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.
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. During the first year, data related to demographics, lifestyle, laboratory and physical examinations will be collected at baseline, at 3 months and at 12 months. Patient Reported Outcomes (PROs), including voice recording will be collected optionally at different time points using the Colive smartphone app while physical activity and quality of sleep will be monitored optionally via a smartwatch. Additionally, participants will be asked to provide biological samples and imaging data (if performed as per standard of care) at different time points (baseline; 3 months; 12 months). A long-term Follow-up (FU) (starting from month 12 and up to 4 years after month 12) is foreseen in this study. During the long-term FU medical data are collected on a yearly basis, and PROs are collected every 6 months.
Study Type
OBSERVATIONAL
Enrollment
100
During the first year from the date of inclusion, data related to demographics, lifestyle, laboratory and physical examinations will be collected at baseline, at 3 months, and at 12 months. Patient-Reported Outcomes (PROs) with voice recordings will be collected at different time points in-between clinical visits using the Colive application. Participants will be asked to provide biological samples (i.e., blood, dried blood spots and stool are mandatory; saliva, urine and hair are optional), tissue samples from endoscopic biopsy and imaging data (if performed as per standard of care) at three timepoints (baseline; 3 months; 12 months). One unscheduled visit may be included in the study in case of occurrence of flare or treatment change.A long-term follow-up (starting from month 12 and up to 4 years after month 12) will include the collection of medical data on a yearly basis, collection of PROs with voice recording every 6 months and continuous collection of data using the smartwatch.
Centre Hospitalier de Luxembourg (CHL)
Luxembourg, Luxembourg
RECRUITINGIdentify 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
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.
Time frame: 2029
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.
Time frame: 2029
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