4.6 Article

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

Journal

MOVEMENT DISORDERS
Volume 37, Issue 8, Pages 1719-1727

Publisher

WILEY
DOI: 10.1002/mds.29077

Keywords

disease progression; multiple system atrophy; multivariate nonlinear mixed-effects models; motor subtype; neurodegenerative disease

Funding

  1. Innovation Fund Denmark [9066-00005B]
  2. Fifth Framework Programme of the European Community [QLK6-CT-2000-00661]

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This study developed a novel disease-progression model to estimate the progression trajectory of multiple system atrophy (MSA) at a population level and predict patient-specific continuous disease stages. The predicted disease continuum was correlated with the time of symptom onset and predictive of survival time. MSA subtype was found to significantly affect disease progression.
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. (c) 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

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