An observational study in Triple -Negative Breast Cancertriple, Meta-Learning and Predictive Models, sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences. Recruiting at 1 site in China. Open to female participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2026-08-19.
Sponsored by Cancer Institute and Hospital, Chinese Academy of Medical Sciences · Observational
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.
The participants in the UPGRADE-TNBC study were all patients with early-stage triple-negative breast cancer who received neoadjuvant therapy.
Exclusion Criteria:
Other: Collect data
Collect multi-source data from patients, including clinical information, radiomics, pathological images, and molecular sequencing
Model building
A predictive model for neoadjuvant therapy in TNBC was successfully established
Time frame: 2 years
Plan to share: No
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Cancer Institute and Hospital, Chinese Academy of Medical Sciences