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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