ArticleJournal of Parkinson's disease2023
Predicting the Prognosis of Multiple System Atrophy Using Cluster and Principal Component Analysis.
Article in Journal of Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- A meta-analysis of survival and prognostic factors in multiple system atrophy.Journal of neurology · 2025Pooled it
- A novel nutritional immune risk score model for long-term prognosis in colorectal cancer using clustering and principal component analysis.Frontiers in nutrition · 2026Article
- Correlations between Dysphagia Severity Scale Scores and Clinical Indices in Individuals with Multiple System Atrophy.Movement disorders clinical practice · 2025Article
- Review
- Lower urinary tract dysfunction in the central nervous system neurogenic bladder and the real-life treatment outcome of botulinum toxin A.Tzu chi medical journalReview
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMultiple system atrophy (MSA) is an intractable neurodegenerative disorder with poorly understanding of prognostic factors.
objectiveThe purpose of this retrospective longitudinal study was to explore the main predictors of survival of MSA patients with new clinical subtypes based on cluster analysis.
methodsA total of 153 Chinese MSA patients were recruited in our study. The basic demographic data and motor and nonmotor symptoms were assessed. Cluster and principal component analysis (PCA) were used to eliminate collinearity and search for new clinical subtypes. The multivariable Cox regression was used to find factors associated with survival in MSA patients.
resultsThe median survival time from symptom onset to death (estimated using data from all patients by Kaplan-Meier analysis) was 6.3 (95% CI = 6.1-6.7) years. The survival model showed that a shorter survival time was associated with motor principal component (PC)1 (HR = 1.71, 95% CI: 1.26-2.30, p < 0.001) and nonmotor PC3 (HR = 1.68, 95% CI: 1.31-2.10, p < 0.001) through PCA. Four clusters were identified: Cluster 1 (mild), Cluster 2 (mood disorder-dominant), Cluster 3 (axial symptoms and cognitive impairment-dominant), and Cluster 4 (autonomic failure-dominant). Multivariate Cox regression indicated that Cluster 3 (HR = 4.15, 95% CI: 1.73-9.90, p = 0.001) and Cluster 4 (HR = 4.18, 95% CI: 1.73-10.1, p = 0.002) were independently associated with shorter survival time.
conclusionMore serious motor symptoms, axial symptoms such as falls and dysphagia, orthostatic hypotension, and cognitive impairment were associated with poor survival in MSA via PCA and cluster analysis.
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