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CT Imaging and Clinical Features to Predict Outcomes in Patients With Gastric Cancer
Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Summary
The goal of this prospective observational study is to evaluate how well a previously developed prediction model can estimate outcomes in adults with gastric cancer. The model combines information from computed tomography (CT) images obtained before treatment with routine clinical information. The main questions are how well the model predicts how long participants live after treatment begins and whether their cancer progresses. Participants will receive their usual medical care. Researchers will collect pretreatment CT images, basic clinical and tumor information, laboratory and tumor marker results, treatment information, and follow-up outcomes obtained during routine care. These data will be entered into the predefined prediction model, and the model's predictions will be compared with what actually happens during follow-up. The study will not change the participants' usual treatment. Model predictions will be used for research purposes only and will not be used to make treatment decisions.
Official title: Prospective Validation of a CT Radiomics-Based Model Combined With Clinical Features for Prognosis Prediction in Gastric Cancer Patients
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
600
Start Date
2026-04-01
Completion Date
2027-04-01
Last Updated
2026-08-20
Healthy Volunteers
No
Conditions
Interventions
No intervention (observational study)
No intervention or treatment will be assigned by the study protocol. All diagnostic and treatment decisions, including surgery, chemotherapy, immunotherapy, or combined treatment, will be made by treating clinicians as part of routine clinical care. The predefined CT radiomics-based prognostic model will be applied to collected imaging and clinical data for research validation only. Model-generated predictions will not be used to guide or modify clinical treatment decisions.
Locations (1)
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, China