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Artificial Intelligence-Assisted Pathological Diagnosis Technology Enhances the Quality and Efficiency of Tumor Patient Care—Development and Validation of an Early Warning Model for Hereditary Endocrine Tumor Syndromes Based on Multi-Omics and Multimodal Information

Artificial Intelligence-Assisted Pathological Diagnosis Technology Enhances the Quality and Efficiency of Tumor Patient Care—Development and Validation of an Early Warning Model for Hereditary Endocrine Tumor Syndromes Based on Multi-Omics and Multimodal Information

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600122235
Enrollment
Unknown
Registered
2026-04-10
Start date
2026-04-10
Completion date
Unknown
Last updated
2026-04-14

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

Conditions

Genetic tumour syndromes

Interventions

Genetic Endocrine Tumor Syndrome Observation Group:None

Sponsors

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1.All newly diagnosed patients meeting the following clinicopathological criteria were consecutively enrolled: (1) Tumor types: All pathologically confirmed high-risk tumor types, including parathyroid tumors, adrenocortical tumors, pheochromocytoma/paraganglioma, and pancreatic neuroendocrine tumors. (2) Clinical context: Regardless of personal or family history, enrollment was eligible if any of the following suggestive features were present: A. Younger age of onset (e.g., <40 years for parathyroid diseases, <50 years for pheochromocytoma). B. Multiple, bilateral, or recurrent tumors. C. Tumors with specific, rare pathological morphological features (e.g., hypercellularity, marked nuclear atypia). D. Accompanying clinical manifestations suggestive of other syndromes (e.g., refractory hypertension, mucocutaneous neuromas). 2.All multimodal data required for model operation were accessible, including complete clinical medical records, relevant imaging reports, paraffin-embedded pathological sections, and basic laboratory test results.

Exclusion criteria

Exclusion criteria: 1.Patients who have a confirmed genetic diagnosis of a hereditary endocrine tumor syndrome in themselves or their first-degree relatives. 2.Patients missing any core data essential for the model's operation, rendering the model unusable. 3.Patients unable to complete subsequent genetic testing. 4.Patients for whom genetic testing is already strongly indicated and planned by clinicians regardless of the model's output, due to a compelling family history or other typical clinical manifestations.

Design outcomes

Primary

MeasureTime frame
The area under the curve of the test subject;Accuracy;Sensitivity;Specificity;Positive predictive value and negative predictive value;

Countries

China

Contacts

Public ContactXiu Nie

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

niexiuyishi@126.com+86 27 8572 6125

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 17, 2026