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A prospective study of MMR/MSI status detection in gastric cancer based on deep learning artificial intelligence diagnosis versus immunohistochemistry

A prospective study of MMR/MSI status detection in gastric cancer based on deep learning artificial intelligence diagnosis versus immunohistochemistry

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500107637
Enrollment
Unknown
Registered
2025-08-15
Start date
2025-08-15
Completion date
Unknown
Last updated
2025-08-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric cancer

Interventions

Gold Standard:Definite MMR/MSI status by immunohistochemistry testing.
Index test:MSH2,MSH6,MLH1,PMS2

Sponsors

Sun Yat-sen University Cancer Center
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 100 Years

Inclusion criteria

Inclusion criteria: Inclusion Criteria:(1) Patients with primary gastric cancer(2) No preoperative treatment: including radiotherapy, chemotherapy, immunotherapy, etc.(3) H&E pathological sections sourced from surgical resection and/or biopsy of gastric cancer pathological specimens(4) Clear MMR/MSI status confirmed through immunohistochemical testing.

Exclusion criteria

Exclusion criteria: Exclusion Criteria: (1) The pathological section shows significant folds. (2) The pathological section is poorly scanned or not accurately focused. (3) The clinical pathological data of the patient is incomplete.

Design outcomes

Primary

MeasureTime frame
AUC;Accuracy;Sensitivity;Specificity;

Countries

China

Contacts

Public ContactXinke Zhang; Muyan Cai

Sun Yat-sen University Cancer Center

zhangxk@sysucc.org.cn+86 138 2609 4643

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026