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NCT Number: NCT07304934

A Prospective Multicenter Study of the TuFEst-LN Model for Axillary Lymph Node Status Assessment in Breast Cancer

Through the research of this project, we expect to validate the clinical utility of the TuFEst-LN model in assessing axillary lymph node status in breast cancer patients. Specifically, we aim to prospectively validate its ability to identify pathologically node-negative patients among clinically and radiologically assessed cN0 patients undergoing upfront surgery ,and explore the predictive value of the TuFEst-LN model combined with preoperative MRI for ypN status assessment in initially node-positive patients following neoadjuvant therapy.

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Key information

Age range

18 year and older

Sex eligibility

Female

Study type

Observational

Primary location

Second affiliated hospital of Medical school, Zhejiang university

Hangzhou, Zhejiang, China

Location status: Recruiting

Location contact

About this study

Through the research of this project, we aim to prospectively validate the locked TuFEst-LN model, a cfDNA fragmentomics-based liquid biopsy model, for axillary lymph node status assessment in patients with breast cancer. This study will evaluate the ability of the TuFEst-LN model to identify pathologically node-negative patients among clinically and radiologically assessed cN0 patients with cT1-3 invasive breast cancer undergoing upfront surgery without neoadjuvant therapy. In addition, this study will explore the predictive value of the TuFEst-LN model combined with preoperative magnetic resonance imaging (MRI) for post-neoadjuvant pathological axillary lymph node status (ypN) in initially node-positive breast cancer patients. Peripheral blood samples and clinical data will be prospectively collected from multiple centers, and model predictions will be compared with final surgical pathology as the reference standard. This study aims to validate the clinical utility of cfDNA fragmentomics-based liquid biopsy for noninvasive axillary lymph node assessment and provide evidence for individualized axillary management in breast cancer.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Cohort 1-Specific Inclusion Criteria

Participants in Cohort 1 must meet all of the following criteria:

  • Histologically confirmed invasive breast cancer.
  • Clinical stage cT1-3, cN0, M0 disease at enrollment.
  • No clinically palpable suspicious metastatic axillary lymph nodes identified by physical examination.
  • No radiologically suspicious metastatic axillary lymph nodes identified by preoperative axillary imaging (at least ultrasound examination). Patients with suspicious lymph nodes must have negative cytological or histological findings confirmed by fine-needle aspiration or core needle biopsy.
  • No prior neoadjuvant therapy, including chemotherapy, targeted therapy, immunotherapy, endocrine therapy, or breast/axillary radiotherapy before enrollment.
  • Planned to undergo definitive breast surgery with sentinel lymph node biopsy (SLNB) and/or axillary lymph node dissection (ALND).
  • Ability to provide qualified preoperative plasma samples for cfDNA analysis.

Cohort 2-Specific Inclusion Criteria

Participants in Cohort 2 must meet all of the following criteria:

  • Histologically confirmed invasive breast cancer.
  • Ipsilateral axillary lymph node metastasis confirmed by fine-needle aspiration or core needle biopsy at initial diagnosis.
  • No evidence of distant metastasis (M0), and planned to receive standard neoadjuvant systemic therapy followed by definitive breast and axillary surgery.
  • Completion of the planned neoadjuvant therapy, or premature discontinuation due to clinical reasons while remaining eligible for subsequent surgery.
  • Ability to provide a baseline plasma sample (T0) within 24-72 hours before initiation of the first systemic treatment (including chemotherapy, immunotherapy, or targeted therapy).
  • Availability of preoperative breast and axillary magnetic resonance imaging (MRI) after completion of neoadjuvant therapy. Patients unable to undergo MRI due to contraindications or other reasons may be included in the cfDNA-only analysis set but will not be included in the complete-case analysis of the combined cfDNA-MRI model.
  • Ability to provide a second plasma sample (T1) within 24-72 hours before surgery after completion of neoadjuvant therapy. Patients without T0 samples may still be included in the exploratory analysis of T1 cfDNA combined with MRI for ypN prediction.
  • Availability of complete postoperative breast and axillary pathological evaluation results.

Exclusion criteria

Participants meeting any of the following criteria will be excluded:

  • Pregnancy or breastfeeding.
  • Prior surgical removal of the primary breast lesion before enrollment, resulting in inability to obtain the required preoperative blood samples.
  • Presence of confirmed distant metastasis.
  • Presence of supraclavicular, internal mammary, or other lymph node lesions that cannot be adequately assessed by planned surgery and pathological evaluation.
  • History of another active malignancy within the previous 5 years, except for cured non-melanoma skin cancer, cervical carcinoma in situ, or other malignancies considered by investigators unlikely to affect study outcomes.
  • Receipt of whole blood, plasma, or other blood product transfusion within 30 days prior to enrollment.
  • Insufficient plasma sample volume, severe hemolysis, or failure to meet cfDNA sequencing quality control requirements determined by the central laboratory.
  • Absence of evaluable axillary surgical pathological results.
  • Any other condition considered by the investigator to make the patient unsuitable for participation in this study.

