Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model

Clinically isolated syndrome (CIS) refers to the initial clinical episode with symptoms suggestive of multiple sclerosis (MS). Due to limited number of long-term follow-up studies, progression pattern from CIS to more advanced stages remains unclear. In the current study, we constructed a Markov mod...

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Autores principales: Hou, Yuli, Jia, Yujuan, Hou, Jingtian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6052069/
https://www.ncbi.nlm.nih.gov/pubmed/30022111
http://dx.doi.org/10.1038/s41598-018-29206-y
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author Hou, Yuli
Jia, Yujuan
Hou, Jingtian
author_facet Hou, Yuli
Jia, Yujuan
Hou, Jingtian
author_sort Hou, Yuli
collection PubMed
description Clinically isolated syndrome (CIS) refers to the initial clinical episode with symptoms suggestive of multiple sclerosis (MS). Due to limited number of long-term follow-up studies, progression pattern from CIS to more advanced stages remains unclear. In the current study, we constructed a Markov model to simulate the natural course of CIS. The model estimated the probabilities of transition from CIS to more advanced disease stages and the duration needed for the progression. The analysis showed: (1) CIS is a solid disease identity: more than 85% of the subjects with a diagnosis of CIS progress to RRMS or more advanced stages within 20 years; (2) the reduction of life expectancy in subjects with CIS is marginal.
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spelling pubmed-60520692018-07-23 Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model Hou, Yuli Jia, Yujuan Hou, Jingtian Sci Rep Article Clinically isolated syndrome (CIS) refers to the initial clinical episode with symptoms suggestive of multiple sclerosis (MS). Due to limited number of long-term follow-up studies, progression pattern from CIS to more advanced stages remains unclear. In the current study, we constructed a Markov model to simulate the natural course of CIS. The model estimated the probabilities of transition from CIS to more advanced disease stages and the duration needed for the progression. The analysis showed: (1) CIS is a solid disease identity: more than 85% of the subjects with a diagnosis of CIS progress to RRMS or more advanced stages within 20 years; (2) the reduction of life expectancy in subjects with CIS is marginal. Nature Publishing Group UK 2018-07-18 /pmc/articles/PMC6052069/ /pubmed/30022111 http://dx.doi.org/10.1038/s41598-018-29206-y Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hou, Yuli
Jia, Yujuan
Hou, Jingtian
Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title_full Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title_fullStr Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title_full_unstemmed Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title_short Natural Course of Clinically Isolated Syndrome: A Longitudinal Analysis Using a Markov Model
title_sort natural course of clinically isolated syndrome: a longitudinal analysis using a markov model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6052069/
https://www.ncbi.nlm.nih.gov/pubmed/30022111
http://dx.doi.org/10.1038/s41598-018-29206-y
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