Introduction <p>Multiple system atrophy (MSA) is a clinically heterogeneous disorder. Conventional motor phenotype-based classification provides limited prognostic information. Previously, we identified data-driven subtypes of early-stage MSA using a latent class analysis (LCA) that incorporated both motor and non-motor features. However, the prognostic significance of these subtypes remains unclear.</p> Methods <p>We analyzed the survival outcomes in a previously reported cohort of 61 patients with probable or possible MSA enrolled within three years of motor symptom onset. Patients were classified according to LCA-derived subtypes and dichotomized into an extensive or restricted dysautonomia group based on shared autonomic profiles. Overall survival was assessed using Kaplan–Meier analysis and compared using the log-rank test. Cox proportional hazards models were used to estimate hazard ratios (HRs) with progressive adjustments for the age at onset, sex, baseline disease severity (Unified Multiple System Atrophy Rating Scale, UMSARS Part I), and disease duration at enrollment.</p> Results <p>Survival analysis was performed in 60 patients, 47 of whom died by the end of follow-up. The extensive dysautonomia group showed a significantly shorter median survival than the restricted group (6.0 vs. 7.0&#xa0;years; log-rank <i>p</i> = 0.008). After adjusting for the age at onset and sex, the restricted group had a lower risk of mortality (adjusted HR: 0.538, 95% CI 0.290–0.996; <i>p</i> = 0.049). This association was attenuated after additional adjustments for the baseline disease severity (UMSARS Part I) and disease duration.</p> Conclusions <p>Data-driven subtypes defined by early symptom patterns correspond to clinically meaningful survival differences in patients with MSA. Extensive dysautonomia reflects a more malignant, globally severe phenotype than isolated autonomic involvement, highlighting the prognostic relevance of incorporating non-motor features into early MSA classification.</p>

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Extensive dysautonomia in early-stage multiple system atrophy reflects survival differences: insights from data-driven subtypes

  • Su Hyeon Ha,
  • Hui-Jun Yang,
  • Seungmin Lee,
  • Kyung Ah Woo,
  • Jung Hwan Shin,
  • Han-Joon Kim

摘要

Introduction

Multiple system atrophy (MSA) is a clinically heterogeneous disorder. Conventional motor phenotype-based classification provides limited prognostic information. Previously, we identified data-driven subtypes of early-stage MSA using a latent class analysis (LCA) that incorporated both motor and non-motor features. However, the prognostic significance of these subtypes remains unclear.

Methods

We analyzed the survival outcomes in a previously reported cohort of 61 patients with probable or possible MSA enrolled within three years of motor symptom onset. Patients were classified according to LCA-derived subtypes and dichotomized into an extensive or restricted dysautonomia group based on shared autonomic profiles. Overall survival was assessed using Kaplan–Meier analysis and compared using the log-rank test. Cox proportional hazards models were used to estimate hazard ratios (HRs) with progressive adjustments for the age at onset, sex, baseline disease severity (Unified Multiple System Atrophy Rating Scale, UMSARS Part I), and disease duration at enrollment.

Results

Survival analysis was performed in 60 patients, 47 of whom died by the end of follow-up. The extensive dysautonomia group showed a significantly shorter median survival than the restricted group (6.0 vs. 7.0 years; log-rank p = 0.008). After adjusting for the age at onset and sex, the restricted group had a lower risk of mortality (adjusted HR: 0.538, 95% CI 0.290–0.996; p = 0.049). This association was attenuated after additional adjustments for the baseline disease severity (UMSARS Part I) and disease duration.

Conclusions

Data-driven subtypes defined by early symptom patterns correspond to clinically meaningful survival differences in patients with MSA. Extensive dysautonomia reflects a more malignant, globally severe phenotype than isolated autonomic involvement, highlighting the prognostic relevance of incorporating non-motor features into early MSA classification.