Gastric CancerNCT04957407
The Research of Constructing a Risk Assessment Model for Gastric Cancer Based on Machine Learning
An observational study of Gastric Cancer and Precancerous Lesion, run by Second Affiliated Hospital, Zhejiang University, School of Medicine at 2 sites in China.
Trial summary
Based on the gastric cancer database established earlier, this project explored the PG standard suitable for Chinese people, and further explored the establishment of machine learning model to stratify gastric cancer risk in the population, guide the frequency of gastroscopy screening, and extract important gastric… Read more about this study
- Who is it for?
- Ages 25 to 75 years
- Conditions the study is for
- Gastric Cancer, Precancerous Lesion, Mechine Learning
- What is being tested?
- pepsinogen
- Type of treatment
- Injection or infusion
- How many people
- 5,000 participants
- Where
- 2 sitesChina
- Study dates
- 1 Jan 2019to 31 Dec 2022
- 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 25 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: consecutive subjects who underwent regular health checkup at nine International Healthcare
Who may be able to join
- 1） intention to undergo gastroscopy during health checkup examination; and 2) 25-75 years of age
Who cannot join
- 1) a history of gastric ulcer, gastric polyp, or GC; 2) a history of gastrectomy; 3) treatment with a proton pump inhibitor in the last month; 4) contraindications to gastroscopy; 5) a history of Hp eradication; 6) a history of abdominal pain, abdominal distention, belching, acid reflux, nausea and other digestive tract symptoms within 1 month or 67) incomplete data.
Trial locations and contacts
2 sites in 1 country.
Yi Zhao, Master contact
China2 sites, 2 recruiting
- Recruiting
Zhejiang Provincial Hospital of Traditional Chinese Medicine
Hangzhou
Xuan Huang
- Recruiting
Ningbo cadres health center
Ningbo
Tong Huang
About this study
Based on the gastric cancer database established earlier, this project explored the PG standard suitable for Chinese people, and further explored the establishment of machine learning model to stratify gastric cancer risk in the population, guide the frequency of gastroscopy screening, and extract important gastric cancer risk factors from it.Establish electronic health records of gastric organs, track the development and outcome of gastric diseases through deep learning method, in order to predict the development and outcome of gastric diseases;Then, the simulation hypothesis deductive method is used to compare the outcomes that may be caused by different lifestyles with the help of deep learning model, so as to guide patients to develop a better lifestyle and explore the establishment of health management paths for gastric cancer patients and high-risk groups in China.
- Conditions
- Gastric Cancer, Precancerous Lesion, Mechine Learning
- Being tested
- pepsinogen
- Medical subject headings
- Stomach Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
pepsinogenOther
diagnostic value of pepsinogen for severe atrophy and gastric cancer
| Study group | Role | What they receive |
|---|---|---|
| non-atrophic gastritis | OLGA-0 group；OLGA (Operative Link on Gastritis Assessment) | |
| mild-moderate atrophic gastritis | OLGA I-II group；OLGA (Operative Link on Gastritis Assessment) | |
| severe atrophic gastritis | OLGA III-IV group；OLGA (Operative Link on Gastritis Assessment) Receives: Other: pepsinogen | |
| gastric cancer | gastric cancer Receives: Other: pepsinogen |
What is being measured
The primary outcome is the main question the study is designed to answer.
pepsinogen value for precanceous lesion and Gastric cancer
pepsinogen value for precanceous lesion and Gastric cancer
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Jul 2021
- Study start1 Jan 2019
- Primary completion31 May 2022 (estimated)
- Study completion31 Dec 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gastric CancerStudies of the same condition, open and under way.
- More trials run by Second Affiliated Hospital, Zhejiang University, School of MedicineThe 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
- 5,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Yuling Tong, Dr., Principal investigator, 2nd affiliated hospital of Zhejiang University, school of medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04957407
- Sponsor's protocol ID
- 71804161
- Status last verified
- Jun 2021
- First submitted
- 8 Jul 2021
- Last updated
- 12 Jul 2021
- 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 12 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Research of Constructing a Risk Assessment Model for Gastric Cancer Based on Machine Learning
- ClinicalTrials.gov ID
- NCT04957407
- Acronym / sponsor ID
- 71804161
- Conditions
- Gastric Cancer, Precancerous Lesion, Mechine Learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 5,000 participants (estimated)
- Lead sponsor
- Second Affiliated Hospital, Zhejiang University, School of MedicineUniversity, hospital or other
- Study start
- 1 Jan 2019 (actual)
- Primary completion
- 31 May 2022 (estimated)
- Study completion
- 31 Dec 2022 (estimated)
- First posted
- 12 Jul 2021 (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.
Based on the gastric cancer database established earlier, this project explored the PG standard suitable for Chinese people, and further explored the establishment of machine learning model to stratify gastric cancer risk in the population, guide the frequency of gastroscopy screening, and extract important gastric cancer risk factors from it.Establish electronic health records of gastric organs, track the development and outcome of gastric diseases through deep learning method, in order to predict the development and outcome of gastric diseases;Then, the simulation hypothesis deductive method is used to compare the outcomes that may be caused by different lifestyles with the help of deep learning model, so as to guide patients to develop a better lifestyle and explore the establishment of health management paths for gastric cancer patients and high-risk groups in China.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| non-atrophic gastritis | – | –OLGA-0 group；OLGA (Operative Link on Gastritis Assessment) |
| mild-moderate atrophic gastritis | – | –OLGA I-II group；OLGA (Operative Link on Gastritis Assessment) |
| severe atrophic gastritis | – | Other: pepsinogenOLGA III-IV group；OLGA (Operative Link on Gastritis Assessment) |
| gastric cancer | – | Other: pepsinogengastric cancer |
Who may qualify
- Ages
- 25 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- consecutive subjects who underwent regular health checkup at nine International Healthcare
Key inclusion criteria (1 listed)
- 1） intention to undergo gastroscopy during health checkup examination; and 2) 25-75 years of age
Key exclusion criteria (1 listed)
- 1) a history of gastric ulcer, gastric polyp, or GC; 2) a history of gastrectomy; 3) treatment with a proton pump inhibitor in the last month; 4) contraindications to gastroscopy; 5) a history of Hp eradication; 6) a history of abdominal pain, abdominal distention, belching, acid reflux, nausea and other digestive tract symptoms within 1 month or 67) incomplete data.
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 |
|---|---|---|
| pepsinogendiagnostic value of pepsinogen for severe atrophy and gastric cancer | Other | gastric cancer, severe atrophic gastritis |
Primary outcome
pepsinogen value for precanceous lesion and Gastric cancer
Time frame: 1 year
pepsinogen value for precanceous lesion and Gastric cancer
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Jul 2021.
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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.
Yi Zhao, Master contact
Yuling Tong, Dr. principal investigator
2nd affiliated hospital of Zhejiang University, school of medicine
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Gastric Cancer and Precancerous Lesion, run by Second Affiliated Hospital, Zhejiang University, School of Medicine at 2 sites 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 1 inclusion and 1 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 12 Jul 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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 Yuling Tong, Dr. (1375821220, tongyl0313@zju.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
pepsinogen value for precanceous lesion and Gastric cancer (time frame: 1 year). 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 12 Jul 2021.