Lung CancerNCT04558255
A Preliminary Study on the Detection of Plasma Markers in Early Diagnosis for Lung Cancer
An observational study of Lung Cancer, run by Peking University People's Hospital at 1 site in China.
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… Read more about this study
- Who is it for?
- Ages 20 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Lung Cancer
- How many people
- 1,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Jan 2020to 1 Dec 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 20 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: 500 cases will be enrolled including 100 cases of benign pulmonary nodules, 300 cases of stage I and II lung cancer, 100 cases of stage III lung cancer. All enrolled patients are newly diagnosed as pulmonary nodules by imaging, benign and malignant conditions of the nodules are determined by postoperative pathology after surgical resection. All clinacal data including cancer stage information are available.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Peking University People's Hospital
Beijing, Beijing Municipality, 100044
Chen Kezhong, M.D.
About this study
Official title: Plasma Biomarkers as a Non-invasive Approach for Early Diagnosis of Lung Cancer
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.
Read more
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.
- Conditions
- Lung Cancer
- Being tested
- A machine-learning method which can robustly discriminate early-stage lung cancer patients from controls
- Medical subject headings
- Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
A machine-learning method which can robustly discriminate early-stage lung cancer patients from controlsDiagnostic test
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.
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 5 days after the surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Sep 2020
- Study start1 Jan 2020
- Primary completion1 Dec 2020 (estimated)
- Study completion1 Dec 2021 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung CancerStudies of the same condition, open and under way.
- More trials run by Peking University People's HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Peking University People's Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jun Wang, Peking University People's Hospital
- Investigators
- Jun Wang, M.D., Study director, Peking University People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04558255
- Sponsor's protocol ID
- PTHO1903
- Status last verified
- Sep 2020
- First submitted
- 13 Sep 2020
- Last updated
- 22 Sep 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 22 Sep 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Plasma Biomarkers as a Non-invasive Approach for Early Diagnosis of Lung Cancer
- ClinicalTrials.gov ID
- NCT04558255
- Acronym / sponsor ID
- PTHO1903
- Conditions
- Lung Cancer
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Peking University People's HospitalUniversity, hospital or other
- Study start
- 1 Jan 2020 (actual)
- Primary completion
- 1 Dec 2020 (estimated)
- Study completion
- 1 Dec 2021 (estimated)
- First posted
- 22 Sep 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
Who may qualify
- Ages
- 20 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- 500 cases will be enrolled including 100 cases of benign pulmonary nodules, 300 cases of stage I and II lung cancer, 100 cases of stage III lung cancer. All enrolled patients are newly diagnosed as pulmonary nodules by imaging, benign and malignant conditions of the nodules are determined by postoperative pathology after surgical resection. All clinacal data including cancer stage information are available.
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (4 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| A machine-learning method which can robustly discriminate early-stage lung cancer patients from controlsIn 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. | Diagnostic test | – |
Primary outcome
Rates of malignant and benign pulmonary nodules measured by the postoperative pathology
Time frame: 5 days after the surgery
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.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Sep 2020.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jun Wang, M.D. study director
Peking University People's Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Cancer, run by Peking University People's Hospital at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 22 Sep 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Kezhong Chen, M.D. (+8613488752289, mdkzchen@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Rates of malignant and benign pulmonary nodules measured by the postoperative pathology (time frame: 5 days after the surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Sep 2020.