An observational study in Lung, Lung Cancer and Cancer, sponsored by The First Affiliated Hospital of Guangzhou Medical University. Recruiting at 1 site in China. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2025-01-16.
Sponsored by The First Affiliated Hospital of Guangzhou Medical University · Observational
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.
7,243 studies on the registry are indexed under Lung Neoplasms; 1,557 are open to participants now.
This study's planned enrollment of 2,500 is above the median of 189 across 1,514 observational studies indexed under Lung Neoplasms.
Browse Lung Neoplasms studies →The First Affiliated Hospital of Guangzhou Medical University is the lead sponsor of 158 studies on the registry; 65 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients with lung nodules confirmed by CT examination.
Exclusion Criteria:
(8) Medication use before pulmonary function testing that does not meet the cessation guidelines; (9) Pulmonary function report quality graded D-F.
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.
Also known as: Draw peripheral blood, Obtain lesion tissue
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: * 1 indicates a perfect model, * 0.5 suggests a model no better than random guessing, * \< 0.5 reflects a model performing worse than random. 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).
Time frame: 3 years
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.
Time frame: 3 years
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The First Affiliated Hospital of Guangzhou Medical University