NCT05354674

Multimodal Deep Learning Signature for Evaluation of Response to Bevacizumab in Patient With Colorectal Cancer Liver Metastasis

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 302 (estimated)
• Sponsor: Fudan University · Academic / Other
• Sex: All
• Age: 18 Years – 79 Years
• Healthy volunteers: Not accepted

Summary

Establishment and validation of the deep learning signature of bevacizumab efficacy in initially unresectable CRLM patients

Detailed description

Initially unresectable CRLM patients were included in this study. The tumor response was assessed by local MDT group. The signature will classified patients into responder or non-responder group. We will administer mFOLFOX6+bevacizumab regimen to responders, and FOLFOXIRI regimen to non-responders.

Conditions

• Colorectal Cancer
• Liver Metastases

Interventions

Type	Name	Description
DRUG	Bevacizumab	AEM A：The specialist's decision to add bevacizumab to chemotherapy will be based on their own judgment ARM B：The patient's PET/CT imaging, pathology, and clinical information were input into the signature, and the FOLFOX+Bevacizumab regimen was selected when the output label was 1. FOLFOXIRI chemotherapy regimen was selected when the output label was 0

Timeline

• Start date: 2023-09-01
• Primary completion: 2025-07-01
• Completion: 2028-07-01
• First posted: 2022-04-29
• Last updated: 2023-07-13

Locations

1 site across 1 country: China