Clinical Trials Logo

Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04558255
Other study ID # PTHO1903
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date January 1, 2020
Est. completion date December 1, 2021

Study information

Verified date September 2020
Source Peking University People's Hospital
Contact Kezhong Chen, M.D.
Phone +8613488752289
Email mdkzchen@163.com
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Lung cancer is the most common cancer with the highest morbidity and mortality in the world. Stagement is closely related to the 5 years of survival rate of patients. The postoperative 5-year survival rate is above 90% for stage ⅠA lung cancer patients, while the 5-year survival rate of stage IV lung cancer patients is less than 5%. Therefore, early screening and diagnosis for lung cancer is a key method to reduce lung cancer mortality and prolong survival for patients.

At present, low-dose computed tomography (LDCT) is the most effective method for early detection of lung cancer. In addition to imaging examination, plasma tumor markers detection is also a common clinical detection method for tumor screening and postoperative monitoring.

Liquid biopsy is a non-invasive or minimally invasive method for testing blood or other liquid samples to analyze tumor-related markers including nucleic acids and proteins. Several studies have explored the detection of hot spot gene mutations, methylation and methylation changes of DNA, protein markers and autoantibodies in peripheral blood in lung cancer patients. Liquid biopsy has generally become the most popular field for early diagnosis of lung cancer.

Based above, it is necessary to combine multi-omics methods to improve the detection of early stage lung cancer. In our study, we intend to integrate molecular features obtained through liquid biopsy and clinical data of lung cancer patients, and develop and prospectively validate a machine-learning method which can robustly discriminate early-stage lung cancer patients from controls.


Recruitment information / eligibility

Status Recruiting
Enrollment 1000
Est. completion date December 1, 2021
Est. primary completion date December 1, 2020
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 20 Years to 75 Years
Eligibility Inclusion Criteria:

- Enrolled patients are newly diagnosed patients

- In patients diagnosed as pulmonary nodules by imaging, benign and malignant conditions of the nodules are determined by postoperative pathology after surgical resection

- There is clear cancer stage information

- In addition to pulmonary nodules, there are no suspicious nodules of other organs

- No previous history of malignant tumor

Exclusion Criteria:

- Patients with a history of malignant tumor

- Patients with suspectednodules in other parts of the body at the time of diagnosis

- Patients who have previously received surgery, chemotherapy or radiotherapy for pulmonary lesions

- Patients with severe blood lipid in peripheral blood extracted which affects subsequent detection

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
A machine-learning method which can robustly discriminate early-stage lung cancer patients from controls
In our study, we intend to integrate molecular features obtained through liquid biopsy and clinical data of lung cancer patients, and develop and prospectively validate a machine-learning method which can robustly discriminate early-stage lung cancer patients from controls.

Locations

Country Name City State
China Peking University People's Hospital Beijing Beijing

Sponsors (1)

Lead Sponsor Collaborator
Peking University People's Hospital

Country where clinical trial is conducted

China, 

Outcome

Type Measure Description Time frame Safety issue
Primary Rates of malignant and benign pulmonary nodules measured by the postoperative pathology After the sugery of each patients with pulmonary nodules, we will get the clinicopathologic characteristics of the patients. Tumor stage and grade will be evaluated by us and rates of malignant and benign pulmonary nodules will be the primary outcome which we follow. 5 days after the surgery
See also
  Status Clinical Trial Phase
Completed NCT03918538 - A Series of Study in Testing Efficacy of Pulmonary Rehabilitation Interventions in Lung Cancer Survivors N/A
Recruiting NCT05078918 - Comprehensive Care Program for Their Return to Normal Life Among Lung Cancer Survivors N/A
Active, not recruiting NCT04548830 - Safety of Lung Cryobiopsy in People With Cancer Phase 2
Completed NCT04633850 - Implementation of Adjuvants in Intercostal Nerve Blockades for Thoracoscopic Surgery in Pulmonary Cancer Patients
Recruiting NCT06037954 - A Study of Mental Health Care in People With Cancer N/A
Recruiting NCT06006390 - CEA Targeting Chimeric Antigen Receptor T Lymphocytes (CAR-T) in the Treatment of CEA Positive Advanced Solid Tumors Phase 1/Phase 2
Recruiting NCT05583916 - Same Day Discharge for Video-Assisted Thoracoscopic Surgery (VATS) Lung Surgery N/A
Completed NCT00341939 - Retrospective Analysis of a Drug-Metabolizing Genotype in Cancer Patients and Correlation With Pharmacokinetic and Pharmacodynamics Data
Not yet recruiting NCT06376253 - A Phase I Study of [177Lu]Lu-EVS459 in Patients With Ovarian and Lung Cancers Phase 1
Recruiting NCT05898594 - Lung Cancer Screening in High-risk Black Women N/A
Active, not recruiting NCT05060432 - Study of EOS-448 With Standard of Care and/or Investigational Therapies in Participants With Advanced Solid Tumors Phase 1/Phase 2
Active, not recruiting NCT03575793 - A Phase I/II Study of Nivolumab, Ipilimumab and Plinabulin in Patients With Recurrent Small Cell Lung Cancer Phase 1/Phase 2
Active, not recruiting NCT03667716 - COM701 (an Inhibitor of PVRIG) in Subjects With Advanced Solid Tumors. Phase 1
Terminated NCT01624090 - Mithramycin for Lung, Esophagus, and Other Chest Cancers Phase 2
Terminated NCT03275688 - NanoSpectrometer Biomarker Discovery and Confirmation Study
Not yet recruiting NCT04931420 - Study Comparing Standard of Care Chemotherapy With/ Without Sequential Cytoreductive Surgery for Patients With Metastatic Foregut Cancer and Undetectable Circulating Tumor-Deoxyribose Nucleic Acid Levels Phase 2
Recruiting NCT06010862 - Clinical Study of CEA-targeted CAR-T Therapy for CEA-positive Advanced/Metastatic Malignant Solid Tumors Phase 1
Recruiting NCT06052449 - Assessing Social Determinants of Health to Increase Cancer Screening N/A
Not yet recruiting NCT06017271 - Predictive Value of Epicardial Adipose Tissue for Pulmonary Embolism and Death in Patients With Lung Cancer
Recruiting NCT05787522 - Efficacy and Safety of AI-assisted Radiotherapy Contouring Software for Thoracic Organs at Risk