New insights into Parkinson’s disease through statistical analysis of standard clinical scales quantifying symptom severity

Clinical research studies in Parkinson's Disease (PD) focusing on symptom assessment often rely on thorough time-consuming physical examinations quantified on clinical scales such as the Unified Parkinson's Disease Rating Scale (UPDRS). Although widely used in clinical research, realistic time constraints preclude its use in daily clinical practice. The Hoehn and Yahr (H&Y) staging is an alternative scale which is easier to administer and provides a succinct descriptor of overall PD severity. There is no universal agreement amongst neurologists on the specific PD symptoms they need to be assessing in order to prescribe treatments and optimize symptom management for their patients, and practically there are no clinical scales which are recorded in daily clinical practice. In this study, we systematically evaluate diverse symptoms (as expressed in 44 UPDRS items) and aim to provide a statistical association with UPDRS and H&Y using rank correlation and mutual information metrics. Moreover, we investigate the projection of a UPDRS item subset on a 2D plot to map onto H&Y. We report some statistically strong correlations of PD symptoms against UPDRS and H&Y (|R| ≥ 0.3), and provide an intuitively appealing visualization mapping onto H&Y. These findings may be useful to neurologists as practical guidance in their daily clinical routine.