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

Not yet recruiting
Conditions
Liver Metastases
Colorectal Cancer
Interventions
Registration Number
NCT05354674
Lead Sponsor
Fudan University
Brief 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.

Recruitment & Eligibility

Status
NOT_YET_RECRUITING
Sex
All
Target Recruitment
302
Inclusion Criteria

Age 18-75 years; Histologically proven colorectal adenocarcinoma; Simultaneous liver-limited metastases; Initially unresectable liver metastases determined by a local MDT; Life expectancy of > 3 months; RAS mutation and BRAF V600E wild-type; ECOG 0-1; Available PET/CT imaging before treatment; Available colonoscopy biopsy specimens before treatment

Exclusion Criteria

Previous systemic treatment for metastatic disease; Previous surgery for metastatic disease; Extrahepatic metastases; Unresectable primary tumor; Major cardiovascular events (myocardial infarction, severe/unstable angina, congestive heart failure, CVA) within 12 months before randomisation; Acute or subacute intestinal obstruction; Second primary malignancy within the past 5 years; Drug or alcohol abuse; No legal capacity or limited legal capacity; Pregnant or lactating women; Uncontrolled hypertension, or unsatisfactory blood pressure control with ≥3 antihypertensive drugs; Peripheral neuropathy;

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
ARM ABevacizumabChemotherapy regimens are determined based on the clinical experience of specialists
ARM BBevacizumabChemotherapy regimens are determined based on the multimodal deep learning signature
Primary Outcome Measures
NameTimeMethod
response rate6 months

response rate will be assessed by local MDT every two months

progression free survival3 years

progression free survival will be assessed by local MDT every two months during

Secondary Outcome Measures
NameTimeMethod
overall survival5 years

overall survival will be assessed by researchers every two months during treatment, and telephone follow-up every three month after treatment

Trial Locations

Locations (1)

Zhongshan hospital

🇨🇳

Shanghai, Shanghai, China

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