Clinical trial NCT04419207: Detecting Lung Cancer Based on Exhaled Breath
Official title: Detecting Lung Cancer by Volatile Organic Compounds in Exhaled Breath: a Study of Lung Cancer Diagnostic Biomarker
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Carcinoma
Lung Cancer
NSCLC
Lung Neoplasms
Keywords: volatile organic compounds
exhaled breath
biomarker
Lead sponsor: Peking University People's Hospital
Sponsor class: OTHER
Collaborators: name: Beijing Haidian Hospital
name: Aerospace 731 Hospital
name: Beijing Breatha Biological Technology Co., Ltd, Beijing
name: The First Affiliated Hospital of Zhengzhou University
name: Jiangsu Cancer Institute & Hospital
First posted: 2020-06-05
Enrollment: 2236
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Eligible inpatients will be recruited from Department of Thoracic Surgery, Peking University People's Hospital and Beijing Haidian Hospital.

For healthy controls, eligible participants will be recruited from those who receive planned annual physical examination at Aerospace 731 Hospital.

Brief summary: Early detection is critical to improve the overall survival of lung cancer. Endogenous volatile organic compounds (VOCs) can be derived from many different metabolic pathways. On the other hand, cancer cells have different metabolism patterns compared with normal cells. Thus, detecting VOCs in exhaled breath using highly sensitive mass spectrometry would be a promising approach for lung cancer detection.

Detailed description: Endogenous volatile organic compounds (VOCs) can be derived from many different metabolic pathways. VOCs can be transported to the alveoli through the blood circulation and expelled by exhalation. Changes in VOCs production, clearance, and alterations in lung air-blood exchange functions can lead to aberrant VOCs profiles in the exhaled breath. Testing exhaled breath has the advantages of being completely non-invasive and easy to collect, and has been considered as a perfect approach for disease diagnoses and therapeutic monitoring. Many clinical studies have found that VOCs in exhaled breath are closely related to disease status. Specific VOCs alterations have been identified in many tumors, especially lung cancer.

In this study, we use a highly sensitive mass spectrometry to detect exhaled VOCs of lung cancer patients and healthy people. A lung cancer diagnosis model based on mass spectrometry data and support vector machine will be initially established and validated.

Eligibility criteria: Inclusion Criteria for inpatient :

* pulmonary nodules in competed tomography images
* plan to receive thoracic surgery

Inclusion Criteria for controls :

* have planned physical examination every year
* plan to receive low-dose computed tomography

Exclusion Criteria:

* history of malignant tumors.
* receive anti-tumor treatment such as radiotherapy, chemotherapy, targeted therapy before surgery
* with infections or liver disease

Primary outcomes:
measure: Diagnostic sensitivity of exhaled breath
timeFrame: 2 year
measure: Diagnostic specificity of exhaled breath
timeFrame: 2 year
measure: Positive predictive value of exhaled breath
timeFrame: 2 year
measure: Negative predictive value of exhaled breath
timeFrame: 2 year
measure: Diagnostic accuracy of exhaled breath
timeFrame: 2 year
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Peking University People's Hospital
state: Beijing
Study officials:
affiliation: Peking University People's Hospital Thoracic Surgery Department
name: Mantang Qiu, M.D
role: STUDY_CHAIR
affiliation: Peking University People's Hospital
name: Zuli Zhou, M.D
role: PRINCIPAL_INVESTIGATOR
References: