Not Yet RecruitingNot Applicable

A Single-arm, Prospective, Multi-center Cohort Study Based on Deep Learning-based cfDNA Fragment Omics to Verify the TuFEst Model for the Staging Diagnosis of Breast Cancer Lesions and Lymph Nodes

269 participantsStarted 2025-12-01

Plain-language summary

Through the research of this project, we expect to achieve the cfDNA fragment omics liquid biopsy technology based on deep learning, verify the accuracy of the TuFEst model in predicting the tumor burden status of breast cancer lesions and lymph nodes in newly diagnosed breast cancer patients and those receiving neoadjuvant therapy, and provide a theoretical basis for large-scale clinical application in the future

Who can participate

Age range18 Years – 70 Years

SexFEMALE

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion criteria

✓. Patients aged 18 to 70;
✓. Direct Surgery Group (Cohort 1) : Radical surgery was performed without neoadjuvant therapy;
✓. Neoadjuvant therapy group (Cohort 2) : The initial diagnosis was invasive breast cancer with confirmed axillary lymph node metastasis, and the patient was willing to undergo radical surgery at the end of treatment;
✓. Plasma from patients during treatment can be obtained;
✓. Be willing to sign the informed consent form. -

Exclusion criteria

✕. Be pregnant or breastfeeding;
✕. Patients whose lesions have been resected;
✕. Suffered from other types of malignant tumors with a clear pathological diagnosis within 5 years prior to enrollment;
✕. Within the past year of enrollment, the patient had other malignant tumors suspected by imaging, but they were not confirmed by pathology;
✕. Suspected distant metastatic lesions on imaging, or potential lymph node lesions that cannot be completely cured by surgery;
✕. Have received any blood product infusion treatment in the past 30 days. -

What they're measuring

Negative predictive value (NPV) of the TuFEst-based classifier for predicting pathologic node-negative status (pN0)

Timeframe: up to 2 weeks

Trial details

NCT IDNCT07304934

SponsorSecond Affiliated Hospital, School of Medicine, Zhejiang University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2027-12-31

View on ClinicalTrials.gov More Breast Cancer trials