Recurrence and Prognosis Prediction Model for Gastric Cancer

NCT07243847 | Completed

• 1 other identifier: Prediction model(GC)
• Study Type: observational
• Target: 5,000
• Locations: 0 countries
• Sites: N/A

Brief 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. 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)

Outcome Measures

Primary Outcomes (1)

• recurrence

  3 year after surgery

Interventions

surgery and/or chemo OTHER

Deep learning model

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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.

You may qualify if:

• 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.

You may not qualify if:

• Presence of distant metastases detected preoperatively or intraoperatively; Prior neoadjuvant chemotherapy or radiotherapy; Incomplete general clinical data.

Sponsors & Collaborators

• Fudan University: lead

MeSH Terms

Conditions

Stomach Neoplasms

Condition Hierarchy (Ancestors)

Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Stomach Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical Professor

Study Record Dates

• First Submitted: November 16, 2025
• First Posted: November 24, 2025
• Study Start: January 1, 2000
• Primary Completion: October 1, 2025
• Study Completion: November 1, 2025
• Last Updated: November 24, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share