Gastric Cancer (GC)NCT07243847
Recurrence and Prognosis Prediction Model for Gastric Cancer
An observational study of Gastric Cancer (GC), run by Fudan University.
Trial summary
This study, utilizing a large-scale multicenter Eastern database, has established a Deep Learning-based predictive model for recurrence following gastric cancer surgery, which demonstrates robust discriminatory power for early recurrence. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Gastric Cancer (GC)
- What is being tested?
- surgery and/or chemo
- How many people
- 5,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Jan 2000to 1 Nov 2025
- 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 Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: A retrospective analysis was conducted on the clinicopathological data of patients who underwent radical gastrectomy for gastric cancer between 2001 and 2022 at 13 tertiary hospitals in China.
Who may be able to join
- Pathologically confirmed gastric adenocarcinoma; No distant metastases confirmed by preoperative examinations such as chest X-ray, abdominal ultrasonography, and upper abdominal computed tomography; Achievement of R0 resection.
Who cannot join
- Presence of distant metastases detected preoperatively or intraoperatively; Prior neoadjuvant chemotherapy or radiotherapy; Incomplete general clinical data.
About this study
Official title: Artificial Deep Learning-Based Model for Predicting Postoperative Recurrence in Gastric Cancer
This study, utilizing a large-scale multicenter Eastern database, has established a Deep Learning-based predictive model for recurrence following gastric cancer surgery, which demonstrates robust discriminatory power for early recurrence. Furthermore, the individualized recurrence probability generated by this model can predict long-term postoperative prognosis and effectively stratify patients based on risk, thereby guiding personalized treatment choices. This individualized risk probability is also applicable to both adjuvant chemotherapy and neoadjuvant chemotherapy populations, offering valuable support for precision treatment in gastric cancer.
- Conditions
- Gastric Cancer (GC)
- Being tested
- surgery and/or chemo
- Medical subject headings
- Stomach Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
surgery and/or chemoOther
Deep learning model
What is being measured
The primary outcome is the main question the study is designed to answer.
recurrence
Measured: 3 year after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Nov 2025
- Study start1 Jan 2000
- Primary completion1 Oct 2025
- Study completion1 Nov 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Gastric Cancer (GC)Studies of the same condition, open and under way.
- More trials run by Fudan 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
- Retrospective
- Enrolment
- 5,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- Fudan University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jun Lu, Fudan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07243847
- Sponsor's protocol ID
- Prediction model(GC)
- Status last verified
- Nov 2025
- First submitted
- 16 Nov 2025
- Last updated
- 24 Nov 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Nov 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Deep Learning-Based Model for Predicting Postoperative Recurrence in Gastric Cancer
- ClinicalTrials.gov ID
- NCT07243847
- Acronym / sponsor ID
- Prediction model(GC)
- Conditions
- Gastric Cancer (GC)
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 5,000 participants (actual)
- Lead sponsor
- Fudan UniversityUniversity, hospital or other
- Study start
- 1 Jan 2000 (actual)
- Primary completion
- 1 Oct 2025 (actual)
- Study completion
- 1 Nov 2025 (actual)
- First posted
- 24 Nov 2025 (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.
This study, utilizing a large-scale multicenter Eastern database, has established a Deep Learning-based predictive model for recurrence following gastric cancer surgery, which demonstrates robust discriminatory power for early recurrence. Furthermore, the individualized recurrence probability generated by this model can predict long-term postoperative prognosis and effectively stratify patients based on risk, thereby guiding personalized treatment choices. This individualized risk probability is also applicable to both adjuvant chemotherapy and neoadjuvant chemotherapy populations, offering valuable support for precision treatment in gastric cancer.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- A retrospective analysis was conducted on the clinicopathological data of patients who underwent radical gastrectomy for gastric cancer between 2001 and 2022 at 13 tertiary hospitals in China.
Key inclusion criteria (1 listed)
- Pathologically confirmed gastric adenocarcinoma; No distant metastases confirmed by preoperative examinations such as chest X-ray, abdominal ultrasonography, and upper abdominal computed tomography; Achievement of R0 resection.
Key exclusion criteria (1 listed)
- Presence of distant metastases detected preoperatively or intraoperatively; Prior neoadjuvant chemotherapy or radiotherapy; Incomplete general clinical 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 |
|---|---|---|
| surgery and/or chemoDeep learning model | Other | – |
Primary outcome
recurrence
Time frame: 3 year after surgery
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Nov 2025.
- Individual participant dataSharing planned: No
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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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Gastric Cancer (GC), run by Fudan University.
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: finished, as of the sponsor's last update on 24 Nov 2025. Status can change between updates, so confirm with the study contact before making plans.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
recurrence (time frame: 3 year after 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 24 Nov 2025.