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Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy
BACKGROUND: Multiple system atrophy (MSA) is a devastating disease characterized by a variable combination of motor and autonomic symptoms. Previous studies identified numerous clinical factors to be associated with shorter survival. OBJECTIVE: To enable personalized patient counseling, we aimed at...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525072/ https://www.ncbi.nlm.nih.gov/pubmed/37772304 http://dx.doi.org/10.1002/mdc3.13822 |
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author | Eschlboeck, Sabine Goebel, Georg Eckhardt, Christine Fanciulli, Alessandra Raccagni, Cecilia Boesch, Sylvia Djamshidian, Atbin Heim, Beatrice Mahlknecht, Philipp Mair, Katherina Nachbauer, Wolfgang Scherfler, Christoph Stockner, Heike Poewe, Werner Seppi, Klaus Kiechl, Stefan Wenning, Gregor Krismer, Florian Barone, Paolo Pellecchia, Maria Teresa Quinn, Niall P Fowler, Clare J Schrag, Anette Giladi, Nir Gurevich, Tanya Ostergaard, Karen Widner, Håkan Oertel, Wolfgang Albanese, Alberto Tolosa, Eduardo Deuschl, Günther Klockgether, Thomas Dodel, Richard Sampaio, Cristina Melamed, Eldad Gasser, Thomas Colosimo, Carlo Rascol, Olivier Meissner, Wassilios Tison, François Geser, Felix Duerr, Susanne Boesch, Sylvia Köllensperger, Martin Koukouni, Vasiliki Mathias, Christopher J Dupont, Erik Nilsson, Christer F Eggert, Karla Maria del Sorbo, Francesca Cardozo, Adriana Hellriegel, Helge Coelho, Miguel Djaldetti, Ruth Kamm, Christoph Meco, Giuseppe |
author_facet | Eschlboeck, Sabine Goebel, Georg Eckhardt, Christine Fanciulli, Alessandra Raccagni, Cecilia Boesch, Sylvia Djamshidian, Atbin Heim, Beatrice Mahlknecht, Philipp Mair, Katherina Nachbauer, Wolfgang Scherfler, Christoph Stockner, Heike Poewe, Werner Seppi, Klaus Kiechl, Stefan Wenning, Gregor Krismer, Florian Barone, Paolo Pellecchia, Maria Teresa Quinn, Niall P Fowler, Clare J Schrag, Anette Giladi, Nir Gurevich, Tanya Ostergaard, Karen Widner, Håkan Oertel, Wolfgang Albanese, Alberto Tolosa, Eduardo Deuschl, Günther Klockgether, Thomas Dodel, Richard Sampaio, Cristina Melamed, Eldad Gasser, Thomas Colosimo, Carlo Rascol, Olivier Meissner, Wassilios Tison, François Geser, Felix Duerr, Susanne Boesch, Sylvia Köllensperger, Martin Koukouni, Vasiliki Mathias, Christopher J Dupont, Erik Nilsson, Christer F Eggert, Karla Maria del Sorbo, Francesca Cardozo, Adriana Hellriegel, Helge Coelho, Miguel Djaldetti, Ruth Kamm, Christoph Meco, Giuseppe |
author_sort | Eschlboeck, Sabine |
collection | PubMed |
description | BACKGROUND: Multiple system atrophy (MSA) is a devastating disease characterized by a variable combination of motor and autonomic symptoms. Previous studies identified numerous clinical factors to be associated with shorter survival. OBJECTIVE: To enable personalized patient counseling, we aimed at developing a risk model of survival based on baseline clinical symptoms. METHODS: MSA patients referred to the Movement Disorders Unit in Innsbruck, Austria, between 1999 and 2016 were retrospectively analyzed. Kaplan–Meier curves and multivariate Cox regression analysis with least absolute shrinkage and selection operator penalty for variable selection were performed to identify prognostic factors. A nomogram was developed to estimate the 7 years overall survival probability. The performance of the predictive model was validated and calibrated internally using bootstrap resampling and externally using data from the prospective European MSA Study Group Natural History Study. RESULTS: A total of 210 MSA patients were included in this analysis, of which 124 patients died. The median survival was 7 years. The following clinical variables were found to significantly affect overall survival and were included in the nomogram: age at symptom onset, falls within 3 years of onset, early autonomic failure including orthostatic hypotension and urogenital failure, and lacking levodopa response. The time‐dependent area under curve for internal and external validation was >0.7 within the first 7 years of the disease course. The model was well calibrated showing good overlap between predicted and actual survival probability at 7 years. CONCLUSION: The nomogram is a simple tool to predict survival on an individual basis and may help to improve counseling and treatment of MSA patients. |
format | Online Article Text |
