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Disease Progression in Multiple System Atrophy—Novel Modeling Framework and Predictive Factors

Kühnel, Line ; Raket, Lars Lau LU orcid ; Åström, Daniel Oudin LU ; Berger, Anna Karin ; Hansen, Ingeborg Helbech ; Krismer, Florian ; Wenning, Gregor K. ; Seppi, Klaus ; Poewe, Werner and Molinuevo, JoséLuis (2022) In Movement Disorders 37(8). p.1719-1727
Abstract

Background: Multiple system atrophy (MSA) is a rare and aggressive neurodegenerative disease that typically leads to death 6 to 10 years after symptom onset. The rapid evolution renders it crucial to understand the general disease progression and factors affecting the disease course. Objectives: The aims of this study were to develop a novel disease-progression model to estimate a population-level MSA progression trajectory and predict patient-specific continuous disease stages describing the degree of progress into the disease. Methods: The disease-progression model estimated a population-level progression trajectory of subscales of the Unified MSA Rating Scale and the Unified Parkinson's Disease Rating Scale using patients in the... (More)

Background: Multiple system atrophy (MSA) is a rare and aggressive neurodegenerative disease that typically leads to death 6 to 10 years after symptom onset. The rapid evolution renders it crucial to understand the general disease progression and factors affecting the disease course. Objectives: The aims of this study were to develop a novel disease-progression model to estimate a population-level MSA progression trajectory and predict patient-specific continuous disease stages describing the degree of progress into the disease. Methods: The disease-progression model estimated a population-level progression trajectory of subscales of the Unified MSA Rating Scale and the Unified Parkinson's Disease Rating Scale using patients in the European MSA natural history study. The predicted disease continuum was validated via multiple analyses based on reported anchor points, and the effect of MSA subtype on the rate of disease progression was evaluated. Results: The predicted disease continuum spanned approximately 6 years, with an estimated average duration of 51 months for a patient with global disability score 0 to reach the highest level of 4. The predicted continuous disease stages were shown to be correlated with time of symptom onset and predictive of survival time. MSA motor subtype was found to significantly affect disease progression, with MSA-parkinsonian (MSA-P) type patients having an accelerated rate of progression. Conclusions: The proposed modeling framework introduces a new method of analyzing and interpreting the progression of MSA. It can provide new insights and opportunities for investigating covariate effects on the rate of progression and provide well-founded predictions of patient-level future progressions.

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author
; ; ; ; ; ; ; ; and
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
disease progression, motor subtype, multiple system atrophy, multivariate nonlinear mixed-effects models, neurodegenerative disease
in
Movement Disorders
volume
37
issue
8
pages
9 pages
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:85135999966
  • pmid:35668573
ISSN
0885-3185
DOI
10.1002/mds.29077
language
English
LU publication?
yes
id
65e5e5aa-33aa-405a-869e-0f63b242941d
date added to LUP
2022-10-28 15:12:07
date last changed
2024-04-18 17:02:25
@article{65e5e5aa-33aa-405a-869e-0f63b242941d,
  abstract     = {{<p>Background: Multiple system atrophy (MSA) is a rare and aggressive neurodegenerative disease that typically leads to death 6 to 10 years after symptom onset. The rapid evolution renders it crucial to understand the general disease progression and factors affecting the disease course. Objectives: The aims of this study were to develop a novel disease-progression model to estimate a population-level MSA progression trajectory and predict patient-specific continuous disease stages describing the degree of progress into the disease. Methods: The disease-progression model estimated a population-level progression trajectory of subscales of the Unified MSA Rating Scale and the Unified Parkinson's Disease Rating Scale using patients in the European MSA natural history study. The predicted disease continuum was validated via multiple analyses based on reported anchor points, and the effect of MSA subtype on the rate of disease progression was evaluated. Results: The predicted disease continuum spanned approximately 6 years, with an estimated average duration of 51 months for a patient with global disability score 0 to reach the highest level of 4. The predicted continuous disease stages were shown to be correlated with time of symptom onset and predictive of survival time. MSA motor subtype was found to significantly affect disease progression, with MSA-parkinsonian (MSA-P) type patients having an accelerated rate of progression. Conclusions: The proposed modeling framework introduces a new method of analyzing and interpreting the progression of MSA. It can provide new insights and opportunities for investigating covariate effects on the rate of progression and provide well-founded predictions of patient-level future progressions.</p>}},
  author       = {{Kühnel, Line and Raket, Lars Lau and Åström, Daniel Oudin and Berger, Anna Karin and Hansen, Ingeborg Helbech and Krismer, Florian and Wenning, Gregor K. and Seppi, Klaus and Poewe, Werner and Molinuevo, JoséLuis}},
  issn         = {{0885-3185}},
  keywords     = {{disease progression; motor subtype; multiple system atrophy; multivariate nonlinear mixed-effects models; neurodegenerative disease}},
  language     = {{eng}},
  number       = {{8}},
  pages        = {{1719--1727}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{Movement Disorders}},
  title        = {{Disease Progression in Multiple System Atrophy—Novel Modeling Framework and Predictive Factors}},
  url          = {{http://dx.doi.org/10.1002/mds.29077}},
  doi          = {{10.1002/mds.29077}},
  volume       = {{37}},
  year         = {{2022}},
}