Efficacy of a Prediction Model-based Algorithm to PREVENT Drug-induced Impulse Control Disorders in Parkinson's Disease

Sponsor
Assistance Publique - Hôpitaux de Paris
Study ID
NCT07505394
Status
Not Yet Recruiting

Notify me when recruiting opens

Save your spot on the interest list for this study. We'll keep your details with this study so our team can follow up when recruiting opens.

Not yet recruiting

Add your contact details and location so we can keep your interest tied to this study.

Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Algorithm-guided group — DEVICE
    After the evaluation of the patient and the clinical inputs entered in the ICD SHIELD app including the planned choice of prescription by the neurologist for the next period, the clinician will receive the therapeutic approach recommended by the ICD SHIELD app depending on the output given by the algorithm. The clinician can repeat the use of the app if he/she plans to try various choice of prescription in the app if deemed necessary, but a single use is recommended at each visit. The neurologist will have to follow the recommendation of the ICD SHIELD app as much as possible unless judged inappropriate. The neurologist makes the final decision.
  • Standard of Care (SoC) group — BEHAVIORAL
    In the SoC arm the patient treatment will be adapted by the neurologistbased only on their clinical appreciation and international guidelines.

Study Details

Impulse control disorders and related behaviors (ICDRBs) are characterized by pathological gambling, compulsive shopping or eating, and hypersexuality, but other related behaviors have been described, e.g. hobbyism, and punding. ICDRBs are frequent in Parkinson's Disease (PD), affecting up to 50% of the patients after 5 years with major medical, social, and legal impact, with life changing consequences for patients and caregivers. The main risk factor is dopaminergic therapy, particularly the cumulative dose of dopamine agonists (DA). On the other hand, the dopaminergic therapy is necessary to control motor symptoms, and DA have demonstrated efficacy in delaying motor complications occurring in PD. Ideally, dopaminergic therapy would have to be adjusted to the individual risk of developing ICRDBs to maximize the benefit/risk ratio of each drug. However, despite several clinical risk factors associated with the risk of ICDRBs (in addition to the dopaminergic therapy), it is still not possible to predict their risk at the individual level, and not every patient treated with dopaminergic medications will develop ICDRBs. A machine learning algorithm to predict ICDRBs, based on clinical data, validated by cross-validation on independent replication cohorts has been developed. The PREVENT-ICD study proposes to test the efficacy of a new application, ICD-Shield, based on an algorithm to predict and prevent ICDs,in a multicenter randomized controlled trial to prevent ICDRBs in PD patients by proposing to the clinician treatment adjustment according to the risk predicted by the algorithm, as compared to the standard of care (SoC)

Key Dates

First listed
Apr 1, 2026
Start date
Jul 1, 2026
Status verified
Mar 2026
Primary completion
Jun 1, 2031
Completion
Jun 1, 2031

Study Design

Enrollment
528 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION

Arms

  • Experimental: Algorithm-guided group
    In the (algorithm-guided arm) the patient treatment will be adapted by the neurologist based on the algorithm output.
  • Other: Standard of Care (SoC) group
    In the SoC arm the patient treatment will be adapted by the neurologist based only on their clinical appreciation and international guidelines.

Primary Outcome Measure

Rate of patients with at least one clinically significant ICDRBs, i.e mild or above (any ASBPD score at 2 or above in any of the subcategories 3 to 5 and 7 to 10 of part IV) over the 3 year-follow up. [ Time Frame: over 3 years ]

Central Contacts

Find similar trials

Nationwide
Parkinson's disease trialsNeurology trialsBrain disorders trials

Related Studies