Classification of long-term clinical course of Parkinson’s disease using clustering algorithms on social support registry database

Although Parkinson’s disease (PD) has a heterogeneous disease course, it remains challenging to establish subtypes. We described and clustered the natural course of Parkinson’s disease (PD) with respect to functional disability and mortality. This retrospective cohort study utilized the Korean National Health Insurance Service database, which contains the social support registry database for patients with PD. We extracted patients newly diagnosed with PD in 2009 and followed them up until the end of 2018. Functional disability was assessed based on the long-term care insurance (LTCI) and National Disability Registry data. Further, we measured all-cause mortality during the observation period. We included 2944 eligible patients. The surviving patients were followed up for 113.7 ± 3.3 months. Among the patients who died, patients with and without disability registration were followed up for 61.4 ± 30.1 and 43.2 ± 32.0 months, respectively. The cumulative survival rate was highest in cluster 1 and decreased from Cluster 1 to Cluster 6. In the multivariable Cox regression analysis, the defined clusters were significantly associated with increased long-term mortality (adjusted hazard ratio [aHR], 3.440; 95% confidence interval [CI], 3.233–3.659; p