A Screening Program to Improve the Early Detection of Sporadic Pancreatic Cancer in Individuals With a High-Risk of Developing Pancreatic Cancer (AI-PACED)

Mayo Clinic

Status: Begins enrollment in 1 month

Conditions: Pancreatic Ductal Adenocarcinoma

Treatments: Procedure: Biospecimen Collection; Procedure: Computed Tomography with Contrast; Other: Electronic Health Record Review

Study type: Interventional

Funder types: Other

Identifiers

NCT07324096

NCI-2025-09279 (Registry Identifier)

25-009433 (Other Identifier)

MC250406 (Other Identifier)

Details and patient eligibility

About

This clinical trial studies a new screening program to improve the early detection of sporadic pancreatic cancer in individuals with a high risk of developing pancreatic cancer. Pancreatic cancer remains one of the deadliest solid tumors, characterized by a long phase without symptoms followed by rapid progression once clinically evident. Despite advancements in treatment, the survival rate for pancreatic cancer remains low. Research has helped to identify a subset of individuals with a markedly high short-term risk for developing pancreatic cancer, which includes adults aged 50 and older with glycemically-defined new-onset diabetes and an Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) score ≥ 3. However, current practice guidelines do not provide clear pathways for surveillance or early detection. The screening program in this trial combines repeated contrast-enhanced computed tomography (CT) scans using artificial intelligence (AI) and blood draws. Contrast-enhanced CT is an imaging technique which creates a series of detailed pictures of areas inside the body; the pictures are created by a computer linked to an x-ray machine and a contrast agent is used to enhance the images. The images are then reviewed using AI, which may make it easier to spot cancer earlier on the CT scans than with the human eye. Studying samples of blood in the laboratory from high-risk individuals may help doctors understand more about why they may develop pancreatic cancer. This may be an effective way to screen high-risk individuals and improve the early detection of sporadic pancreatic cancer.

Enrollment: 100 estimated patients

Sex: All

Ages: 50 to 85 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age ≥ 50 and ≤ 85 years
• Glycemically-defined new-onset diabetes (gNOD) with onset ≤ 180 days preceding enrollment
• Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) score ≥ 3, based on validated risk stratification models
• Provide written or remote informed consent

Exclusion criteria

• Prior diagnosis of pancreatic ductal adenocarcinoma (PDA)
• Known hereditary cancer syndromes (e.g., BRCA1/2, Lynch syndrome, Peutz-Jeghers)
• Prior history of pancreatic surgery
• Pancreatic cyst surveillance at time of registration
• Contraindications to contrast-enhanced CT imaging per standard clinical practice at time of registration

Trial design

Primary purpose: Diagnostic

Allocation: Non-Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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100 participants in 3 patient groups

Group A1 (CT, blood, EMR surveillance)

Experimental group

Description:

Patients undergo contrast-enhanced abdominal CT and blood sample collection at baseline, 6 months, and 12 months in the absence of unacceptable toxicity. Patients also undergo EMR surveillance for PDA diagnosis for up to 36 months.

Treatment:

Other: Electronic Health Record Review

Procedure: Computed Tomography with Contrast

Procedure: Biospecimen Collection

Group A2 (blood, EMR surveillance)

Experimental group

Description:

Patients undergo blood sample collection at baseline, 6 months, and 12 months in the absence of unacceptable toxicity. Patients also undergo EMR surveillance for PDA diagnosis for up to 36 months.

Treatment:

Other: Electronic Health Record Review

Procedure: Biospecimen Collection

Group B (EMR surveillance)

Active Comparator group

Description:

Patients undergo EMR surveillance for PDA diagnosis for up to 36 months.

Treatment:

Other: Electronic Health Record Review