Randomizing patients, and changing the care itself — a nationwide trial that hands colorectal surgery risk assessment to AI — a clinical trial (ClinicalTrials.gov)
A researcher-initiated trial across Danish hospitals randomizing 1,200 patients scheduled for curative colorectal cancer surgery to risk assessment by a surgeon using standard methods or by a surgeon with AI assistance. Because the level of perioperative care follows from the assessed risk, the AI output reaches the care patients actually receive.
Trial overview (primary data)
- StatusRecruiting
- ConditionsColo-rectal Cancer
- InterventionsDEVICE: AI augmented risk-stratification, OTHER: Expert-based Risk-stratification
- SponsorZealand University Hospital
- Target enrollment1,200 participants
- Period2025-10-24 〜 2028-02-01
Key points
- A researcher-initiated trial randomizing 1,200 patients scheduled for curative colorectal cancer surgery to standard or AI-assisted risk assessment across Danish hospitals.
- Because the intensity of perioperative care follows the assessed risk level, the AI output reaches the care the patient receives rather than staying in a report.
- The primary hypothesis is more efficient and economic care without a deterioration in outcomes, not improvement in outcomes.
- All patients receive standard treatment under national guidelines, with the modality of risk assessment as the only difference between groups.
- The record gives the number of hospitals as seven in one passage and eight in another, so any quoted figure should be checked against the source passage.
1Not assisting a reading, but changing the care received
Most trials of medical AI measure how well an image is read or how often a diagnosis lands. This one touches what comes after. Patients scheduled for curative colorectal cancer surgery are randomized to have their risk assessed by a surgeon in the standard way or by a surgeon working with AI assistance, and the level of perioperative care then follows from the assessed risk.
The AI output does not stay in a report; it reaches the care the patient actually receives.
2What changes on the other side of the allocation
- 1Risk assessmentA surgeon assesses risk by standard methods, or with artificial-intelligence assistance
- 2StratificationPatients are separated by the assessed level of risk
- 3Allocation of careThe intensity of perioperative management follows that level
- 4Outcomes and resourcesCheck whether allocation grew more efficient without worsening complications or death
The primary hypothesis, as recorded, is more efficient and economic care without a deterioration in outcomes. Not improvement, but a change in allocation that does no harm, and that phrasing captures the character of the trial. Intensive perioperative care is finite; hand it to everyone and it runs out. What is being evaluated is a tool for deciding who to concentrate it on.
3How much this rung carries
Roughly a fifth of the clinical trials held here mention randomization. Most of those compare readings, or the way advice is presented; a design in which the allocation changes the treatment a patient receives sits at the heavier end.
That the record states all patients receive standard treatment under national guidelines, with the assessment modality as the only difference between groups, is the other side of that same weight.
4One caution in reading the record
The body of the registration states the number of participating hospitals as seven in one place and eight in another. Registrations are revised over time, and discrepancies between passages can survive. When a figure is quoted, it is safer to confirm which passage it came from.
The record also notes that the preceding pilot suggested reductions in complications, hospital stays and readmissions, but that is the pilot, not a result of this trial.
Why it matters
A design in which the allocation changes the treatment a patient receives carries more responsibility than most AI evaluations. Framing the hypothesis as changed allocation without deterioration, rather than as improved outcomes, answers the practical question of where limited resources should go. For anyone measuring the effect of a deployment, the choice of primary hypothesis here is worth studying.
FAQ
Does the AI decide the operation?
Why is the hypothesis no deterioration rather than improvement?
Are results available?
Sources (primary)
Source: ClinicalTrials.gov (U.S. NIH/NLM, public domain). This site does not provide medical advice. Verify the latest and exact details with the official source. This site is not endorsed or certified by the NIH/NLM.
- ClinicalTrials.gov (study record, original)
- NCT ID: NCT06645015