id | pubmed-10525072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105250722023-09-28 Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy Eschlboeck, Sabine Goebel, Georg Eckhardt, Christine Fanciulli, Alessandra Raccagni, Cecilia Boesch, Sylvia Djamshidian, Atbin Heim, Beatrice Mahlknecht, Philipp Mair, Katherina Nachbauer, Wolfgang Scherfler, Christoph Stockner, Heike Poewe, Werner Seppi, Klaus Kiechl, Stefan Wenning, Gregor Krismer, Florian Barone, Paolo Pellecchia, Maria Teresa Quinn, Niall P Fowler, Clare J Schrag, Anette Giladi, Nir Gurevich, Tanya Ostergaard, Karen Widner, Håkan Oertel, Wolfgang Albanese, Alberto Tolosa, Eduardo Deuschl, Günther Klockgether, Thomas Dodel, Richard Sampaio, Cristina Melamed, Eldad Gasser, Thomas Colosimo, Carlo Rascol, Olivier Meissner, Wassilios Tison, François Geser, Felix Duerr, Susanne Boesch, Sylvia Köllensperger, Martin Koukouni, Vasiliki Mathias, Christopher J Dupont, Erik Nilsson, Christer F Eggert, Karla Maria del Sorbo, Francesca Cardozo, Adriana Hellriegel, Helge Coelho, Miguel Djaldetti, Ruth Kamm, Christoph Meco, Giuseppe Mov Disord Clin Pract Research Articles BACKGROUND: Multiple system atrophy (MSA) is a devastating disease characterized by a variable combination of motor and autonomic symptoms. Previous studies identified numerous clinical factors to be associated with shorter survival. OBJECTIVE: To enable personalized patient counseling, we aimed at developing a risk model of survival based on baseline clinical symptoms. METHODS: MSA patients referred to the Movement Disorders Unit in Innsbruck, Austria, between 1999 and 2016 were retrospectively analyzed. Kaplan–Meier curves and multivariate Cox regression analysis with least absolute shrinkage and selection operator penalty for variable selection were performed to identify prognostic factors. A nomogram was developed to estimate the 7 years overall survival probability. The performance of the predictive model was validated and calibrated internally using bootstrap resampling and externally using data from the prospective European MSA Study Group Natural History Study. RESULTS: A total of 210 MSA patients were included in this analysis, of which 124 patients died. The median survival was 7 years. The following clinical variables were found to significantly affect overall survival and were included in the nomogram: age at symptom onset, falls within 3 years of onset, early autonomic failure including orthostatic hypotension and urogenital failure, and lacking levodopa response. The time‐dependent area under curve for internal and external validation was >0.7 within the first 7 years of the disease course. The model was well calibrated showing good overlap between predicted and actual survival probability at 7 years. CONCLUSION: The nomogram is a simple tool to predict survival on an individual basis and may help to improve counseling and treatment of MSA patients. John Wiley & Sons, Inc. 2023-07-17 /pmc/articles/PMC10525072/ /pubmed/37772304 http://dx.doi.org/10.1002/mdc3.13822 Text en © 2023 The Authors. Movement Disorders Clinical Practice published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Eschlboeck, Sabine Goebel, Georg Eckhardt, Christine Fanciulli, Alessandra Raccagni, Cecilia Boesch, Sylvia Djamshidian, Atbin Heim, Beatrice Mahlknecht, Philipp Mair, Katherina Nachbauer, Wolfgang Scherfler, Christoph Stockner, Heike Poewe, Werner Seppi, Klaus Kiechl, Stefan Wenning, Gregor Krismer, Florian Barone, Paolo Pellecchia, Maria Teresa Quinn, Niall P Fowler, Clare J Schrag, Anette Giladi, Nir Gurevich, Tanya Ostergaard, Karen Widner, Håkan Oertel, Wolfgang Albanese, Alberto Tolosa, Eduardo Deuschl, Günther Klockgether, Thomas Dodel, Richard Sampaio, Cristina Melamed, Eldad Gasser, Thomas Colosimo, Carlo Rascol, Olivier Meissner, Wassilios Tison, François Geser, Felix Duerr, Susanne Boesch, Sylvia Köllensperger, Martin Koukouni, Vasiliki Mathias, Christopher J Dupont, Erik Nilsson, Christer F Eggert, Karla Maria del Sorbo, Francesca Cardozo, Adriana Hellriegel, Helge Coelho, Miguel Djaldetti, Ruth Kamm, Christoph Meco, Giuseppe Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title | Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title_full | Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title_fullStr | Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title_full_unstemmed | Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title_short | Development and Validation of a Prognostic Model to Predict Overall Survival in Multiple System Atrophy |
title_sort | development and validation of a prognostic model to predict overall survival in multiple system atrophy |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10525072/ https://www.ncbi.nlm.nih.gov/pubmed/37772304 http://dx.doi.org/10.1002/mdc3.13822 |
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