Pancreatic cancer is one of the most fatal malignancies with a 5-year survival rate of only \~6%\[1\]. The reasons for this high mortality rate can be attributed to several factors, of which perhaps the most important is delayed diagnosis due to vague symptoms and consequently missed opportunities for surgical resection. Therefore, the ability to detect pancreatic cancer at an early, more curable stage is urgently needed.
Identifying risk factors and biomarkers of early pancreatic cancer could facilitate screening for individuals at higher than average risk and expedite the diagnosis in individuals with symptoms and substantially improve an individual's chance of surviving the disease. Thus, the investigators propose this longitudinal study entitled, "Artificial Intelligence-based Early Screening of Pancreatic Cancer and High Risk Tracing (ESPRIT-AI)" in order to generate clinical data sets and bank serial blood specimens of high risk individuals.
Subject is able and willing to provide informed consent and sign an informed consent form.
Subject or authorized representative must be willing to complete a detailed questionnaire.
New onset diabetes (diagnosed within the past 3 years)
Familial pancreatic cancer
Subject has been diagnosed with pancreatic cancer or other malignant tumors in the last 5 years;
Subject has any medical condition that contraindicates high-resolution MRI or CT;
Subject cannot be followed up or is participating in other clinical trials.
High risk individuals of pancreatic cancer
Cohort
Prospective
high-resolution MRI/CT examinations
Diagnostic testParticipants will undergo annual questionnaire survey, laboratory tests and high-resolution MRI/CT examinations of the pancreas. Any suspicious lesions will be further examined by endoscopic ultrasound (EUS).
Incidence
Determine incidence of pancreatic cancer or precursor lesions among high risk individuals.
Hazard ratio (HR)
Assesses the influence of risk factors on the incidence of pancreatic cancer or precursor lesions among high risk individuals.
Survival time
Calculate survival time from point of diagnosis and treatment among the identified patients with pancreatic cancer.
HR
Assesses the influence of risk factors on survival time among the identified patients with pancreatic cancer.
Diagnostic yield
Determine diagnostic yield (sensitivity, specificity, positive/negative predictive value and accuracy) of AI-based surveillance program to predict early stage pancreatic cancer.
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