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临床试验/NCT07280871
NCT07280871尚未招募不适用

Clinnova-MS: A Prospective Cohort Study of Patients With Multiple Sclerosis: A Trans-regional Digital Health Effort Unlocking the Potential of Artificial Intelligence and Data Science in Health Care

Luxembourg Institute of Health1 个研究点 分布在 1 个国家目标入组 100 人开始时间: 2026年6月1日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
尚未招募
入组人数
100
试验地点
1
主要终点
Identification of Clinical, Imaging, and Omics Signatures for MS Subtype Stratification

研究概览

简要总结

The Clinnova-Multiple Sclerosis (MS) study is part of the Clinnova program (NCT06526364; NCT06235684 and NCT05733702), which seeks to advance precision medicine and the digitalization of healthcare through high-quality, interoperable health data.

This program focuses on people with multiple sclerosis (MS) and aims to identify objective surrogate markers derived from clinical, epidemiological, imaging, and omics data that can predict disease activity, such as progression or relapses.

By combining data science and artificial intelligence, the project seeks to improve patient stratification, support personalized therapeutic decisions, and provide insights into the mechanisms underlying treatment response and disease progression.

Although many therapies are available for MS, it remains challenging to determine the most appropriate strategy for each patient and to prevent long-term disability. Current treatments mainly target relapses and inflammation, with limited effects on chronic progression. Clinnova-MS will collect and analyze real-world and research data to better understand variability in disease activity and treatment outcomes, enabling more precise, evidence-based care within the standard of care. This study represents the first step toward the broader Clinnova objective: developing sustainable, personalized, and preventive healthcare for people living with MS.

详细描述

Multiple sclerosis (MS) treatments have advanced substantially, yet selecting the most effective therapy and preventing long-term progression remain challenging because of the disease's heterogeneity and variable treatment responses. Current drugs mainly target relapses and inflammation, while only partially protecting against neurodegeneration. Identifying predictive and prognostic biomarkers and improving monitoring are key to more personalized, evidence-based MS care.

Clinnova-MS, part of the Clinnova program, is a prospective, observational cohort designed to explore objective markers of disease activity (progression or relapses) and treatment outcomes using clinical, imaging, molecular, digital, and patient-reported data. Artificial intelligence and data science will be applied to integrate information from sources such as MRI, deep molecular phenotyping, exposome data, Patient Reported Outcome Measures (PROMs)/Patient-Reported Experience Measures (PREMs), and connected devices.

Up to 800 participants with early MS, transitioning to progressive disease, or undergoing treatment change will be enrolled in France, Switzerland, Germany, and Luxembourg (about 100 at Centre Hospitalier du Luxembourg (CHL)). Participants will provide clinical data, biological samples (blood mandatory; other specimens optional), imaging (as per standard care), and digital health information. They will be followed for up to five years, with visits at baseline, 6 months (optional), 12 months, annual follow-up, and unscheduled visits if new symptoms or relapses occur.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Signed informed consent form
  • ≥ 18 years of age
  • Willing and able to comply with the protocol for the duration of the study including data and samples collection as well as study visits and examinations.
  • Diagnosed with MS according to the revised McDonald criteria 2017 or revised McDonald criteria 2024, all clinical forms inclusive (CIS, RRMS, SPMS, PPMS) AND early disease stages (< 3 years), OR presenting at hospital for evaluation of a change in therapy (flare) OR transitioning phase to progressive disease as evaluated based on EDSS.

排除标准

  • Diagnosis uncertain (no fulfilment of inclusion criteria)
  • Any condition that could potentially hamper the compliance with the study protocol, including study procedures and study visits such as mental disability that makes it difficult or impossible to answer questionnaires.
  • Not fluent in any of the following languages: French, English or German.
  • Known pregnancy before the inclusion into the study

研究组 & 干预措施

Single Arm Study

Patients with MS

干预措施: Cohort (Other)

结局指标

主要结局

Identification of Clinical, Imaging, and Omics Signatures for MS Subtype Stratification

时间窗: 1 year

Identify clinical, epidemiological, imaging and omics characteristics associated with changes of status for different subtypes of MS patients allowing the stratification of these patients according to similar patterns and disease courses.The primary endpoint will be the change of status of the patients' disease between the baseline and at Year 1. The status of the disease will be determined by using the No Evidence of Disease Activity (NEDA MS- 3).

次要结局

  • Building Resources and Digital Tools to Advance Research and Healthcare in Multiple Sclerosis(1 year)

研究者

申办方类型
Other Gov
责任方
Sponsor

研究点 (1)

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