Characterization of Multi-Omics Landscapes and AI Pathological Prediction Model for Long-Term Survival in NSCLC Immunotherapy
Recruiting · NCT07668037 · Observational (researchers observe without assigning treatment)
View the official record on ClinicalTrials.gov →What this trial is about
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.
Who can take part
Age range
18 Years and older
Sex
All (male and female)
Healthy volunteers
No - a diagnosis or condition is required
Phase
Not specified
Study type
Observational (researchers observe without assigning treatment)
Inclusion criteria
- Patients with pathologically confirmed advanced or locally advanced non-small cell lung cancer (NSCLC).
- Patients derived from real-world data of multiple centers (including Cancer Hospital, Chinese Academy of Medical Sciences; Cancer Hospital of Shanxi, Chinese Academy of Medical Sciences \[Shanxi Cancer Hospital\]; and other participating centers) or from completed phase III clinical trials (e.g., Choice-01, Rationale-307, Rationale-304).
- Patients who received first-line or later-line immune checkpoint inhibitor (ICI) monotherapy or ICI-based combination therapy.
- Patients with complete clinical information and available follow-up data.
Exclusion criteria
- Patients whose systemic therapy did not include an immunotherapy regimen.
- Patients lost to follow-up.
Where it is running
1 location listed.
- Cancer Hospital Chinese Academy of Medical Sciences - Beijing, China