Lung Cancer
Conditions
Brief summary
The investigators aim to develop an AI-powered precision medicine system based on liquid biopsy that can comprehensively provide lung cancer patients with information on disease stage, histologic subtype, and presence of genetic mutations.
Interventions
None listed
Sponsors
Korea University Guro Hospital
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
40 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
(Patients) * Republic of Korea nationality * Age ≥ 30 years * Lung cancer based on radiologic and/or histopathologic examination * No prior diagnosis of any other cancer and no history of anticancer treatment before the date of blood sample collection
Exclusion criteria
(Patients) * History of other cancers before blood collection * Prior cancer treatment before blood collection * Incomplete clinical data * No consent for sample use Inclusion Criteria (Healthy Controls): * Republic of Korea nationality * No history of any cancer * Age ≥ 30 years
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic accuracy of the AI-based classification model using SERS signals from plasma-derived exosomes | Retrospective, based on pre-collected samples through study completion, an average of 1 year | To evaluate the diagnostic performance (sensitivity, specificity, and overall accuracy) of a machine learning model trained on SERS spectral data of plasma-derived exosomes in distinguishing lung cancer patients from healthy controls. |
Countries
South Korea
Outcome results
None listed