Novel Approach to Movement Disorder Society-Unified Parkinson's Disease Rating Scale Monitoring in Clinical Trials: Longitudinal Item Response Theory Models.

Bayesian modeling Parkinson's disease clinimetrics disease progression longitudinal data

Journal

Movement disorders clinical practice
ISSN: 2330-1619
Titre abrégé: Mov Disord Clin Pract
Pays: United States
ID NLM: 101630279

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 04 06 2021
revised: 05 07 2021
accepted: 09 07 2021
entrez: 11 10 2021
pubmed: 12 10 2021
medline: 12 10 2021
Statut: epublish

Résumé

Although nontremor and tremor Part 3 Movement Disorder Society-Unified Parkinson's Disease Rating Scale items measure different impairment domains, their distinct progression and drug responsivity remain unstudied longitudinally. The total score may obscure important time-based and treatment-based changes occurring in the individual domains. Using the unique advantages of item response theory (IRT), we developed novel longitudinal unidimensional and multidimensional models to investigate nontremor and tremor changes occurring in an interventional Parkinson's disease (PD) study. With unidimensional longitudinal IRT, we assessed the 33 Part 3 item data (22 nontremor and 10 tremor items) of 336 patients with early PD from the STEADY-PD III (Safety, Tolerability, and Efficacy Assessment of Isradipine for PD, placebo vs. isradipine) study. With multidimensional longitudinal IRT, we assessed the progression rates over time and treatment (in overall motor severity, nontremor, and tremor domains) using Markov Chain Monte Carlo implemented in Stan. Regardless of treatment, patients showed significant but different time-based deterioration rates for total motor, nontremor, and tremor scores. Isradipine was associated with additional significant deterioration over placebo in total score and nontremor scores, but not in tremor score. Further highlighting the 2 separate latent domains, nontremor and tremor severity changes were positively but weakly correlated (correlation coefficient, 0.108). Longitudinal IRT analysis is a novel statistical method highly applicable to PD clinical trials. It addresses limitations of traditional linear regression approaches and previous IRT investigations that either applied cross-sectional IRT models to longitudinal data or failed to estimate all parameters simultaneously. It is particularly useful because it can separate nontremor and tremor changes both over time and in response to treatment interventions.

Sections du résumé

BACKGROUND BACKGROUND
Although nontremor and tremor Part 3 Movement Disorder Society-Unified Parkinson's Disease Rating Scale items measure different impairment domains, their distinct progression and drug responsivity remain unstudied longitudinally. The total score may obscure important time-based and treatment-based changes occurring in the individual domains.
OBJECTIVE OBJECTIVE
Using the unique advantages of item response theory (IRT), we developed novel longitudinal unidimensional and multidimensional models to investigate nontremor and tremor changes occurring in an interventional Parkinson's disease (PD) study.
METHOD METHODS
With unidimensional longitudinal IRT, we assessed the 33 Part 3 item data (22 nontremor and 10 tremor items) of 336 patients with early PD from the STEADY-PD III (Safety, Tolerability, and Efficacy Assessment of Isradipine for PD, placebo vs. isradipine) study. With multidimensional longitudinal IRT, we assessed the progression rates over time and treatment (in overall motor severity, nontremor, and tremor domains) using Markov Chain Monte Carlo implemented in Stan.
RESULTS RESULTS
Regardless of treatment, patients showed significant but different time-based deterioration rates for total motor, nontremor, and tremor scores. Isradipine was associated with additional significant deterioration over placebo in total score and nontremor scores, but not in tremor score. Further highlighting the 2 separate latent domains, nontremor and tremor severity changes were positively but weakly correlated (correlation coefficient, 0.108).
CONCLUSIONS CONCLUSIONS
Longitudinal IRT analysis is a novel statistical method highly applicable to PD clinical trials. It addresses limitations of traditional linear regression approaches and previous IRT investigations that either applied cross-sectional IRT models to longitudinal data or failed to estimate all parameters simultaneously. It is particularly useful because it can separate nontremor and tremor changes both over time and in response to treatment interventions.

Identifiants

pubmed: 34631944
doi: 10.1002/mdc3.13311
pii: MDC313311
pmc: PMC8485609
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1083-1091

Subventions

Organisme : NIA NIH HHS
ID : R01 AG064803
Pays : United States

Informations de copyright

© 2021 The Authors. Movement Disorders Clinical Practice published by Wiley Periodicals LLC. on behalf of International Parkinson and Movement Disorder Society.

Déclaration de conflit d'intérêts

The research of Sheng Luo was supported by National Institute on Aging (Grant R01AG064803). The Rush Parkinson's Disease and Movement Disorders Program is a designated Clinical Center of Excellent supported by the Parkinson Foundation. The authors have no conflicts of interest to report.

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Auteurs

Sheng Luo (S)

Department of Biostatistics and Bioinformatics Duke University Durham North Carolina USA.

Haotian Zou (H)

Department of Biostatistics University of North Carolina at Chapel Hill Chapel Hill North Carolina USA.

Christopher G Goetz (CG)

Department of Neurological Sciences, Section of Movement Disorders Rush University Medical Center Chicago Illinois USA.

Dongrak Choi (D)

Department of Biostatistics and Bioinformatics Duke University Durham North Carolina USA.

David Oakes (D)

University of Rochester Medical Center Department of Biostatistics and Computational Biology Rochester New York USA.

Tanya Simuni (T)

Parkinson's disease and Movement Disorders Center Northwestern University Medical Center Chicago Illinois USA.

Glenn T Stebbins (GT)

Department of Neurological Sciences, Section of Movement Disorders Rush University Medical Center Chicago Illinois USA.

Classifications MeSH