Background: Initiation of symptomatic therapy in Parkinson disease is a disease progression milestone, and its prediction is important. Previous studies were limited in duration and number of variables included in their predictive models.

Objectives: To identify predictors of time to initiation of symptomatic therapy in patients with PD not on treatment, using a large pool of candidate variables from the Parkinson's Progression Markers Initiative dataset, analyzed at ten years.

Methods: Kaplan Meier survival curve was used to estimate time to initiation of symptomatic treatment. Potential predictors included 33 baseline clinical, imaging, biofluid, and genetic biomarkers. Univariate Cox regression was used for variable selection, significant predictors subsequently entering a multivariate Cox proportional hazard model, which was further reduced using the Akaike Information Criterion into a final reduced model.

Results: Of 425 participants with Parkinson's Disease, 406 initiated symptomatic therapy at last follow up. The outcome was censored for 4.5% of the sample. The risk of initiating symptomatic therapy was 65% (95%CI 60-70%) within the first year from enrollment. Predictors included dopamine transporter SPECT, the Movement Disorders Society Unified Parkinson Disease Rating Scale, and anxiety (State Trait Anxiety Inventory).

Conclusions: Baseline dopamine transporter SPECT specific binding ratio was found to be the most impactful predictor for time to initiation of symptomatic therapy in this 10-year follow up analysis of the Progressive Parkinson Markers Initiative cohort, when treatment status was known for 95.5% of the sample.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.parkreldis.2023.105796DOI Listing

Publication Analysis

Top Keywords

initiation symptomatic
20
symptomatic therapy
20
time initiation
16
parkinson disease
12
symptomatic treatment
8
initiative cohort
8
10-year follow
8
markers initiative
8
predictors included
8
dopamine transporter
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!