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Establishment of a Multi-omics Prediction Model for Early Triple-negative Breast Cancer Based on UPGRADE-TNBC Study

RECRUITINGSponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Actively Recruiting
SponsorCancer Institute and Hospital, Chinese Academy of Medical Sciences
Started2026-08-06
Est. completion2028-09-01
Eligibility
Age18 Years – 75 Years
SexFEMALE
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT07773818

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.

Eligibility

Age: 18 Years – 75 YearsSex: FEMALEHealthy volunteers accepted
Inclusion Criteria:

* The UPGRADE-TNBC Study Population

Exclusion Criteria:

* Populations outside the UPGRADE-TNBC study

Conditions6

Breast CancerCancerMeta-LearningMultimodalPredictive ModelsTriple -Negative Breast Cancertriple

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