Status:
COMPLETED
Machine Learning Model Guided by TLS Predicts Survival and Immune Features in Gastric Cancer
Lead Sponsor:
Qun Zhao
Conditions:
Locally Advanced Gastric Cancer
Tumor Immune Microenvironment
Eligibility:
All Genders
18-80 years
Brief Summary
This study aims to develop and validate a machine learning model that uses information from tertiary lymphoid structures (TLSs)-specialized immune-related cell clusters found near tumors-to predict su...
Eligibility Criteria
Inclusion
- Histologically confirmed locally advanced gastric adenocarcinoma (clinical stage cT2-T4 and/or N+)
- Underwent curative-intent gastrectomy (with or without neoadjuvant therapy)
- Availability of adequate tumor tissue specimens for TLS assessment via digital pathology
- Complete baseline clinical, pathological, and follow-up data
- Age ≥ 18 years
- Written informed consent provided (if prospective study component is included)
Exclusion
- Distant metastases at the time of diagnosis or surgery (M1 stage)
- Prior history of other malignancies within the past 5 years, except for adequately treated in situ carcinoma or non-melanoma skin cancer
- Incomplete or missing essential clinical, pathological, or survival data
- Poor-quality tissue samples not suitable for TLS quantification or digital analysis
- Participation in another clinical trial that may interfere with the study outcomes
Key Trial Info
Start Date :
January 1 2012
Trial Type :
OBSERVATIONAL
Allocation :
ACTUAL
End Date :
January 1 2024
Estimated Enrollment :
1200 Patients enrolled
Trial Details
Trial ID
NCT06979817
Start Date
January 1 2012
End Date
January 1 2024
Last Update
May 20 2025
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