Prediction of STN DBS Motor Response in PD

NCT04093908 | Completed

• 1 other identifier: 2019-0739-A9
• Study Type: observational
• Target: 322
• Locations: 1 country
• Sites: 1

Brief Summary

Despite careful patient selection for subthalamic nucleus deep brain stimulation (STN DBS), some Parkinson's disease (PD) patients show limited improvement of motor disability. Non-conclusive results and the lack of a practical implantable prediction algorithm from previous prediction studies maintain the need for a simple tool for neurologists that provides a reliable prediction on postoperative motor improvement for individual patients. In this study, a prior developed prediction model for motor response after STN DBS in PD patients is validated. The model generates individual probabilities for becoming a weak responder one year after surgery. The model will be validated in a validation cohort collected from several international centers. The predictive model is made public accessible before data collection on: https://github.com/jgvhabets/DBSPREDICT

Conditions

Parkinson Disease

Keywords

deep brain stimulation; motor outcome; prediction model; machine learning; Subthalamic nucleus

Outcome Measures

Primary Outcomes (4)

• area under the curve of the receiver operator curve

  Motor outcome is categorised in a binary outcome variable. The model will predict to which outcome group the patient will belong one-year postoperatively. The primary outcome measure is the performance of the predicted outcome categories with the actual outcome categories. Performance of prediction models is expressed as area under the curve of the receiver operator curve, predictive accuracy, true positive prediction rate, and false positive prediction rate.

  one-year postoperative

• predictive accuracy

  See description primary outcome 1.

  one-year postoperative

• true positive prediction rate

  See description primary outcome 1.

  one-year postoperative

• false positive prediction rate

  See description primary outcome 1.

  one-year postoperative

Study Arms (1)

multi-center validation cohort

We collect retrospective data from several international centers containing preoperative variables (demographical and clinical) and postoperative outcome (UPDRS II, III, IV) one year postoperatively, and merge these data to one validation cohort.

Other: Prediction of motor outcome after STN DBS based on preoperative variables

Interventions

Prediction of motor outcome after STN DBS based on preoperative variables OTHER

Generating individual probabilities for motor response based on preoperative variables

multi-center validation cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

One cohort consisting of PD patients who underwent STN DBS in several international centers.

You may qualify if:

• underwent STN DBS for Parkinson's disease
• completed one year follow up after surgery

You may not qualify if:

• \- missing data in postoperative UPDRS II, III, IV

Sponsors & Collaborators

• Maastricht University Medical Center: lead

Study Sites (1)

MaastrichtUMC

Maastricht, Limburg, 6229 AZ, Netherlands

Location

MeSH Terms

Conditions

Parkinson Disease

Condition Hierarchy (Ancestors)

Parkinsonian Disorders; Basal Ganglia Diseases; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Movement Disorders; Synucleinopathies; Neurodegenerative Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 17, 2019
• First Posted: September 18, 2019
• Study Start: August 1, 2019
• Primary Completion: December 17, 2019
• Study Completion: December 17, 2019
• Last Updated: September 1, 2020

Record last verified: 2020-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ANALYTIC CODE
• Time Frame: After data collection and analysis.
• Access Criteria: Data can be made available on request.

Locations

NL (1)