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Establishment of a Multi-omics Prediction Model for Early Triple-negative Breast Cancer Based on UPGRADE-TNBC Study
Sponsor: Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Summary
Based on the UPGRADE-TNBC study, a high-quality TNBC sample repository was established. By integrating multi-source data-including clinical information, radiomics, pathological images, and molecular sequencing-and innovatively incorporating a meta-learning strategy, a treatment response prediction model based on multimodal small-sample learning was developed. This approach aims to optimize drug combinations and precisely identify patient subgroups likely to benefit from treatment, thereby providing a new paradigm for personalized therapy in early-stage TNBC.
Key Details
Gender
FEMALE
Age Range
18 Years - 75 Years
Study Type
OBSERVATIONAL
Enrollment
32
Start Date
2026-08-06
Completion Date
2029-09-01
Last Updated
2026-08-19
Healthy Volunteers
No
Interventions
Collect data
Collect multi-source data from patients, including clinical information, radiomics, pathological images, and molecular sequencing
Locations (1)
Cancer Hospital, Chinese Academy of Medical Sciences
Beijing, Beijing Municipality, China