Disease progression subtypes of Parkinson's disease based on milestone events.

ABSTRACT

BACKGROUND: Parkinson's disease (PD) demonstrates considerable heterogeneity in the manifestation of clinical symptoms and disease progression. Recently, six clinical milestones have been proposed to evaluate disease severity in PD. However, the identification of PD progression subtypes based on these milestone events has not yet been performed. METHODS: Latent class analysis (LCA) was employed to identify subtypes of PD progression based on the timing of the first occurrence of six milestones within a 6-year follow-up period in Parkinson's Progression Markers Initiative (PPMI) database. RESULTS: The study cohort consisted of 354 early PD patients, of whom 42.9% experienced at least one milestone within six years. LCA identified two distinct subtypes of PD progression slow progression (83%) and rapid progression (17%). The total number of milestones over six years was significantly higher in the rapid progression subtype compared to the slow progression subtype (median 3.00 vs. 0.00, p < 0.001). At baseline, the rapid progression subtype, compared to the slow progression subtype, was characterized by an older age at onset and more severe motor and non-motor symptoms. On biomarkers, the rapid progression subtype demonstrated elevated CSF p-tau and serum NFL, but decreased mean striatal DAT uptake. Five clinical variables (age, SDMT score, MDS-UPDRS I score, MDS-UPDRS II + III scores, and RBD) were selected to construct the predictive model. The original predictive model achieved an AUC of 0.82. In internal validation using bootstrap resampling, the model achieved an AUC of 0.82, with a 95%CI ranging from 0.76 to 0.87. The model's performance was acceptable regarding both calibration and clinical utility. CONCLUSION: Approximately 17% of early PD patients exhibited the rapid progression subtype, characterized by the occurrence of more and earlier-onset milestones. The nomogram predictive model, incorporating five baseline clinical variables (age, SDMT score, MDS-UPDRS I score, MDS-UPDRS II + III scores, RBD), serves as a valuable tool for prognostic counseling and patient selection in PD clinical trials.