To Establish a Molecular Typing System for Early Diagnosis of Lung Cancer
Study Details
Study Description
Brief Summary
This topic to take large multicenter study real world, the advanced liquid biopsy will ctDNA methylation detection technique is applied to pulmonary nodules differential diagnosis and early lung cancer screening, validation of early lung cancer screening and diagnosis of molecular classification system model, the feasibility of the development of early lung cancer screening and diagnosis of molecular classification system, improve its early screening early detection accuracy and efficiency, Improve the survival status of lung cancer high-risk population. At the same time, this project combined AI analysis technology of LDCT image results with ctDNA methylation detection, so as to overcome false negatives caused by the deficiency of ctDNA methylation detection technology in sensitivity, specificity, stability and flux, and correct false positive results that may be caused by AI analysis technology of LDCT image results. The combination of the two can avoid missed diagnosis and over - examination and over - treatment.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
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All patients underwent low-dose CT pulmonary nodule AI detection and peripheral blood ctDNA methylation detection at baseline
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Follow-up plan: Low-risk and medium-risk nodules and some high-risk nodules (5-10mm) were followed up. 10ml peripheral blood was collected from each follow-up and stored for testing until the end of the study. The high-risk nodules over 10mm were evaluated by the expert group and the patients were informed by biopsy or surgical resection. Histopathological diagnosis was made and compared with ctDNA methylation results to analyze the sensitivity and specificity of ctDNA methylation markers of lung cancer.
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Endpoint: Tissue samples were pathologically diagnosed as benign or malignant.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Low-risk group Combined with AI calculation of malignant probability and ctDNA methylation results, patients were divided into three groups. The high probability of malignancy calculated by AI was defined as positive, and vice versa. The methylation markers detected in specific peripheral blood of lung cancer were defined as positive, and vice versa. Negative for both items was considered as low risk group. Follow-up was conducted according to The Chinese Expert Consensus on the Diagnosis and Treatment of Pulmonary Nodules (2018 edition). 10ml peripheral blood was collected from each follow-up and stored for testing until the end of the study. |
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| medium-risk group As above, one positive patient was considered to be in the medium-risk group and was reexamined every 6 months, with a total of 3 reexaminations expected |
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| High-risk group Same as above, both positive are considered high-risk group.Part of high-risk nodules (5-10mm) will be reviewed every 3 months for the above two examinations, which is expected to be reviewed 6 times in total. Biopsy or surgical resection of high-risk nodules over 10mm will be performed after evaluation by the expert group and the patient's knowledge, and histopathological diagnosis will be made and compared with ctDNA methylation results. To analyze the sensitivity and specificity of ctDNA methylation markers in lung cancer. |
Outcome Measures
Primary Outcome Measures
- To develop a molecular typing system for early screening and diagnosis of lung cancer [assessed up to 36 months]
The feasibility of the molecular typing system model for early screening and diagnosis of lung cancer was verified through clinical studies, which significantly improved the accuracy and efficiency of early screening and early diagnosis, and improved the survival status of high-risk population of lung cancer.
- AI technology was combined with ctDNA methylation detection technology [assessed up to 36 months]
In addition to overcoming false negatives caused by deficiencies in sensitivity, specificity, stability and flux of ctDNA methylation detection technology, and correcting false positive results that may be caused by AI, the combination of the two can avoid missed diagnosis, over-examination and over-treatment.
Eligibility Criteria
Criteria
Inclusion Criteria:
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Patients with pulmonary nodules confirmed by chest CT are not limited to single nodules;
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Nodule diameter 5-30mm
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Nodules include solid, semi-solid and ground glass nodules;
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Age 18-75, no gender limitation;
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The newly diagnosed patients did not receive surgery, radiotherapy, chemotherapy, targeted therapy or other tumor-related interventions;
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Sign informed consent.
Exclusion Criteria:
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Patients with diagnosed lung cancer and extrapulmonary malignant tumor;
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Pulmonary sarcoidosis, pulmonary vasculitis, pulmonary tuberculosis;
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Patients with poor compliance are expected to be unable to complete follow-up according to the study protocol;
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Major trauma requiring blood transfusion occurred within one week before enrollment;
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Pregnant and lactation patients.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | China-Japan Friendship Hospital | Beijing | Beijing | China | 100029 |
Sponsors and Collaborators
- Singlera Genomics Inc.
- China-Japan Friendship Hospital
Investigators
- Principal Investigator: Rui Liu, Doctor, Singlera Genomics Inc.
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 2019YFC1315803