AI model could spot hidden pancreatic cancer in chronic pancreatitis patients
NCT ID NCT07045181
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study tested a computer model (XGBoost) to predict whether suspicious spots on CT scans in people with chronic pancreatitis are cancerous. Researchers analyzed data from 113 patients to see how accurate the model was. The goal is to help doctors make better decisions without needing surgery right away.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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113 people
The number who actually took part.
- Started
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Jul 2025
- Finished
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Aug 2025
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Chronic pancreatitis patients who has indeterminate focal pancreatic lesions discovered through contrast-enhanced CT scans
- Ages
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Children (under 18), adults (18 to 64) and older adults (65 and over)
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
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Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * Diagnosis of chronic pancreatitis * Patients has indeterminate focal pancreatic lesions discovered through contrast-enhanced CT scans Exclusion Criteria: * Patients had incomplete clinical data * Patients had no surgical pathology results for the focal pancreatic lesions and loss to follow-up, indicating that a final diagnosis of the focal pancreatic lesions could not been established
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Changhai Hospital
Shanghai, Shanghai Municipality, 200433, China
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Other studies related to the condition(s) this trial covers.
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