AI (Artificial Intelligence), NSCLC Brain Metastasis
Conditions
Brief summary
The goal of this nationwide, multicenter observational study is to develop and externally validate multimodal large models that can (1) predict the risk of brain metastases and (2) estimate long-term prognosis in patients with non-small cell lung cancer (NSCLC). The main questions it aims to answer are: * Can a multimodal large model that fuses imaging, pathology, genomic, and clinical data accurately identify NSCLC patients at high risk of developing brain metastases? * Can a multimodal large model reliably forecast intracranial progression-free survival, progression-free survival, and overall survival across diverse real-world treatment settings? (ie, patients receiving distinct treatment regimens, in different treatment lines and with or without intracranial local therapies). Because this is an observational study, there are no investigational treatments; instead, researchers will compare outcomes among patients who receive standard-of-care therapies (surgery, radiotherapy, systemic therapy) to determine how well the model's predictions align with observed events. Participants will: * Allow use of their routinely collected clinical information, imaging (chest CT, brain MRI), pathology slides, and molecular test results for model training and validation * Undergo standard-of-care follow-ups * Complete optional quality-of-life questionnaires during scheduled visits
Interventions
OTHERNo Intervention: Observational Cohort
No intervention
Sponsors
Fudan University
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Age≥18 years old; * KPS score≥70; * Pathologically confirmed lung cancer; * Receiving guideline-concordant standard-of-care therapy, defined as: radical surgical resection for early- to mid-stage non-small cell lung cancer (NSCLC); stereotactic radiotherapy for early-stage NSCLC deemed medically inoperable; radical chemoradiotherapy for locally advanced NSCLC; or systemic therapy for advanced-stage NSCLC. * Complete systemic imaging before treatment initiation, including contrast-enhanced brain MRI and contrast-enhanced chest CT; * Informed consent of the patient.
Exclusion criteria
* Multiple primary or metastatic tumors (except early skin cancer, cervical carcinoma in situ that has been treated radically, with no recurrence or progression for more than 5 years); * 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; * Physical examination findings, clinical laboratory abnormalities, or other uncontrolled medical conditions identified by the investigator as potentially interfering with study results interpretation or increasing the patient's risk of treatment complications * Pregnant or lactating women.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The predictive performance of the multimodal large models | 2 years | Including Sensitivity (SEN), Specificity (SPE), Matthews Correlation Coefficient (MCC), Area Under the Receiver Operating Characteristic Curve (AUC) with its corresponding 95 % confidence interval (CI) |
Secondary
| Measure | Time frame |
|---|---|
| Overall Survival (OS) | 2 years |
| Progression-Free Survival (PFS) | 2 years |
| Intracranial Progression-Free Survival (iPFS) | 2 years |
Contacts
Primary ContactZhengfei Zhu, PhD
Outcome results
None listed