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Psychometric Properties of Clinical Indicators for Identification and Management of Advanced Parkinson’s Disease : Real-World Evidence From G7 Countries

Antonini, Angelo ; Pahwa, Rajesh ; Odin, Per LU orcid ; Henriksen, Tove ; Soileau, Michael J. ; Rodriguez-Cruz, Ramon ; Isaacson, Stuart H. ; Merola, Aristide ; Lindvall, Susanna and Domingos, Josefa , et al. (2022) In Neurology and Therapy 11(1). p.303-318
Abstract

Introduction: Standardized and validated criteria to define advanced Parkinson’s disease (PD) or identify patient eligibility for device-aided therapy are needed. This study assessed the psychometric properties of clinical indicators of advanced PD and eligibility for device-aided therapy in a large population. Methods: This retrospective analysis of the Adelphi Parkinson’s Disease Specific Programme collected data from device-aided therapy-naïve people with PD in G7 countries. We assessed the presence of 15 clinical indicators of advancing PD and seven indicators of eligibility for device-aided therapy in patients classified with advanced PD or as eligible for device-aided therapy by the treating physician. Accuracy was assessed using... (More)

Introduction: Standardized and validated criteria to define advanced Parkinson’s disease (PD) or identify patient eligibility for device-aided therapy are needed. This study assessed the psychometric properties of clinical indicators of advanced PD and eligibility for device-aided therapy in a large population. Methods: This retrospective analysis of the Adelphi Parkinson’s Disease Specific Programme collected data from device-aided therapy-naïve people with PD in G7 countries. We assessed the presence of 15 clinical indicators of advancing PD and seven indicators of eligibility for device-aided therapy in patients classified with advanced PD or as eligible for device-aided therapy by the treating physician. Accuracy was assessed using area under the curve (AUC) and multivariable logistic regression models. Construct validity was examined via known-group comparisons of disease severity and burden among patients with and without each clinical indicator. Results: Of 4714 PD patients, 14.9% were classified with advanced PD and 17.5% as eligible for device-aided therapy by physician judgment. The presence of each clinical indicator was 1.9- to 7.3-fold more likely in patients classified with advanced PD. Similarly, the presence of device-aided therapy eligibility indicators was 1.8- to 5.5-fold more likely in patients considered eligible for device-aided therapy. All indicators demonstrated high clinical screening accuracy for identifying advanced PD (AUC range 0.84–0.89) and patients eligible for device-aided therapy (AUC range 0.73–0.80). The Unified Parkinson’s Disease Rating Scale (UPDRS) score, cognitive function, quality of life, and caregiver burden were significantly worse in indicator-positive patients. Conclusion: Specific clinical indicators of advanced PD and eligibility for device-aided therapy demonstrated excellent psychometric properties in a large sample, and thus may provide an objective and reliable approach for patient identification and treatment optimization.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Accuracy, Advanced Parkinson’s disease, Clinical indicators, Device-aided therapy eligibility, Validity
in
Neurology and Therapy
volume
11
issue
1
pages
303 - 318
publisher
Springer Healthcare
external identifiers
  • scopus:85122748277
  • pmid:35015215
ISSN
2193-8253
DOI
10.1007/s40120-021-00313-9
language
English
LU publication?
yes
id
9aa67bf7-1fad-4a4e-a174-9b03c117e1e5
date added to LUP
2022-02-18 15:19:00
date last changed
2024-07-02 07:20:49
@article{9aa67bf7-1fad-4a4e-a174-9b03c117e1e5,
  abstract     = {{<p>Introduction: Standardized and validated criteria to define advanced Parkinson’s disease (PD) or identify patient eligibility for device-aided therapy are needed. This study assessed the psychometric properties of clinical indicators of advanced PD and eligibility for device-aided therapy in a large population. Methods: This retrospective analysis of the Adelphi Parkinson’s Disease Specific Programme collected data from device-aided therapy-naïve people with PD in G7 countries. We assessed the presence of 15 clinical indicators of advancing PD and seven indicators of eligibility for device-aided therapy in patients classified with advanced PD or as eligible for device-aided therapy by the treating physician. Accuracy was assessed using area under the curve (AUC) and multivariable logistic regression models. Construct validity was examined via known-group comparisons of disease severity and burden among patients with and without each clinical indicator. Results: Of 4714 PD patients, 14.9% were classified with advanced PD and 17.5% as eligible for device-aided therapy by physician judgment. The presence of each clinical indicator was 1.9- to 7.3-fold more likely in patients classified with advanced PD. Similarly, the presence of device-aided therapy eligibility indicators was 1.8- to 5.5-fold more likely in patients considered eligible for device-aided therapy. All indicators demonstrated high clinical screening accuracy for identifying advanced PD (AUC range 0.84–0.89) and patients eligible for device-aided therapy (AUC range 0.73–0.80). The Unified Parkinson’s Disease Rating Scale (UPDRS) score, cognitive function, quality of life, and caregiver burden were significantly worse in indicator-positive patients. Conclusion: Specific clinical indicators of advanced PD and eligibility for device-aided therapy demonstrated excellent psychometric properties in a large sample, and thus may provide an objective and reliable approach for patient identification and treatment optimization.</p>}},
  author       = {{Antonini, Angelo and Pahwa, Rajesh and Odin, Per and Henriksen, Tove and Soileau, Michael J. and Rodriguez-Cruz, Ramon and Isaacson, Stuart H. and Merola, Aristide and Lindvall, Susanna and Domingos, Josefa and Alobaidi, Ali and Jalundhwala, Yash J. and Kandukuri, Prasanna L. and Parra, Juan Carlos and Kukreja, Pavnit K. and Onuk, Koray and Bergmann, Lars and Pike, James and Ray Chaudhuri, K.}},
  issn         = {{2193-8253}},
  keywords     = {{Accuracy; Advanced Parkinson’s disease; Clinical indicators; Device-aided therapy eligibility; Validity}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{303--318}},
  publisher    = {{Springer Healthcare}},
  series       = {{Neurology and Therapy}},
  title        = {{Psychometric Properties of Clinical Indicators for Identification and Management of Advanced Parkinson’s Disease : Real-World Evidence From G7 Countries}},
  url          = {{http://dx.doi.org/10.1007/s40120-021-00313-9}},
  doi          = {{10.1007/s40120-021-00313-9}},
  volume       = {{11}},
  year         = {{2022}},
}