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临床试验/NCT05733702
NCT05733702招募中不适用

A Prospective Cohort Study of Patients With Inflammatory Bowel Disease: 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: 2024年2月1日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
100
试验地点
1
主要终点
Identify clinical, epidemiological and omics characteristics associated with IBD activity triggering a treatment change in patients with UC or CD and allow the phenotyping of patients with similar characteristics

研究概览

简要总结

This study is part of the Clinnova program. This is a prospective cohort study including patients with IBD recruited at the time of a treatment change.

At least 800 participants (recruited in France, Germany and Luxembourg) will be enrolled, of which 100 participants are expected to be recruited in Luxembourg with the present study protocol.

The mission of Clinnova is to support the digitalization of healthcare and precision medicine by creating a data-enabling environment for accessing, sharing and analyzing interoperable, high-quality health data.

The main hypothesis is that treatment change decided by clinicians is predictable using objective surrogate markers derived from clinical, epidemiological, and omics data. Identifying these objective markers may facilitate future treatment decisions, provide new insights on the molecular causes for differential treatment response, pathogenesis and progression, and potential pointers for improved personalized therapeutic interventions.

详细描述

Due to the complexity and heterogeneity of IBD, personalized treatment should be implemented in the management of patients.

In particular, the patient stratification by their predicted response to different drugs and the stratification of patients by predicted disease course, which might result in the use of more or less aggressive treatment approaches, are the major unmet clinical needs that should be addressed.

In this context, key unmet needs that can be addressed by data science and Artificial Intelligence (AI) include:

  1. Identification of predictive biomarkers for drug response estimation and identification of prognostic biomarkers to estimate the future course of the disease, focusing on patients in whom treatment needs to be changed.
  2. Improved monitoring of patient well-being.

Patients deemed eligible for the study will be asked to provide data and samples for collection and analysis. They will be followed up for a maximum of 5 years starting from the date of inclusion.

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

  • ≥ 18 years old
  • Participants are willing and able to comply with the protocol including undergoing data and sample collection as well as study visits and examinations.
  • Signed informed consent form
  • Diagnosed with Inflammatory bowel disease, either Crohn's disease or ulcerative colitis, at least 3 months before the enrolment AND occurrence of a significant change in the treatment of the disease (either change of drug dosage OR change of medication within the same treatment class OR change of treatment class OR addition of a drug to a treatment regimen already ongoing). A change of drug dosage or frequency is considered significant if it fulfills the requirements in section 7.1 Note: Patients with ostomy or with short bowel syndrome can be included if they fulfill all the eligibility criteria

排除标准

  • 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

结局指标

主要结局

Identify clinical, epidemiological and omics characteristics associated with IBD activity triggering a treatment change in patients with UC or CD and allow the phenotyping of patients with similar characteristics

时间窗: 2029

The main hypothesis is that treatment change decided by clinicians is predictable using objective surrogate markers derived from clinical, epidemiological and omics data Identifying these objective markers may facilitate future treatment decisions, provide new insights on the molecular causes for differential treatment response, pathogenesis and progression, and potential pointers for improved personalized therapeutic interventions.

次要结局

  • Identify clinical, epidemiological and omics characteristics associated with IBD individual patient outcome. Establish a sample and data bank to enable research on IBD. Develop applications for improved interaction between patients and medical doctors.(2029)

研究者

申办方类型
Other Gov
责任方
Sponsor

研究点 (1)

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