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

Study Overview
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Brief Summary
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Establishment and validation of the deep learning signature of bevacizumab efficacy in initially unresectable CRLM patients

Detailed Description
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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.

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

Conditions
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Colorectal Cancer, Liver Metastases

Intervention / Treatment
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* Drug: Bevacizumab


Participation Criteria
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Eligibility Criteria
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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;

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 79 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| ARM A<br>Chemotherapy regimens are determined based on the clinical experience of specialists | Drug: Bevacizumab<br>* 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<br>|
| ARM B<br>Chemotherapy regimens are determined based on the multimodal deep learning signature | Drug: Bevacizumab<br>* 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<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| response rate | response rate will be assessed by local MDT every two months | 6 months | 
| progression free survival | progression free survival will be assessed by local MDT every two months during | 3 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| overall survival | overall survival will be assessed by researchers every two months during treatment, and telephone follow-up every three month after treatment | 5 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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colorectal cancer liver metastasis, bevacizumab, radiomics, multimodal