Modeling the Heterogeneity and Trajectories of Cognitive Dysfunction in Parkinson's Disease Using Partially Ordered Set (POSET) Models
Zweber, C.; Cholerton, B.; Ryan, A.; Zabetian, C.; Miller, R.; Iyer, V.; Hiller, A.; Sahoo, S. S.; Tatsuoka, C.; Gupta, D. K.
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Traditional binary classifications of Parkinsons disease (PD) cognitive dysfunction fail to capture its inherent heterogeneity. This study introduces the Partially Ordered Set (POSET) model, a Bayesian framework, to analyze cognitive trajectories using Parkinsons Progression Markers Initiative (PPMI) data. Five cognitive domains: Attention, Visuospatial Judgement, Executive Functioning, Working Memory, and Episodic Memory, were mapped onto nine neuropsychological measures to calculate Cognitive Performance Scores (CPS). Of 264 patients without baseline cognitive dysfunction, 21.7% developed dysfunction by Year 3. These individuals exhibited significantly lower median CPS across all domains during follow up visits in Years 1-3. Notably, baseline Attention and Visuospatial CPS were significant predictors of future impairment, with an area under the curve (AUC) of 0.782; a specificity of 91.3%, and a sensitivity or 35.7%. POSET modeling provides a sophisticated approach to characterizing PD cognitive decline, offering greater granularity than conventional schemes. Further large-cohort studies are needed to confirm these findings.
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