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Abstract Details

Leveraging patient-reported outcomes to discern mobility trajectories in Parkinson’s disease
Movement Disorders
P10 - Poster Session 10 (8:00 AM-9:00 AM)

Mobility impairments are common, complex symptoms experienced by PWP. The underlying mechanisms and accrual patterns are not well understood, which impedes therapeutic shared-decision making.

To characterize subgroups of persons with Parkinson’s disease (PWP) with similar longitudinal mobility impairment patterns based on an easy-to-use patient-reported outcome (PRO) measure.

Latent class growth analysis (LCGA) uses finite mixture models to estimate discrete groups of trajectory parameters using maximum likelihoods. Using longitudinal data available through Fox Insight Data Exploration Network, LCGA was applied to 16,863 PWP stratified by early (N=8612; <3 years), mid (N=6181; 3-10 years) and later (N=2070; >10 years) disease duration spanning ~4.5 years, to empirically discern clusters of PWP with similar longitudinal mobility impairment patterns. Mobility impairment was measured using a generic health-related quality of life tool that has shown construct validity in PWP (EuroQol 5 dimensions [EQ-5D-5L] mobility component). Associations were evaluated between latent trajectory classes and sociodemographic/clinical factors.

In the early and mid-disease duration strata, four clusters were identified, while a fifth cluster was identified in the later disease duration strata. The subgroup trajectories ranged from none to moderate mobility problems, with a smaller cluster of subjects with severe mobility problems. The percentage of subjects with moderate (early=17.5%, mid=26.4%, later=32.5%) and severe (early=3.8%, mid=7.4%, later=15.4%) mobility problems at baseline increased across disease duration groups. The trajectories tended to be variable or slightly worsening in the early and later duration group and more stable in the mid-duration group. Across strata, the clusters with moderate to severe mobility problems were associated with more severe impairment, depression, anxiety and arthritis, higher BMI, lower income, and lower education. There were no differences by race.

The approach described and applied to PWP provides a novel template for using a easy-to-use PRO to improve our understanding of mobility trajectories in Parkinson’s disease.

Farren Briggs, PhD (University of Miami Miller School of Medicine)
The institution of Prof. Briggs has received research support from NIH. The institution of Prof. Briggs has received research support from Michael J. Fox Foundation.
Doug Gunzler Doug Gunzler has received publishing royalties from a publication relating to health care.
Steven Alexander Gunzler, MD, FAAN (Parkinson's and Movement Disorders Ctr, University Hospitals) Dr. Gunzler has received research support from NIH/NINDS. The institution of Dr. Gunzler has received research support from Biogen. The institution of Dr. Gunzler has received research support from Amneal. Dr. Gunzler has received research support from Michael J Fox Foundation.