Treatment and study plan

No Intervention: Observational Cohort

Other

No Intervention: Observational Cohort

Primary outcomes

  1. Pathological axillary lymph node positivity rate among TuFEst-LN-negative patients

    Time frame: up to 2 weeks

    Defined as the proportion of patients with pathological axillary lymph node positivity (pN1mi or higher) among patients predicted as negative by the locked TuFEst-LN model in Cohort 1. FOR = FN/(TN+FN) = 1-NPV.

Secondary outcomes

  1. Negative Predictive Value (NPV) of the TuFEst-LN Model

    Time frame: 2 weeks

    The proportion of patients with negative pathological axillary lymph node status (pN0 or pN0(i+)) among patients classified as negative by the locked TuFEst-LN model.

  2. Sensitivity and False Negative Rate (FNR) for Detecting Pathological Axillary Lymph Node Positivity

    Time frame: 2 weeks

    The ability of the locked TuFEst-LN model to identify patients with pathological axillary lymph node metastasis (pN1mi or higher). FNR is defined as 1-sensitivity.

  3. Specificity of the TuFEst-LN Model

    Time frame: 2 weeks

    The proportion of patients with true pathological node-negative status (pN0 or pN0(i+)) who are correctly classified as negative by the locked TuFEst-LN model.

  4. Positive Predictive Value (PPV), Overall Accuracy, and Discrimination Performance

    Time frame: 2 weeks

    Evaluation of the predictive performance of the locked TuFEst-LN model, including PPV, overall accuracy, area under the receiver operating characteristic curve (ROC-AUC), area under the precision-recall curve (PR-AUC), and likelihood ratios.

  5. Proportion of Patients Classified as Negative by the TuFEst-LN Model

    Time frame: 2 weeks

    The proportion of evaluable patients in Cohort 1 who are classified as negative by the locked TuFEst-LN model, used to estimate the potential rate of sentinel lymph node biopsy (SLNB) omission.

  6. Calibration and Net Clinical Benefit of the TuFEst-LN Model

    Time frame: 2 weeks

    Assessment of model calibration and clinical utility using Brier score, calibration intercept, calibration slope, calibration curve, and decision curve analysis.

  7. Pathological Burden of Missed Positive Cases

    Time frame: 2 weeks

    Evaluation of pathological characteristics among false-negative patients, including the number of micrometastatic and macrometastatic lymph node cases, extranodal extension, and other adverse pathological features.

Other outcomes

  1. Predictive Performance of the TuFEst-LN Model for ypN Status

    Time frame: 2 weeks

    Using final surgical pathology as the reference standard, the predictive performance of the TuFEst-LN model for post-neoadjuvant pathological axillary lymph node status (ypN) will be evaluated, including area under the receiver operating characteristic curve (ROC-AUC), sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and calibration performance.

  2. Predictive Performance of Preoperative MRI for ypN Status

    Time frame: 2 weeks

    Evaluation of the ability of preoperative magnetic resonance imaging (MRI) clinical and quantitative imaging features after neoadjuvant therapy to predict residual pathological axillary lymph node status (ypN0 versus ypN-positive).

  3. Performance of Combined cfDNA Fragmentomics and MRI Model

    Time frame: 2 weeks

    Evaluation of the incremental value of integrating TuFEst-LN cfDNA fragmentomic features with MRI-based prediction models by comparing changes in ROC-AUC, Brier score, calibration performance, and decision curve analysis.

  4. Changes in cfDNA Fragmentomic Features From T0 to T1

    Time frame: 2 weeks

    Exploration of the association between longitudinal changes in cfDNA fragmentomic scores or features before and after neoadjuvant therapy and pathological outcomes, including ypN status, breast pathological complete response (pCR), residual cancer burden (RCB), and residual tumor burden.

  5. Exploratory Subgroup Analysis

    Time frame: 2 weeks

    Exploration of the predictive performance of the TuFEst-LN model across clinically relevant subgroups, including molecular subtype, treatment regimen, and baseline lymph node burden.

Study contacts

Contact information is provided by the study sponsor or research team.

Sponsors and collaborators

Lead sponsor

Second Affiliated Hospital, Zhejiang University, School of Medicine

Other

Collaborators

  • First People's Hospital of Hangzhou
  • Ningbo Medical Center Lihuili Hospital
  • Shandong Cancer Hospital and Institute
  • Suzhou Municipal Hospital
  • Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University

Registry information

Official study title

A Prospective Multi-center Cohort Study Based on Deep Learning-based cfDNA Fragment Omics to Verify the TuFEst Model for Axillary Lymph Node Status Assessment in Breast Cancer Patients Undergoing Primary Surgery or Neoadjuvant Therapy

Acronym: PRO-TuFEst-LN

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Dec 26, 2025
Registry last updated
Aug 10, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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