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Early Diagnosis of Pancreatic Cancer Via Deciphering Multi-modal Immunological Signatures

NCT06495749 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 3000

Last updated 2024-07-16

No results posted yet for this study

Summary

Prospective inclusion of 1000 patients with pancreatic cancer (early-stage pancreatic cancer accounts for approximately 75% of cases), 1000 patients with benign pancreatic diseases, and 1000 healthy individuals as controls. Peripheral blood samples were collected from newly diagnosed pancreatic cancer patients and healthy individuals. Using techniques such as plasma TCR/BCR-seq, CyTOF, and plasma proteomics, multi-modal individual immune characteristics were obtained and analyzed along with clinical information. An artificial intelligence predictive model was built based on these multi-modal individual immune characteristics to establish an early screening technique for pancreatic cancer. The sensitivity and specificity of this artificial intelligence model for early pancreatic cancer diagnosis were evaluated using an external multicenter sample test set.

Conditions

  • Pancreatic Cancer Resectable

Sponsors & Collaborators

  • The Affiliated Hospital of the Chinese Academy of Military Medical Sciences

    collaborator OTHER

  • Nanjing Medical University

    collaborator OTHER

  • Zhejiang University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-08-01
Primary Completion
2027-01-01
Completion
2027-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06495749 on ClinicalTrials.gov