Dataset Information

Item response theory analysis of the Clinical Dementia Rating.

ABSTRACT:

Introduction

The Clinical Dementia Rating (CDR) is widely used in Alzheimer's disease research studies and has well established reliability and validity. To facilitate the development of an online, electronic CDR (eCDR) for more efficient clinical applications, this study aims to produce a shortened version of the CDR, and to develop the statistical model for automatic scoring.

Methods

Item response theory (IRT) was used for item evaluation and model development. An automatic scoring algorithm was validated using existing CDR global and domain box scores as the reference standard.

Results

Most CDR items discriminate well at mild and very mild levels of cognitive impairment. The bi-factor IRT model fits best and the shortened CDR still demonstrates very high classification accuracy (81%∼92%).

Discussion

The shortened version of the CDR and the automatic scoring algorithm has established a good foundation for developing an eCDR and will ultimately improve the efficiency of cognitive assessment.

SUBMITTER: Li Y

PROVIDER: S-EPMC8016711 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Item response theory analysis of the Clinical Dementia Rating.

Li Yan Y Xiong Chengjie C Aschenbrenner Andrew J AJ Chang Chih-Hung CH Weiner Michael W MW Nosheny Rachel L RL Mungas Dan D Bateman Randall J RJ Hassenstab Jason J Moulder Krista L KL Morris John C JC

Alzheimer's & dementia : the journal of the Alzheimer's Association 20201120 3

<h4>Introduction</h4>The Clinical Dementia Rating (CDR) is widely used in Alzheimer's disease research studies and has well established reliability and validity. To facilitate the development of an online, electronic CDR (eCDR) for more efficient clinical applications, this study aims to produce a shortened version of the CDR, and to develop the statistical model for automatic scoring.<h4>Methods</h4>Item response theory (IRT) was used for item evaluation and model development. An automatic scor ...[more]

PMID: 33215873

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Project description:BackgroundAlthough 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.ObjectiveUsing 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.MethodWith 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.ResultsRegardless 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).ConclusionsLongitudinal 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.

Dataset Information

Item response theory analysis of the Clinical Dementia Rating.

Introduction

Methods

Results

Discussion

Publications

Item response theory analysis of the Clinical Dementia Rating.

Similar Datasets

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