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

NCT07773818 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 32

Last updated 2026-08-19

No results posted yet for this study

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.

Conditions

  • Triple -Negative Breast Cancertriple
  • Meta-Learning
  • Predictive Models
  • Multimodal

Interventions

OTHER

Collect data

Collect multi-source data from patients, including clinical information, radiomics, pathological images, and molecular sequencing

Sponsors & Collaborators

  • Cancer Institute and Hospital, Chinese Academy of Medical Sciences

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
FEMALE
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-08-06
Primary Completion
2028-09-01
Completion
2029-09-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07773818 on ClinicalTrials.gov