Unique ID issued by UMIN | UMIN000053882 |
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Receipt number | R000061507 |
Scientific Title | Clinical Study of Pancreatic Cancer Diagnostic Performance Using Machine Learning Model with Urinary Biomarkers |
Date of disclosure of the study information | 2024/03/18 |
Last modified on | 2024/04/30 09:17:22 |
Clinical Study of Pancreatic Cancer Diagnostic Performance Using Machine Learning Model with Urinary Biomarkers
Clinical Study of Pancreatic Cancer Diagnostic Performance Using Machine Learning Model with Urinary Biomarkers
Clinical Study of Pancreatic Cancer Diagnostic Performance Using Machine Learning Model with Urinary Biomarkers
Clinical Study of Pancreatic Cancer Diagnostic Performance Using Machine Learning Model with Urinary Biomarkers
Japan |
Pancreatic cancer, pancreatic cancer high-risk patients
Hepato-biliary-pancreatic medicine | Hepato-biliary-pancreatic surgery | Laboratory medicine |
Malignancy
NO
1. Performance evaluation of a pancreatic cancer prediction model based on miRNA profiles
We will evaluate the diagnostic performance of our prediction model for pancreatic cancer based on miRNA profiles obtained from comprehensive measurements of miRNAs extracted from urine samples of pancreatic cancer patients, non-pancreatic cancer (high-risk pancreatic cancer) patients and healthy adults, and clinical information obtained during routine medical care.
2. Evaluation of the performance of the prediction model for pancreatic cancer based on DNA methylation patterns
We will evaluate the diagnostic performance of the predictive model for pancreatic cancer based on DNA methylation patterns obtained from comprehensive measurement of cfDNA extracted from urine samples of pancreatic cancer patients, non-pancreatic cancer (high-risk pancreatic cancer) patients, and healthy adults, as well as clinical information obtained in the usual medical practice.
Others
Exploratory analysis of other biomarkers in urine
We will measure and analyze other biomarkers (nucleic acids, proteins, metabolites, urine qualitative analysis, etc.) extracted from urine samples of pancreatic cancer patients, non-pancreatic cancer (high-risk pancreatic cancer) patients, and healthy adults, and by correlating them with clinical information obtained during routine medical care, we will improve the risk prediction performance of miSignal for pancreatic cancer, and develop new biomarkers combining them.
Confirmatory
Others
Not applicable
Using the predictive model or biomarker constructed to classify pancreatic cancer and non-pancreatic cancer (pancreatic cancer high-risk) groups, the following will be evaluated.
(1) Sensitivity, specificity, positive predictive value, negative predictive value, and positive diagnostic value for pancreatic cancer
(2) Sensitivity to pancreatic cancer by stage
(3) Sensitivity to pancreatic cancer by tumor size
(4) Comparison with sensitivity, specificity, positive predictive value, negative predictive value, and positive diagnostic value of each test item (including imaging tests) in the participants of this study
(5) Comparison with the sensitivity and specificity of each test item (including imaging tests) in previous reports
(6) Sensitivity, specificity, and positive predictive value for pancreatic cancer in multiple prediction models
(7) Sensitivity, specificity, and positive diagnostic rate for pancreatic cancer in each of the other subpopulations
(8) Sensitivity, specificity, and positive diagnostic rate for pancreatic cancer when combined with other test items
Observational
18 | years-old | <= |
Not applicable |
Male and Female
Pancreatic Cancer Patients:
To qualify for this study, individuals must meet criteria (1) through (5):
(1) Japanese nationals aged 18 years or older at the time of signing the consent form.
(2) Written consent, approved by the Ethical Review Committee of the respective research institution, can be obtained from the individual or their surrogate, based on their free will.
(3) Diagnosis of invasive pancreatic ductal carcinoma (PDAC) or suspected intraductal papillary mucinous carcinoma (IPMC) with scheduled surgery.
(4) Blood samples collected within the past 90 days used to measure CA19-9.
(5) No prior treatment for invasive PDAC or suspected IPMC at the time of consent.
Non-Pancreatic Cancer (Pancreatic Cancer High-Risk) Patients:
To be eligible for this study, individuals must meet criteria (1) through (4):
(1) Japanese nationals aged 18 years or older at the time of signing the consent form.
(2) Written consent, based on their or their surrogate's free will, using an approved consent document from the Ethical Review Committee of the respective research institution.
(3) Imaging studies ruling out pancreatic cancer or pathology confirming the absence of pancreatic cancer.
(4) Presence of high-risk factors for pancreatic cancer: type 2 diabetes mellitus, chronic pancreatitis, family history of pancreatic cancer, intraductal papillary mucinous neoplasm (IPMN), pancreatic cyst, or pancreatic duct dilation.
Healthy Volunteers:
To participate in this study, individuals must meet criteria (1) through (3):
(1) Japanese nationals aged 50 years or older at the time of signing the consent form.
(2) Able to provide written consent willingly using an approved consent document from the Ethical Review Committee of the respective research institution.
(3) Assessed by a physician to be in good health based on medical evaluation, including history, physical examination, vital signs, and laboratory values.
Patients who meet any of the following criteria (1) through (6) will not be included in this study.
(1) Patients who have difficulty urinating on their own due to severe renal failure, need nursing care for urination, etc.
(2) Patients who are pregnant or may become pregnant.
(3) Women who are menstruating at the time of scheduled urine sample collection.
(4) Patients with a history of malignancy in the past.
(5) Those who are currently participating in an interventional study (including clinical trials) other than this study.
(6) Any other person who is deemed inappropriate by the investigator.
800
1st name | Yuki |
Middle name | |
Last name | Ichikawa |
Craif Inc.
Chief Technology Officer
113-0034
5F ITP Hongo Office , 2-25-7 Yushima, Bunkyo-ku, Tokyo, 113-0034, Japan
03-6801-8334
clinicaltrial@craif.com
1st name | Motoki |
Middle name | |
Last name | Mikami |
Craif inc.
Clinical Development
113-0034
5F ITP Hongo Office , 2-25-7 Yushima, Bunkyo-ku, Tokyo, 113-0034, Japan
03-6801-8334
clinicaltrial@craif.com
Craif Inc.
Self funded
Profit organization
Japan
Craif Institutional Review Board
5F ITP Hongo Office , 2-25-7 Yushima, Bunkyo-ku, Tokyo, 113-0034, Japan
03-6801-8334
clinicaltrial@craif.com
NO
2024 | Year | 03 | Month | 18 | Day |
Unpublished
Open public recruiting
2024 | Year | 02 | Month | 14 | Day |
2024 | Year | 03 | Month | 07 | Day |
2024 | Year | 04 | Month | 30 | Day |
2025 | Year | 12 | Month | 31 | Day |
None
2024 | Year | 03 | Month | 18 | Day |
2024 | Year | 04 | Month | 30 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000061507
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