Characterization of Multi-Omics Landscapes and AI Pathological Prediction Model for Long-Term Survival in NSCLC Immunotherapy
Characterization of Multi-Omics Landscapes in Long-Term Survival Following Immunotherapy and Development of an AI Pathological Prediction Model for Long-Term Survival Based on H&E-Stained Images in Advanced Non-Small Cell Lung Cancer
Cancer Institute and Hospital, Chinese Academy of Medical Sciences
600 participants
May 1, 2026
OBSERVATIONAL
Conditions
Summary
This study is a retrospective, multicenter, observational cohort study in patients with advanced or locally advanced non-small cell lung cancer (NSCLC). The aim of this study was to establish a long-term survival (LTS) versus short-term survival (STS) real-world cohort, to systematically characterize the multi-omics landscapes, and to develop and validate an artificial intelligence (AI) pathological prediction model based on routine H\&E-stained images for predicting immune microenvironment features and long-term survival outcomes following immunotherapy.
Eligibility
Plain Language Summary
Simplified for easier understanding
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NCT07668037