International audiencePURPOSE: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 estimat...
Using machine learning, we developed a statistical progression model of early Parkinson’s disease th...
OBJECTIVES: Developing disease modifying therapies for Parkinson's disease (PD) calls for outcome me...
Objective: To analyze the change in health-related quality-of-life (HRQoL) in patients with Parkinso...
International audiencePURPOSE:This manuscript aims to precisely describe the natural disease progres...
In the current work, we present the methodology for development of an Item Response Theory model wit...
Abstract Item response theory (IRT) has been recently adopted to successfully characterize the progr...
Purpose: The aim of this work was to allow combination of information from recent and historical tri...
BACKGROUND: Indices of physical function may have a hierarchy of items. In cases where this can be d...
In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effe...
Parkinson's disease is the second most common neurological disease and affects about 1% of persons o...
International audienceINTRODUCTION:In this paper, we studied the effect over time of agomelatine, an...
Parkinson’s disease is the second most common neurological disease and affects about 1% of persons o...
International audiencePatients with idiopathic Parkinson’s Disease (iPD) may have very different pat...
Using machine learning, we developed a statistical progression model of early Parkinson’s disease th...
OBJECTIVES: Developing disease modifying therapies for Parkinson's disease (PD) calls for outcome me...
Objective: To analyze the change in health-related quality-of-life (HRQoL) in patients with Parkinso...
International audiencePURPOSE:This manuscript aims to precisely describe the natural disease progres...
In the current work, we present the methodology for development of an Item Response Theory model wit...
Abstract Item response theory (IRT) has been recently adopted to successfully characterize the progr...
Purpose: The aim of this work was to allow combination of information from recent and historical tri...
BACKGROUND: Indices of physical function may have a hierarchy of items. In cases where this can be d...
In this study, we report the development of the first IRT model within a NLME (Non Linear Mixed Effe...
Parkinson's disease is the second most common neurological disease and affects about 1% of persons o...
International audienceINTRODUCTION:In this paper, we studied the effect over time of agomelatine, an...
Parkinson’s disease is the second most common neurological disease and affects about 1% of persons o...
International audiencePatients with idiopathic Parkinson’s Disease (iPD) may have very different pat...
Using machine learning, we developed a statistical progression model of early Parkinson’s disease th...
OBJECTIVES: Developing disease modifying therapies for Parkinson's disease (PD) calls for outcome me...
Objective: To analyze the change in health-related quality-of-life (HRQoL) in patients with Parkinso...