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Innovative Imaging and cognitive BIOmarkers to predict Huntington’s Disease progression

Innovative Imaging and cognitive BIOmarkers to predict Huntington’s Disease progression - I2BIO-HD

Status
Not yet recruiting
Phases
Phase 3
Study type
Interventional
Source
EU CTR
Registry ID
EUCTR2021-004141-20-FR
Enrollment
100
Registered
2022-05-24
Start date
2022-08-10
Completion date
Unknown
Last updated
2024-10-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Patients with Huntington's disease : symptomatic (HD) and pre-symptomatic (pre-HD). MedDRA version: 20.0 Level: PT Classification code 10070668 Term: Huntington's disease System Organ Class: 10010331 - Congenital, familial and genetic disorders

Interventions

Product Name: [18F]-MNI-659 Product Code: [18F]-MNI-659 Pharmaceutical Form: Solution for injection

Sponsors

ASSISTANCE-PUBLIQUE HOPITAUX DE PARIS (AP-HP)
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: - Age 18-65 - Information and collection of written consent - Affiliation to a social security scheme, beneficiary or beneficiary Controls: - TFC (Total Functional Capacity) = 13 - TMS (Total Motor Score ) 5 if TFC=13 - Diagnostic confidence level =4 - Age onset of disease > 20 years - Patients physically able to sign Presymptomatic preMH patients: - Number of CAG = 40 - CAP score =250 - TFC = 13 - TMS =65 years) no F.1.3.1 Number of subjects for this age range

Exclusion criteria

Exclusion criteria: - Participant under guardianship or curatorship - Neurological or psychiatric disorder unrelated to HD - Intercurrent illness that may impact participants' performance - Progressive chronic neurological disease - Claustrophobia - Brain damage not related to HD - Pacemaker, intracorporeal metal, intracerebral clip - Catheters with metal components (Swan-Ganz catheter), metal fragments such as bullets, shotgun pellets and metal shrapnel, cerebral artery aneurysm clips, magnetic dental implants, tissue expander, artificial limb, hearing aid, piercing such as pacemaker - Known hypersensitivity to the radiopharmaceutical preparation (excipients in the radiopharmaceutical preparation) - Pregnant or breastfeeding woman - Person under AME - Person deprived of liberty - Person participating or having participated in an interventional study for less than 3 months or without time limit in a trial of neural transplants or gene therapy. - Person participating or having participated in a research protocol with injection of a radiopharmaceutical for less than 12 months.

Design outcomes

Primary

MeasureTime frame
Main Objective: Define a multidomain composite score to measure the clinical evolution of patients, from the presymptomatic stages, in the context of clinical trials;Secondary Objective: 1) Identify patient profiles and HD progression trajectories (unsupervised analyses); 2) Identify the best predictive biomarkers, individually or in combination, and establish their prognostic value on disease progression (supervised analyses).;Primary end point(s): The construction of the composite score will be based on a sequential approach, aiming to i) calculate for each candidate measure the longitudinal evolution in absolute and relative value and in terms of effect size; ii) select the measures with the largest effect sizes (i.e. Cohen’s d) in HD and preMH patients, as well as evolutions significantly different from those observed in controls; iii) carry out a principal component analysis (PCA) on the basis of the best individual scores previously identified in order to define a composite score, a linear combination of the individual variables. The candidate measures for constructing the composite score will include measures related to cognition, motor skills, functional status, mood, behaviors and paraclinical imaging parameters.;Timepoint(s) of evaluation of this end point: period of 23 months compared to Month 1

Secondary

MeasureTime frame
Secondary end point(s): 1) The analysis of patient progression profiles and trajectories will be based on socio-demographic characteristics, as well as on initial clinical and paraclinical scores and their evolution over time. The clustering analyzes will be based on statistical validation indices in order to determine the optimal number of clusters and inform on the quality of the groupings. 2) The identification of the best predictive biomarkers of an unfavorable progression of the disease will be carried out using conventional regression and machine learning methods. The discrimination and calibration performances will be systematically evaluated and compared for each of the models built. ;Timepoint(s) of evaluation of this end point: Month 1,Month 12 ans Month 24

Countries

France

Contacts

Public Contactproject Manager

Assistance Publique - Hôpitaux Paris - Direction de la Recherche Clinique et de l'Innovation

candy.estevez@aphp.fr13344841747

Outcome results

None listed

Source: EU CTR (via WHO ICTRP) · Data processed: Feb 4, 2026