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| ID | Type | Description | Link |
|---|---|---|---|
| ES-2924-051-02 | Other Identifier | First Affiliated Hostipal of Guangzhou Medical University |
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This study will utilize tissue and peripheral blood samples for proteomics analysis and establish a longitudinal proteomics cohort at multiple critical treatment time points to explore the research value of proteomics in the diagnosis and treatment of lung cancer. The study includes key time points such as screening, postoperative efficacy prediction, and efficacy prediction after medication.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Using tissue and peripheral blood proteomics to distinguish the benign and malignant nature of lung cancer in patients, as well as to evaluate therapeutic efficacy and long-term prognosis during the t | Other | Peripheral blood samples from enrolled participants will be drawn, or lesion tissues will be obtained through procedures such as biopsy or surgery, followed by quantitative proteomics analysis using mass spectrometry. |
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| Measure | Description | Time Frame |
|---|---|---|
| Area Under the Curve | AUC, or Area Under the Curve, is a commonly used metric in statistical and machine learning models, particularly for evaluating the performance of classification models. It refers to the area under the Receiver Operating Characteristic (ROC) curve, which plots the true positive rate (sensitivity) against the false positive rate (1-specificity) at various threshold settings. An AUC value ranges from 0 to 1, where:
In clinical studies, AUC is often used to assess diagnostic tests, where a higher AUC indicates better test accuracy in distinguishing between conditions (e.g., disease vs. no disease). | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Differentially Expressed Proteins | Differential proteins, or differentially expressed proteins (DEPs), refer to proteins that show significant changes in expression levels between different biological or experimental conditions, such as disease vs. healthy states, treated vs. untreated groups, or across time points in longitudinal studies. These proteins are identified through quantitative proteomics techniques, including mass spectrometry or label-free methods, and analyzed using statistical or bioinformatics tools to determine significance. |
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Inclusion Criteria:
Exclusion Criteria:
(8) Medication use before pulmonary function testing that does not meet the cessation guidelines; (9) Pulmonary function report quality graded D-F.
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Patients with lung nodules confirmed by CT examination.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jianxing He, Professor | Contact | 86-20-83337792 | drjiaxing.he@gmail.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| the First Affiliated of Guangzhou Medical University | Recruiting | Guangzhou | Guangdong | 510120 | China |
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| 3 years |
| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
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