Breast Neoplasm FemaleNCT06102018
Diagnostic Biomarkers Exploration of Breast Cancer From Serum and Urine
An observational study of Breast Neoplasm Female, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University at 1 site in China.
Trial summary
The goal of this observational study is to find the diagnostic biomarkers in serum and urine from early breast cancer patients. The main questions it aims to answer are: compare the different biomarkers in serum and urine from breast cancer patients, benign lesions and healthy population. Read more about this study
- Who is it for?
- Ages 18 to 70 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Breast Neoplasm Female
- What is being tested?
- Collect blood and urine，pathological specimens if necessary
- How many people
- 150 participants
- Where
- 1 siteChina
- Study dates
- 22 Jun 2022to 1 Jul 2024
- 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 18 to 70 years
- Women only
- Healthy volunteers accepted
- Adult, Older adult
Study population: early breast cancer(Tis,T1-3N0-1M0)
Who may be able to join
- Signing the consent of informedness;
- Patients with breast mass who need surgery after examination;
- Cardiac ultrasound indicates that the blood score of the heart is within the normal range;
- ECOG≤0-2 points;
- Oversure function is acceptable.
Who cannot join
- Merge other malignant tumors such as gynecologic oncology;
- After evaluation, the internal organs are not suitable.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Guangzhou, Guangdong, 510120
Jieqiong Liu, 020-34078091, liujieqiong01@163.com
About this study
The goal of this observational study is to find the diagnostic biomarkers in serum and urine from early breast cancer patients. The main questions it aims to answer are:
- compare the different biomarkers in serum and urine from breast cancer patients, benign lesions and healthy population.
- construct the best diagnostic model by machine learning to distinguish breast cancer and non-breast cancer patients.
Participants, including breast and non-breast cancer patients will be asked to provides blood and urine during their diagnosis and treatment process without changing the original treatment. When necessary, specimens will be collected during the surgery，without affecting pathological diagnosis.
- Conditions
- Breast Neoplasm Female
- Being tested
- Collect blood and urine，pathological specimens if necessary
- Keywords
- Serum and Urine Biomarkers,Machine Learning,Diagnostic Model
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Collect blood and urine，pathological specimens if necessaryDiagnostic test
Use EDTA anticoagulant pipe to collect all blood 2ml, and collect 3ml of urine with sterile test tube
| Study group | Role | What they receive |
|---|---|---|
| Breast cancer patients | No intervention. The patients who are diagnosed as breast cancer by postoperative pathological. Receives: Diagnostic Test: Collect blood and urine，pathological specimens if necessary | |
| Patients with benign breast lesions | No intervention. The patients who are diagnosed asbenign breast lesions by postoperative pathological. Receives: Diagnostic Test: Collect blood and urine，pathological specimens if necessary | |
| Healthy population | No intervention. The volunteers. Receives: Diagnostic Test: Collect blood and urine，pathological specimens if necessary |
What is being measured
The primary outcome is the main question the study is designed to answer.
The different biomarkers in malignant and benign breast diseases
By analyzing the differences (eg:PCA, FC and et al.)in the composition of proteins in blood and urine, biomarkers with significant differences between the two groups will be obtained.
Measured: It is expected to be one to two years.
Diagnostic models used different biomarkers by machine learning
Using biomarkers that detect discrepancies, combined with machine learning to build early breast cancer diagnostic models.
Measured: Within half a year after the completion of the test.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Oct 2023
- Study start22 Jun 2022
- Primary completion1 Jul 2024 (estimated)
- Study completion1 Jul 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast Neoplasm FemaleStudies of the same condition, open and under way.
- More trials run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityThe 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06102018
- Sponsor's protocol ID
- SYSKY-2022-149-02
- Status last verified
- Oct 2023
- First submitted
- 9 May 2023
- Last updated
- 26 Oct 2023
- 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 26 Oct 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Diagnostic Biomarkers Exploration of Breast Cancer From Serum and Urine
- ClinicalTrials.gov ID
- NCT06102018
- Acronym / sponsor ID
- SYSKY-2022-149-02
- Conditions
- Breast Neoplasm Female
- Keywords
- Serum and Urine Biomarkers,Machine Learning,Diagnostic Model
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 22 Jun 2022 (actual)
- Primary completion
- 1 Jul 2024 (estimated)
- Study completion
- 1 Jul 2024 (estimated)
- First posted
- 26 Oct 2023 (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.
The goal of this observational study is to find the diagnostic biomarkers in serum and urine from early breast cancer patients. The main questions it aims to answer are:
- compare the different biomarkers in serum and urine from breast cancer patients, benign lesions and healthy population.
- construct the best diagnostic model by machine learning to distinguish breast cancer and non-breast cancer patients.
Participants, including breast and non-breast cancer patients will be asked to provides blood and urine during their diagnosis and treatment process without changing the original treatment. When necessary, specimens will be collected during the surgery，without affecting pathological diagnosis.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Breast cancer patients | – | Diagnostic Test: Collect blood and urine，pathological specimens if necessaryNo intervention. The patients who are diagnosed as breast cancer by postoperative pathological. |
| Patients with benign breast lesions | – | Diagnostic Test: Collect blood and urine，pathological specimens if necessaryNo intervention. The patients who are diagnosed asbenign breast lesions by postoperative pathological. |
| Healthy population | – | Diagnostic Test: Collect blood and urine，pathological specimens if necessaryNo intervention. The volunteers. |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- early breast cancer(Tis,T1-3N0-1M0)
Key inclusion criteria (5 listed)
- Signing the consent of informedness;
- Patients with breast mass who need surgery after examination;
- Cardiac ultrasound indicates that the blood score of the heart is within the normal range;
- ECOG≤0-2 points;
- Oversure function is acceptable.
Key exclusion criteria (2 listed)
- Merge other malignant tumors such as gynecologic oncology;
- After evaluation, the internal organs are not suitable.
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 |
|---|---|---|
| Collect blood and urine，pathological specimens if necessaryUse EDTA anticoagulant pipe to collect all blood 2ml, and collect 3ml of urine with sterile test tube | Diagnostic test | Breast cancer patients, Healthy population, Patients with benign breast lesions |
Primary outcome
The different biomarkers in malignant and benign breast diseases
Time frame: It is expected to be one to two years.
By analyzing the differences (eg:PCA, FC and et al.)in the composition of proteins in blood and urine, biomarkers with significant differences between the two groups will be obtained.
Diagnostic models used different biomarkers by machine learning
Time frame: Within half a year after the completion of the test.
Using biomarkers that detect discrepancies, combined with machine learning to build early breast cancer diagnostic models.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2023.
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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.
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 Breast Neoplasm Female, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University 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 2 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 26 Oct 2023. 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 Jieqiong Liu Ph.D. (13922272706, liujieqiong01@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The different biomarkers in malignant and benign breast diseases (time frame: It is expected to be one to two years.). The study lists 2 primary outcomes in all. 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 26 Oct 2023.