Parkinson's disease; predictive modeling; diagnostic delay; diverse symptoms; non-motor symptoms; gait impairment; disease progression; early diagnosis; neurodegeneration; model-based approach; longitudinal data; patient-reported time to diagnosis; clinical trials; disease-modifying treatments; latent time joint mixed-effects model; LTJMM; clinical symptoms; PPMI; ICEBERG; LuxPARK; demographic factors; clinical manifestations; disease timescale; motor scores; non-motor scores; cohorts
Abstract :
[en] PD patients present with diverse symptoms, complicating timely diagnosis. We analyzed 1124 PD trajectories using a novel model-based approach to estimate whether diagnosis was early or late compared to cohort averages. Higher age, specific non-motor symptoms, and fast disease progression were linked to later diagnosis, while gait impairment led to earlier diagnosis. Our findings are in line with a biological definition of PD that extends beyond classical motor symptoms.
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group)
Disciplines :
Neurology Human health sciences: Multidisciplinary, general & others Biotechnology Life sciences: Multidisciplinary, general & others
Author, co-author :
Hähnel, T.
Raschka, T.
Klucken, J.
GLAAB, Enrico ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Biomedical Data Science
Corvol, J.-C.
Falkenburger, B.H.
Fröhlich, H.
External co-authors :
yes
Language :
English
Title :
Predictive modeling to uncover Parkinson s disease characteristics that delay diagnosis
