An Artificial Intelligence Model for Aiding Claudin18.2 Expression Diagnosis in Gastric Adenocarcinoma

Development and Real-World Validation of an Intelligent Interpretation Model for Claudin18.2 Protein Expression in Digestive System Tumors

Status

Enrolling by invitation

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07274579

Enrollment

2000

Registered

2025-12-10

Start date

2025-10-01

Completion date

2028-08-01

Last updated

2026-02-10

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

Conditions

Digestive Oncology

Brief summary

The investigators plan to develop a deep learning-based automatic interpretation model for Claudin18.2(CLDN18.2) using the institution's and multiple other centers' extensive pathological resources of digestive system adenocarcinomas. This study will not only strictly follow the latest domestic expert consensus and standards, but also aims to address current pain points in manual interpretation. It seeks to provide technical support for standardizing, objectifying, and streamlining CLDN18.2 testing, thereby advancing the application of precision medicine in the diagnosis and treatment of digestive system diseases. The project has clear clinical necessity and broad application prospects.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

1. Age over 18 years. 2. Patients who underwent CLDN18.2 immunohistochemistry and H\&E staining. 3. Availability of complete pathology reports and clinical information.

Exclusion criteria

1.Patients with missing data or specimens not meeting quality control requirements for analysis.

Design outcomes

Primary

Measure	Time frame	Description
Area under ROC curve (AUC)	Diagnostic evaluation will be performed within 1 week when the whole slide images(WSIs) are obtained.	Area under the curve

Secondary

Measure	Time frame	Description
Specificity	Diagnostic evaluation will be performed within 1 week when the WSIs are obtained	The true negative rate (TNR) of the diagnostic platform, which is the ratio between the number of negative individuals correctly categorized by platform and the total number of actual negative individuals (%).
Sensitivity	Diagnostic evaluation will be performed within 1 week when the WSIs are obtained	The true positive rate (TPR) of the diagnostic platform, which is the ratio between the number of positive individuals correctly categorized by platform and the total number of actual positive individuals (%).

Countries

China

Contacts

STUDY_DIRECTORLi Liang

Nanfang Hospital, Southern Medical University

Outcome results