Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer
NCT ID: NCT06684418
Last Updated: 2025-01-20
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
RECRUITING
6000 participants
OBSERVATIONAL
2024-12-01
2026-06-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Multimodal Large Model-Driven Risk and Prognosis Assessment for Brain Metastases in Lung Cancer
NCT07107035
Prediction of Mediastinal Station IV Lymph Node Metastasis in Non-small Cell Lung Cancer
NCT06496360
Deep Learning Signature for Predicting Occult Nodal Metastasis of Clinical N0 Lung Cancer
NCT05425134
The Accuracy of Targeted Lymph Node Dissection of Non-small Cell Lung Cancer Patients According to Predictive Models
NCT06768853
A Study of Lymph Node Metastatic Pattern Based Incorporating Tumor Location, GGO Components and Size for Non-small Cell Lung Cancer
NCT06161935
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Retrospective Cohort
Enrolling about 5,000 early-stage NSCLC patients from January 2018 to June 2024 across 25 centers in China, data including chest CT scans and clinicopathological parameters will be used to train and validate the AI model. Patients will be divided into "high-risk" and "low-risk" groups based on the model's risk score, and clinical benefits of treatments like lymph node dissection, adjuvant therapy, and SBRT will be analyzed.
chest enhanced CT
This is an observational study and patients will receive routine clinical treatment according to the corresponding guidelines. We will collect the enrolled patient's chest enhanced CT and clinicopathological parameters.
Prospective Cohort
Enrolling 1,000 patients from November 2024 to October 2025, this cohort will prospectively validate the AI model's performance and explore the biological basis of metastasis by analyzing pathological tissues, RNA sequencing, and tumor immune microenvironment characteristics.
chest enhanced CT
This is an observational study and patients will receive routine clinical treatment according to the corresponding guidelines. We will collect the enrolled patient's chest enhanced CT and clinicopathological parameters.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
chest enhanced CT
This is an observational study and patients will receive routine clinical treatment according to the corresponding guidelines. We will collect the enrolled patient's chest enhanced CT and clinicopathological parameters.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Clinical stage I (AJCC, 8th edition, 2017);
* Age≥18 years old;
* KPS score≥70;
* Patients who have undergone primary NSCLC radical surgery or SBRT treatment;
* Complete systemic lesion imaging assessment before primary NSCLC radical surgery or SBRT treatment (Note: Tumor size ≥ 3 cm or centrally located tumor requires PET/CT and/or invasive mediastinal staging);
* Patients willing to cooperate with the follow-up after primary NSCLC radical surgery;
* informed consent of the patient.
Exclusion Criteria
* Baseline imaging shows pure ground-glass nodules (GGO);
* Uncontrolled epilepsy, central nervous system disease, or history of mental disorders, judged by the researcher to potentially interfere with the signing of the informed consent form or affect patient compliance.;
* Loss to follow-up.
18 Years
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Fudan University
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Zhengfei Zhu
Professor
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Fudan university Shanghai Cancer Center
Shanghai, , China
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
OLNM-AI
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.