducting personalized survival path mapping based on time-series survival data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851545/ https://www.ncbi.nlm.nih.gov/pubmed/36608157 http://dx.doi.org/10.1371/journal.pcbi.1010830 |
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