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This study is a multi-center, observational study aiming at developing a machine learning-based early detection model using prospectively collected liquid biopsy samples from clinically-annotated individuals.
Full description
Peripheral blood samples from participants with new diagnosis of pancreatic cancers will be collected to characterize the cancer-specific circulating signals by sequencing cell free DNA. A noninvasive test integrating machine learning algorithm will be trained and validated through a two-stage approach in recruited well-classified individuals, along with non-cancers without clinical diagnosis of cancer after routine medical screening. The performance of liquid biospy assays discovering cancer from non-cancer will be evaluated in participants with benign disease as well as average risk individuals.
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Cancer Arm
Inclusion Criteria:
Exclusion Criteria:
Benign Disease Arm
Inclusion Criteria:
Exclusion Criteria:
276 participants in 2 patient groups
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Central trial contact
Si Shi, M.D., Ph.D.; Xian-Jun Yu, M.D., Ph.D.
Data sourced from clinicaltrials.gov
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