ArticleCPT: pharmacometrics & systems pharmacology2025
Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.
Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores from the Parkinson's Progression Markers Initiative, three different models of varying complexity, (total score, item response theory (IRT) and artificial neural network (ANN)) were evaluated to determine their ability to differentiate between PD and SWEDDs. Each of the models provided as output a predicted probability of having PD (P
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