Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer
Artificial Intelligence-based Model for the Prediction of Occult Lymph Node Metastasis and Improvement of Clinical Decision-making in Non-small Cell Lung Cancer: A Multicenter, Prospective, Observational Study
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Zhengfei Zhu, PhD
- Phone Number: +86-18017312901
- Email: fuscczzf@163.com
Study Locations
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Shanghai, China
- Recruiting
- Fudan University Shanghai Cancer Center
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Contact:
- Zhengfei Zhu, PhD
- Phone Number: 18017312901
- Email: fuscczzf@163.com
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Pathologically confirmed non-small cell lung cancer;
- 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:
- Poor quality of computed tomography imaging;
- 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.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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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.
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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.
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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.
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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.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Recurrence-free survival (RFS)
Time Frame: 1 year
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The time from surgical treatment or SBRT to disease recurrence or death.
Patients who were still not progressing at the time of analysis will have the date of their last contact as the cutoff date.
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1 year
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Overall Survival (OS)
Time Frame: 1 year
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The time from the surgery or SBRT until death from any cause.
Patients who are still alive at the time of analysis will have their last contact date used as the cutoff date.
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1 year
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Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- OLNM-AI
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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