ArticlePharmaceutical research2017
Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson's Disease Patients.
Article in Pharmaceutical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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The trial behind it
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Who cites it
33 citing papers in PubMed.
- Item response theory in early phase clinical trials: Utilization of a reference model to analyze the Montgomery-Åsberg Depression Rating Scale.CPT: pharmacometrics & systems pharmacology · 2023Trial
- Detecting placebo and drug effects on Parkinson's disease symptoms by longitudinal item-score models.CPT: pharmacometrics & systems pharmacology · 2021Trial
- Application of Item Response Theory to Model Disease Progression and Agomelatine Effect in Patients with Major Depressive Disorder.The AAPS journal · 2019Trial
- An item response theory based integrated model of headache, nausea, photophobia, and phonophobia in migraine patients.Journal of pharmacokinetics and pharmacodynamics · 2018Trial
- A Pharmacometric Analysis of Patient-Reported Outcomes in Breast Cancer Patients Through Item Response Theory.Pharmaceutical research · 2018Trial
- Longitudinal Evaluation of an Abbreviated Patient-Reported Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) for Predicting Dopaminergic Therapy Initiation in Early Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Integrated Modeling of Digital-Motor and Clinician-Reported Outcomes Using Item Response Theory: Towards Powerful Trials for Rare Neurological Diseases.CPT: pharmacometrics & systems pharmacology · 2025Observational
- Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.CPT: pharmacometrics & systems pharmacology · 2025Article
- The Potential of Disease Progression Modeling to Advance Clinical Development and Decision Making.Clinical pharmacology and therapeutics · 2025Review
- Comparison of the power and type 1 error of total score models for drug effect detection in clinical trials.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Sparse item testing of clinical scales in neurology trials to alleviate burden to patients.Journal of neurology · 2024Article
- Item performance of the scale for the assessment and rating of ataxia in rare and ultra-rare genetic ataxias.CPT: pharmacometrics & systems pharmacology · 2024Article
- Prediction of Individual Disease Progression Including Parameter Uncertainty in Rare Neurodegenerative Diseases: The Example of Autosomal-Recessive Spastic Ataxia Charlevoix Saguenay (ARSACS).The AAPS journal · 2024Article
- Validation of the RBD Symptom Severity Scale in the North American Prodromal Synucleinopathy Consortium.Neurology · 2024Article
- Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models.The AAPS journal · 2024Article
- Modeling of Parkinson's Disease Progression and Implications for Detection of Disease Modification in Treatment Trials.Journal of Parkinson's disease · 2024Article
- Patient feasibility as a novel approach for integrating IRT and LCA statistical models into patient-centric qualitative data-a pilot study.Frontiers in digital health · 2024Article
- Application of longitudinal item response theory models to modeling Parkinson's disease progression.CPT: pharmacometrics & systems pharmacology · 2022Article
- Dissecting the Domains of Parkinson's Disease: Insights from Longitudinal Item Response Theory Modeling.Movement disorders : official journal of the Movement Disorder Society · 2022Article
- Novel Approach to Movement Disorder Society-Unified Parkinson's Disease Rating Scale Monitoring in Clinical Trials: Longitudinal Item Response Theory Models.Movement disorders clinical practice · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis manuscript aims to precisely describe the natural disease progression of Parkinson's disease (PD) patients and evaluate approaches to increase the drug effect detection power.
methodsAn item response theory (IRT) longitudinal model was built to describe the natural disease progression of 423 de novo PD patients followed during 48 months while taking into account the heterogeneous nature of the MDS-UPDRS. Clinical trial simulations were then used to compare drug effect detection power from IRT and sum of item scores based analysis under different analysis endpoints and drug effects.
resultsThe IRT longitudinal model accurately describes the evolution of patients with and without PD medications while estimating different progression rates for the subscales. When comparing analysis methods, the IRT-based one consistently provided the highest power.
conclusionIRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.
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