To Establish a Molecular Typing System for Early Diagnosis of Lung Cancer

NCT05432128 | Recruiting

• 1 other identifier: 2019YFC1315803
• Study Type: observational
• Target: 600
• Locations: 1 country
• Sites: 1

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.

Conditions

Lung Cancer

Keywords

ctDNA methylation; AI analysis of LDCT images

Outcome Measures

Primary Outcomes (2)

• To develop a molecular typing system for early screening and diagnosis of lung cancer

  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.

  assessed up to 36 months

• AI technology was combined with ctDNA methylation detection technology

  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.

  assessed up to 36 months

Study Arms (3)

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.

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

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.

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

600 patients who were newly diagnosed with pulmonary nodules confirmed by chest CT

You may qualify if:

• Patients with pulmonary nodules confirmed by chest CT are not limited to single nodules;
• Nodule diameter 5-30mm
• Nodules include solid, semi-solid and ground glass nodules;
• Age 18-75, no gender limitation;
• The newly diagnosed patients did not receive surgery, radiotherapy, chemotherapy, targeted therapy or other tumor-related interventions;
• Sign informed consent.

You may not qualify if:

• Patients with diagnosed lung cancer and extrapulmonary malignant tumor;
• Pulmonary sarcoidosis, pulmonary vasculitis, pulmonary tuberculosis;
• Patients with poor compliance are expected to be unable to complete follow-up according to the study protocol;
• Major trauma requiring blood transfusion occurred within one week before enrollment;
• Pregnant and lactation patients.

Sponsors & Collaborators

• Singlera Genomics Inc.: lead
• China-Japan Friendship Hospital: collaborator

Study Sites (1)

China-Japan Friendship Hospital

Beijing, Beijing Municipality, 100029, China

RECRUITING

Related Publications (1)

• Yang M, Yu H, Feng H, Duan J, Wang K, Tong B, Zhang Y, Li W, Wang Y, Liang C, Sun H, Zhong D, Wang B, Chen H, Gong C, He Q, Su Z, Liu R, Zhang P. Enhancing the differential diagnosis of small pulmonary nodules: a comprehensive model integrating plasma methylation, protein biomarkers, and LDCT imaging features. J Transl Med. 2024 Oct 31;22(1):984. doi: 10.1186/s12967-024-05723-5.

  PMID: 39482707 DERIVED

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Study Officials

• Rui Liu, Doctor

  Singlera Genomics Inc.

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Meng Yang, Bachelor

CONTACT

18618307980; 1943826591@qq.com

Sinan Wu

CONTACT

13810293738; tks0423@hotmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 20, 2022
• First Posted: June 27, 2022
• Study Start: January 1, 2020
• Primary Completion: December 31, 2025
• Study Completion: December 31, 2025
• Last Updated: April 17, 2024

Record last verified: 2024-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)