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Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson’s Disease Patients

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Abstract

Purpose

This 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.

Methods

An 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.

Results

The 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.

Conclusion

IRT is a powerful tool which enables to capture the heterogeneous nature of the MDS-UPDRS.

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Abbreviations

CV:

Coefficient of variation

EOT:

End of trial

IIV:

Inter-individual variability

IRT:

Item response theory

LRT:

Likelihood ratio test

MDS-UPDRS:

Movement Disorder Society UPDRS

MJFF:

Michael J. Fox Foundation

NONMEM:

NON-linear mixed effect model

PD:

Parkinson’s disease

PPMI:

Parkinson’s Progression Markers Initiative

RSE:

Relative standard error

SD:

Standard deviation

SIS:

Sum of item scores

SWEDD:

Scans without Evidence of Dopaminergic Deficit

UPDRS:

Unified Parkinson’s Disease Rating Scale

VPC:

Visual predictive check

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Authors and Affiliations

  1. Roche Pharma Research and Early Development, Clinical Pharmacology Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070, Basel, Switzerland

    Simon Buatois, Sylvie Retout & Nicolas Frey

  2. IAME, UMR 1137, INSERM, University Paris Diderot, Sorbonne Paris Cité, Paris, France

    Simon Buatois

  3. INSTITUT ROCHE, Roche S.A.S, 30, cours de l’île Seguin, 92650, Boulogne-Billancourt, France

    Simon Buatois & Sylvie Retout

  4. Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

    Sebastian Ueckert

Authors
  1. Simon Buatois
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  2. Sylvie Retout
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  3. Nicolas Frey
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  4. Sebastian Ueckert
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Correspondence to Simon Buatois.

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Buatois, S., Retout, S., Frey, N. et al. Item Response Theory as an Efficient Tool to Describe a Heterogeneous Clinical Rating Scale in De Novo Idiopathic Parkinson’s Disease Patients. Pharm Res 34, 2109–2118 (2017). https://doi.org/10.1007/s11095-017-2216-1

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  • DOI: https://doi.org/10.1007/s11095-017-2216-1

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