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| Name | Class |
|---|---|
| The First Affiliated Hospital of Guangzhou Medical University | OTHER |
| First People's Hospital of Foshan | OTHER |
| Sichuan Cancer Hospital and Research Institute | OTHER |
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The goal of this observational study is to develop an advanced expiratory algorithm model utilizing exhaled breath volatile organic compound (VOC) markers. This model aims to accurately differentiate benign from malignant nodules in individuals harboring pulmonary nodules. The primary objectives it strives to accomplish are:
By utilizing this comprehensive approach, the study hopes to contribute significantly to early detection and accurate classification of pulmonary nodules, ultimately leading to improved patient care and treatment outcomes.
This is a prospective, cross-sectional, and observational cohort study aiming at recruiting 3000 participants with pulmonary nodules ranging from 5 to 30 mm in diameter. Prior to invasive surgery, exhaled breath samples will be collected from these participants and analyzed using Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system. Following the acquisition of μGC-PID results, a comprehensive evaluation of the diagnostic performance of VOC biomakers distinguishing between benign and malignant pulmonary nodules will be conducted, leveraging histopathological findings, CT examination data, and clinical data.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Pulmonary Nodules | Pre-surgery adult patients with pulmonary nodule found by CT scan. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Gas chromatography-mass spectrometry(GC-MS) and micro Gas Chromatography-photoionisation detector (μGC-PID) system | Other | Detection of volatile organic compound molecules in human exhaled breath by GC-MS and μGC-PID |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic accuracy of an exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model in distinguishing benign and malignant pulmonary nodules. | The diagnostic performance of the exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model will be compared with pathologic diagnosis and CT/LDCT data, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| The diagnostic effectiveness of an AI model to identify specific types of malignant nodules, including lung adenocarcinoma, lung squamous cell carcinoma, and small cell lung cancer. | The diagnostic performance of the exhaled breath VOC-assisted diagnostic artificial intelligence (AI) model will be compared with pathologic diagnosis, including sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). |
| Measure | Description | Time Frame |
|---|---|---|
| Establish an exhaled breath VOC model for predicting EGFR mutations in malignant pulmonary nodules. | Establish an exhaled breath VOC model for predicting EGFR mutations in pathologically confirmed malignant pulmonary nodules. And evaluate the prediction accuracy by comparing the results of EGFR gene testing. | 3 years |
Inclusion Criteria:
Exclusion Criteria:
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People who have pulmonary nodules with a large diameter between 5 mm and 30 mm on a CT scan within six months.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Hengrui Liang, MD | Contact | +86 15625064712 | hengrui_liang@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Jianxing He, MD | The First Affiliated Hospital of Guangzhou Medical University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Peking Union Medical College Hospital | Recruiting | Beijing | Beijing Municipality | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33538338 | Background | Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4. | |
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| Liwan District Central Hospital |
| UNKNOWN |
| Shanghai Chest Hospital | OTHER |
| Peking Union Medical College Hospital | OTHER |
| Guangzhou Development Zone Hospital | UNKNOWN |
| Huangpu District Hongshan Street Community Health Service Center | UNKNOWN |
| Huangpu District Chinese Medicine Hospital | UNKNOWN |
| Fifth Affiliated Hospital of Guangzhou Medical University | OTHER |
| Huangpu District Jiufo Street Community Health Service Center | UNKNOWN |
| Huangpu District Xinlong Town Central Hospital | UNKNOWN |
| Huangpu District Yonghe Street Community Health Service Center | UNKNOWN |
| Huangpu District Lianhe Street Second Community Health Service Center | UNKNOWN |
| Renmin Hospital of Wuhan University | OTHER |
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Volatile Organic Compounds in Human Exhaled Breath
| 3 years |
| First People's Hospital of Foshan | Recruiting | Foshan | Guangdong | 528000 | China |
|
| The First Affiliated Hospital of Guangzhou Medical University | Recruiting | Guangzhou | Guangdong | 510140 | China |
|
| Liwan District Central Hospital | Recruiting | Guangzhou | Guangdong | 510175 | China |
|
| Guangzhou Development Zone Hospital | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Chinese Medicine Hospital | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Hongshan Street Community Health Service Center | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Jiufo Street Community Health Service Center | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Lianhe Street Second Community Health Service Center | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Xinlong Town Central Hospital | Recruiting | Guangzhou | Guangdong | China |
|
| Huangpu District Yonghe Street Community Health Service Center | Recruiting | Guangzhou | Guangdong | China |
|
| The Fifth Affiliated Hospital of Guangzhou Medical University | Recruiting | Guangzhou | Guangdong | China |
|
| Renmin Hospital of Wuhan University | Recruiting | Wuhan | Hubei | China |
|
| Shanghai Chest Hospital | Recruiting | Shanghai | Shanghai Municipality | China |
|
| Sichuan Cancer Hospital | Recruiting | Chengdu | Sichuan | 610042 | China |
|
| 27253694 | Background | Miller KD, Siegel RL, Lin CC, Mariotto AB, Kramer JL, Rowland JH, Stein KD, Alteri R, Jemal A. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016 Jul;66(4):271-89. doi: 10.3322/caac.21349. Epub 2016 Jun 2. |
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| ID | Term |
|---|---|
| D055613 | Multiple Pulmonary Nodules |
| D003074 | Solitary Pulmonary Nodule |
| D008175 | Lung Neoplasms |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
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| ID | Term |
|---|---|
| D016503 | Drug Delivery Systems |
| ID | Term |
|---|---|
| D004358 | Drug Therapy |
| D013812 | Therapeutics |
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