The severity assessment of Parkinson's disease based on plasma inflammatory factors and third ventricle width by transcranial sonography
© 2024 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd..
BACKGROUND: Predicting Parkinson's disease (PD) can provide patients with targeted therapies. However, disease severity can be roughly evaluated in clinical practice based on the patient's symptoms and signs.
OBJECTIVE: The current study attempted to explore the factors linked with PD severity and construct a predictive model.
METHOD: The PD patients and healthy controls were recruited from our study center while recording their basic demographic information. The serum inflammatory markers levels, such as Cystatin C (Cys C), C-reactive protein (CRP), RANTES (regulated on activation, normal T cell expressed and secreted), Interleukin-10 (IL-10), and Interleukin-6 (IL-6) were determined for all the participants. PD patients were categorized into early and mid-advanced groups based on the Hoehn and Yahr (H-Y) scale and evaluated using PD-related scales. LASSO logistic regression analysis (Model C) helped select variables based on clinical scale evaluations, serum inflammatory factor levels, and transcranial sonography measurements. The optimal harmonious model coefficient λ was determined via 10-fold cross-validation. Moreover, Model C was compared with multivariate (Model A) and stepwise (Model B) logistic regression. The area under the curve (AUC) of a receiver operator characteristic (ROC), brier score, calibration curve, and decision curve analysis (DCA) helped determine the discrimination and calibration of the predictive model, followed by configuring a forest plot and column chart.
RESULTS: The study included 113 healthy individuals and 102 PD patients, with 26 early and 76 mid-advanced patients. Univariate analysis of variance screened out statistically significant differences among inflammatory markers Cys C and RANTES. The average Cys C level in the mid-advanced stage was significantly higher than in the early stage (p < 0.001) but not for RANTES (p = 0.740). The LASSO logistic regression model (λ.1se = 0.061) associated with UPDRS-I, UPDRS-II, UPDRS-III, HAMA, PDQ-39, and Cys C as the included independent variables revealed that the Model C discrimination and calibration (AUC = 0.968, Brier = 0.049) were superior to Model A (AUC = 0.926, Brier = 0.079) and Model B (AUC = 0.929, Brier = 0.071) models.
CONCLUSION: The study results show multiple factors are linked with PD assessment. Moreover, the inflammatory marker Cys C and transcranial sonography measurement could objectively predict PD symptom severity, helping doctors monitor PD evolution in patients while targeting interventions.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
CNS neuroscience & therapeutics - 30(2024), 3 vom: 01. März, Seite e14670 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lu, Yue [VerfasserIn] |
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| Links: |
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| Themen: |
9007-41-4 |
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| Anmerkungen: |
Date Completed 11.03.2024 Date Revised 12.03.2024 published: Print Citation Status MEDLINE |
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| doi: |
10.1111/cns.14670 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369493982 |
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| 245 | 1 | 4 | |a The severity assessment of Parkinson's disease based on plasma inflammatory factors and third ventricle width by transcranial sonography |
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| 500 | |a Date Revised 12.03.2024 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2024 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd. | ||
| 520 | |a BACKGROUND: Predicting Parkinson's disease (PD) can provide patients with targeted therapies. However, disease severity can be roughly evaluated in clinical practice based on the patient's symptoms and signs | ||
| 520 | |a OBJECTIVE: The current study attempted to explore the factors linked with PD severity and construct a predictive model | ||
| 520 | |a METHOD: The PD patients and healthy controls were recruited from our study center while recording their basic demographic information. The serum inflammatory markers levels, such as Cystatin C (Cys C), C-reactive protein (CRP), RANTES (regulated on activation, normal T cell expressed and secreted), Interleukin-10 (IL-10), and Interleukin-6 (IL-6) were determined for all the participants. PD patients were categorized into early and mid-advanced groups based on the Hoehn and Yahr (H-Y) scale and evaluated using PD-related scales. LASSO logistic regression analysis (Model C) helped select variables based on clinical scale evaluations, serum inflammatory factor levels, and transcranial sonography measurements. The optimal harmonious model coefficient λ was determined via 10-fold cross-validation. Moreover, Model C was compared with multivariate (Model A) and stepwise (Model B) logistic regression. The area under the curve (AUC) of a receiver operator characteristic (ROC), brier score, calibration curve, and decision curve analysis (DCA) helped determine the discrimination and calibration of the predictive model, followed by configuring a forest plot and column chart | ||
| 520 | |a RESULTS: The study included 113 healthy individuals and 102 PD patients, with 26 early and 76 mid-advanced patients. Univariate analysis of variance screened out statistically significant differences among inflammatory markers Cys C and RANTES. The average Cys C level in the mid-advanced stage was significantly higher than in the early stage (p < 0.001) but not for RANTES (p = 0.740). The LASSO logistic regression model (λ.1se = 0.061) associated with UPDRS-I, UPDRS-II, UPDRS-III, HAMA, PDQ-39, and Cys C as the included independent variables revealed that the Model C discrimination and calibration (AUC = 0.968, Brier = 0.049) were superior to Model A (AUC = 0.926, Brier = 0.079) and Model B (AUC = 0.929, Brier = 0.071) models | ||
| 520 | |a CONCLUSION: The study results show multiple factors are linked with PD assessment. Moreover, the inflammatory marker Cys C and transcranial sonography measurement could objectively predict PD symptom severity, helping doctors monitor PD evolution in patients while targeting interventions | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a LASSO logistic regression | |
| 650 | 4 | |a Parkinson's disease | |
| 650 | 4 | |a cystatin C | |
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| 700 | 1 | |a Xue, Xingya |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Jian |e verfasserin |4 aut | |
| 700 | 1 | |a Yan, Jiuqi |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Xiang |e verfasserin |4 aut | |
| 700 | 1 | |a Chang, Lei |e verfasserin |4 aut | |
| 700 | 1 | |a Zhao, Liang |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Bei |e verfasserin |4 aut | |
| 700 | 1 | |a Qiu, Chang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wenbin |e verfasserin |4 aut | |
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