Identifying biomarkers for predicting complications after surgery in inflammatory bowel disease
Official title: Spatially and Temporally Resolving Predictive Biomarkers of Postoperative Recurrence and Complications in Chronic Intestinal Inflammation
Run by IRCCS Ospedale San Raffaele · NCT06516341 · Data updated 2026-11-12
This study is trying to find specific markers in patients with inflammatory bowel disease after surgery to see if they can help predict complications and the chance of the disease coming back.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years to 69 Years |
| Sex | All |
| Enrollment | 35 (estimated) |
| Sponsor | IRCCS Ospedale San Raffaele Academic / other |
| Locations | 1 site (Milan, Italy) |
| Status | Recruiting |
| Started | February 27, 2025 |
| Main results expected | September 2025 |
| Study ends | September 2026 |
| Registry record updated | March 14, 2025 |
| Trial ID | NCT06516341 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include adults over 18 years with histologically confirmed Crohn's disease or ulcerative colitis undergoing intestinal resection due to stricturing disease.
✕Probably not a fit
Patients under 18 or over 70 years, those with unconfirmed diagnoses, or those with concurrent dysplasia or cancer may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study focuses on patients with inflammatory bowel disease (IBD) who require surgical intervention due to inadequate response to existing therapies. The researchers aim to identify and validate specific biomarkers that may remain in the resection margins after surgery, which could indicate the risk of postoperative complications and disease recurrence. By utilizing humanized experimental models and machine learning, the study seeks to develop a predictive model for these risks, although it will not alter clinical decision-making. Patients will continue to receive standard care while being monitored throughout the study.
Why it matters
Potential benefit: If successful, this study could lead to improved prediction of postoperative complications in IBD patients, potentially enhancing patient management and outcomes.
How similar studies have gone: While the approach of using machine learning for predictive modeling in IBD is innovative, similar studies have shown promise in identifying risk factors for postoperative complications in other contexts.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * adult (age \>18 years) patients with histologically confirmed CD or UC undergoing intestinal resection due to stricturing disease, regardless of their current or past medical treatment; * given that it is an observational study, also pregnant and breastfeeding patients could be included; * able and willing to sign the informed consent. Exclusion Criteria: * patients \<18 years or \> 70 years; * patients with unconfirmed both UC and CD diagnoses; * patients with superimposed dysplasia or cancer diagnosis and resections for which post- operative endoscopic assessment of recurrence is not feasible; * patients unable or unwilling to sign the informed consent.
Where it's running
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IRCCS Ospedale San Raffaele
Milan, Italy, Italy Recruiting
Study contacts
- Study coordinator: Pierpaolo Sileri, MD. PhD.
- Email: sileri.pierpaolo@hsr.it
- Phone: +39 0226436275
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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This study is testing if robotic surgery can be a good option for adults with inflammatory bowel disease, like Crohn's or ulcerative colitis, compared to traditional surgery methods.
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.