Abstract

Background/Objective: To synchronize data collection, the National Institute of Neurological Disorders and Stroke (NINDS) recommended Common Data Elements (CDEs) for use in Parkinson's disease (PD) research. This study delineated the progression patterns of these CDEs in a cohort of PD patients. Methods: One hundred-twenty-five PD patients participated in the PD Biomarker Program (PDBP) at Penn State. CDEs, including MDS-Unified PD Rating Scale (UPDRS)-total, questionnaire-based non-motor (-I) and motor (-II), and rater-based motor (-III) subscales; Montreal Cognitive Assessment (MoCA); Hamilton Depression Rating Scale (HDRS); University of Pennsylvania Smell Identification Test (UPSIT); and PD Questionnaire (PDQ-39) were obtained at baseline and three annual follow-ups. Annual change was delineated for PD or subgroups [early=PDE, disease duration (DD) <1y; middle=PDM, DD=1-5y; and late=PDL, DD>5y] using mixed effects model analyses. Results: UPDRS-total, -II, and PDQ-39 scores increased significantly, and UPSIT decreased, whereas UPDRS-I, -III, MoCA, and HDRS did not change, over 36 months in the overall PD cohort. In the PDE subgroup, UPDRS-II increased and UPSIT decreased significantly, whereas MoCA and UPSIT decreased significantly in the PDM subgroup. In the PDL subgroup, UPDRS-II and PDQ-39 increased significantly. Other metrics within each individual subgroup did not change. Sensitivity analyses using subjects with complete data confirmed these findings. Conclusion: Among CDEs, UPDRS-total, -II, PDQ-39, and UPSIT all are sensitive metrics to track PD progression. Subgroup analyses revealed that these CDEs have distinct stage-dependent sensitivities, with UPSIT for DD<5y, PDQ-39 for DD>5y, UPDRS-II for early (DD<1) or later stages (DD>5).

Original languageEnglish (US)
Pages (from-to)1075-1085
Number of pages11
JournalJournal of Parkinson's Disease
Volume10
Issue number3
DOIs
StatePublished - 2020

All Science Journal Classification (ASJC) codes

  • Clinical Neurology
  • Cellular and Molecular Neuroscience

Fingerprint Dive into the research topics of 'Clinical Progression of Parkinson's Disease: Insights from the NINDS Common Data Elements'. Together they form a unique fingerprint.

Cite this