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| Name | Class |
|---|---|
| Alrijne Hospital | OTHER |
| Maasstad Hospital | OTHER |
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The proposed study will use a PROM (Patient report Outcome Measurement)-tool in combination with clinical and biochemical data to train and validate a Relapse Prediction Model for individual patients.
The primary objective is to train and validate a relapse prediction model for individual patients available for daily (remote) care management. Besides that, risk-based care pathways for different prediction outcomes will be evaluated, prediction scores will be correlated to medication type, CRP/Calprotectin and/or endoscopy, and with known IBD clinical risk profiles. Moreover dietary intake will be correlated with the IBD risk profiles.
Study design: Multicentre, retrospective analysis of two prospective cohorts. Study population: Adult IBD patients. Main study parameters/endpoints: The endpoint will be a prediction regarding step-up or step-down in the care pathways. In other words, the percentage of patients in each individual care pathway with agreement between risk score of the individual patient and actual flares during a follow-up time of 24 months. Furthermore insight will be gained in dietary patterns amongst patients with different IBD risk profiles.
No benefits or risks are associated with participating in this study, because only standard of care is given.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| training phase | The study procedures for both cohorts are the same. |
| |
| validation phase | The study procedures for both cohorts are the same. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention | Other | Patients will receive standard of care. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Develop a relapse prediction model for individual patients (agreement between risk score of the individual patient and actual flares) based on both clinical parameters and biochemical parameters in the individual care pathways. | This model will be based on both clinical parameters and biochemical parameters in the individual care pathways. | After 2 years |
| Validate the above mentioned prediction model and make it available for daily (remote) care management. | Based on the information form the validation cohort. The model will be validated retrospectively. | After 2 years |
| Measure | Description | Time Frame |
|---|---|---|
| evaluate risk-based care pathways for different prediction outcomes in clinical practice e.g. high intensity monitoring care pathway for patients with a high prediction score. | Evaluate whether predefined risk-based care pathways are in line with prediction outcomes of the relapse prediction model. | After 2 years |
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Inclusion Criteria:
Exclusion Criteria:
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In clinical practice, consecutive IBD patients in the LUMC, AH, and MH are registered on the platform and will be asked to participate in the current project. At least 200 UC patients and at least 200 CD patients will be included. Following inclusion, each patient will spend at least 12, but preferably 24 months on the platform.
Patients are already using the PROM-tool to allow remote monitoring; this has been implemented since 2021.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| L.J.M. Koppelman, Msc. | Contact | 0031715297902 | patientenibd@lumc.nl |
| Name | Affiliation | Role |
|---|---|---|
| A.E. van der Meulen - de Jong, MD, PhD | Leiden University Medical Centre | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Leiden University Medical Centre | Recruiting | Leiden | South Holland | 2300 RC | Netherlands |
| Type | Date | Date Unknown |
|---|---|---|
| Release | Dec 17, 2025 | |
| Reset | Jan 8, 2026 |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Dec 17, 2025 | Jan 8, 2026 |
| ID | Term |
|---|---|
| D010000 | Osteitis |
| ID | Term |
|---|---|
| D001847 | Bone Diseases |
| D009140 | Musculoskeletal Diseases |
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| Correlate the prediction scores of the different care pathways to medication type. |
See if there is a statistical correlation between medication type and prediction score |
| After 2 years |
| Correlate prediction scores of the different pathways with biomarkers CRP/Calprotectin and/or endoscopy | See if there is a statistical correlation between prediction score and biomarkers CRP/Calprotectin and/or endoscopy | After 2 years |
| Correlate prediction scores from the algorithm with known IBD clinical risk factors | See if there is a statistical correlation between prediction scores from the model to known clinical risk factors like e.g. operation history, presence of EIM. | After 2 years |
| Correlate dietary intake with the assigned IBD clinical risk profiles | See if there is a statistical correlation between dietary intake and assigned IBD clinical risk profile. | After 2 years |