2-[2-[3-[4-(2-(18F)FLUORANYLETHOXY)PHENYL]-7-METHYL-4-OXOQUINAZOLIN-2-YL]ETHYL]-4-PROPAN-2-YLOXYISOINDOLE-1,3-DIONE for Huntington's disease|Pre-symptomatic Huntington's disease|Symptomatic Huntington's disease

Inclusion criteria

• {"criterion_text":"- For all participants: - Age ≥18 years and ≤65 years; - Information and collection of written consent; - Affiliation with a social security plan, beneficiary or beneficiary's right"}
• {"criterion_text":"- For Healthy volunteers (control): - UHDRS functional score TFC = 13; - Motor UHDRS score TMS < 6; - With no known genetic disease and no direct relationship to an HD patient or family ancestors carrying the HD mutation (or knowing their genetic status with CAG < 36)"}
• {"criterion_text":"- For Symptomatic huntington's disease patients: - Number of GACs ≥ 40; - CAP score ≥ 250; - 10 ≤ TFC ≤ 13; - TMS >5 if TFC=13; - Diagnostic confidence level =4; - Age of onset of disease > 20 years ; - Patient physically able to sign consent"}
• {"criterion_text":"- For Pre-symptomatic Huntington's disease patients: - Number of GACs ≥ 40; - CAP score ≥250; - TFC = 13; - TMS < 6; - Patient physically able to sign consent"}

Exclusion criteria

• {"criterion_text":"- Participant under guardianship or curatorship"}
• {"criterion_text":"- Neurological or psychiatric disorder unrelated to HD"}
• {"criterion_text":"- Intercurrent illness that may impact participant's performance"}
• {"criterion_text":"- Chronic progressive neurological disease"}
• {"criterion_text":"- Claustrophobia"}
• {"criterion_text":"- Brain injury unrelated to HD"}
• {"criterion_text":"- Pacemaker, intracorporeal metal, intracerebral clip, any metallic foreign body: implantable cardiac electronic device such as pacemakers, implantable cardioverter defibrillators etc., metallic intraocular foreign bodies, implantable neurostimulation systems, cochlear implants/ear implants, drug infusion pumps (insulin administration, analgesic drugs), or chemotherapy pumps): if possible, the patient should remove the device."}
• {"criterion_text":"- 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"}
• {"criterion_text":"- Known hypersensitivity to the radiopharmaceutical preparation (excipients in the radiopharmaceutical preparation)"}
• {"criterion_text":"- Pregnant or breastfeeding woman"}
• {"criterion_text":"- 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."}
• {"criterion_text":"- Person participating or having participated in a research protocol with a radiopharmaceutical injection for less than 12 months."}
• {"criterion_text":"- Person under state medical aid"}
• {"criterion_text":"- Person deprived of liberty"}

Primary endpoints

• {"endpoint_text":"- The primary endpoint will be effect size, assessed by the standardized mean difference (Cohen's d) for each biomarker between the values measured initially and their assessment at 2-year follow-up.","definition_or_measurement_approach":"Effect size measured by the standardized mean difference (Cohen's d) comparing baseline values and values at 2-year follow-up for each biomarker."}

Secondary endpoints

• {"endpoint_text":"- Analysis of patient profiles and progression trajectories, taking into account all available data at D0, M1, M1 bis, M12, M24 and M24 bis, will be based on socio-demographic characteristics, as well as initial clinical and paraclinical scores and their evolution over time. Clustering analyses will use statistical validation indices to determine the optimal number of clusters and provide information on cluster quality.","definition_or_measurement_approach":"Clustering analyses across timepoints (D0, M1, M1 bis, M12, M24, M24 bis) using socio-demographic, clinical and paraclinical scores; statistical validation indices to determine optimal clusters and assess cluster quality."}
• {"endpoint_text":"- Identification of the best biomarkers predicting an unfavorable disease course will be carried out using conventional regression and machine learning methods. Discrimination and calibration performances will be systematically evaluated and compared for each of the models constructed.","definition_or_measurement_approach":"Use of conventional regression and machine learning methods to identify predictive biomarkers; models evaluated for discrimination and calibration performance and compared."}

France

Earliest CTIS Part Ii Submission Date

07-10-2024

Latest Decision Or Authorization Date

17-09-2025

Processing Time Days

345

Number Of Sites

4

Number Of Participants

100

Primary sponsor

Full Name

Assistance Publique Hopitaux De Paris

Organisation Type

Hospital/Clinic/Other health care facility

Country Of Registered Address

France