Machine Learning for Recurrence Risk of Pancreatic Cancer After Radical Resection (PaC)
Multimodal Data Prediction Based on Machine Learning for Recurrence Risk of Pancreatic Cancer After Radical Resection
Recurrence of Pancreatic Cancer(PCa) is a multifactorial event. Based on the clinicopathological characteristics and imaging data of patients with PCa, the investigators used image processing and machine learning algorithms to build a more comprehensive and robust model, and added some unused features to explore its clinical application value.
A retrospective analysis of patients with PCa who underwent radical resection at Zhejiang Cancer Hospital (Hangzhou, China) from January 2013 to December 2020. The database was extracted from the preoperative demographics, blood markers, and surgical pathology information of patients undergoing radical PCa surgery in the investigators' hospital. The investigators used the PyRadiomics platform to extract image features.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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-
Zhejiang
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Hangzhou, Zhejiang, China, 310000
- Zhejiang Province Cancer Hospital
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Have the results of enhanced CT examination of the pancreas within 1 month before surgery in our hospital;
- Radical resection of pancreatic cancer was performed in our hospital;
- There are follow-up results in our hospital, and the follow-up endpoints include disease recurrence or at least 12 months.
- Complete clinical medical records and imaging data.
Exclusion Criteria:
- non-R0 resection;
- Combined with other malignant tumors
- The patient's imaging data has technical problems or the lesion is too small (less than 1cm), which is not suitable for omics analysis.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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postoperative recurrence
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preoperative demographics, blood markers, surgical pathology information,and enhanced CT features.
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postoperative non-recurrence
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preoperative demographics, blood markers, surgical pathology information,and enhanced CT features.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
Recurrence-free survival
Time Frame: 1 year
|
1 year
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- Zhejiang CH
- Grant 20212B037 (OTHER_GRANT: the Zhejiang Traditional Chinese Medicine Scientific Research Fund)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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