Uncovering Clinical Characteristics of Parkinson’s Disease Patients with Delayed Diagnosis Through Predictive Modeling#

Authors#

Tom Hähnel, Tamara Raschka, Jochen Klucken, Enrico Glaab, Jean-Christophe Corvol, Björn Falkenburger, Holger Fröhlich

Abstract#

Background: People with Parkinson’s disease (PwPD) present with a variety of motor and non-motor symptoms, and a more biological definition of Parkinson’s disease is poised to expand the diagnostic spectrum beyond the stereotypical “elderly male with tremor”. This heterogeneity can potentially pose a challenge for an accurate and early diagnosis. Objectives: To determine whether demographic or initial clinical characteristics systematically affect the time till diagnosis by modeling large-scale longitudinal cohort data. Methods: Using multimodal data from three large longitudinal PD cohorts and a latent time joint mixed-effects model (LTJMM), we aligned the disease courses of individual PwPD and estimated whether individual PD diagnosis was early or late compared to the average time of PD diagnosis in each cohort. Moreover, we modeled progression of several clinical scores over time using linear, binary and ordinal mixed-effects models to estimate the initial clinical manifestations of PwPD at the typical time of PD diagnosis. Results: We included 1,124 PwPD in our analysis. The median patient-reported time to diagnosis was 1.0 years and was not associated with any clinical or demographic factors. Yet, several clinical and demographic factors were associated with a later-than-average diagnosis of PD in our model-based approach: higher age (P<0.0001), tremor dominance (P=0.0005), rapid progression (P=0.039), anxiety (P=0.0043), autonomic symptoms (P=0.0019), depression (P=0.0004), fatigue (P=0.012), pain (P=0.0085), sleep problems (P=0.0043) and in general more non-motor symptoms (P=0.0006) at initial manifestation. In contrast, more severe postural and gait disturbance was associated with an earlier-than-average PD diagnosis (P=0.0004). Sex, family history of PD and predominantly affected side did not impact the time of PD diagnosis. Conclusions: Using statistical modeling, we were able to study initial clinical characteristics of PwPD even in the absence of directly observable clinical data at the time when PD is diagnosed typically. Our findings are consistent with a biological definition of PD that includes patients who present initially with non-motor symptoms.