Establishment and validation of the deep learning model of Cetuximab efficacy in simultaneous RAS wild unresectable CRLM patients
Ras wild unresectable CRLM patients with primary tumor resection followed by Cetuximab in combination with chemotherapy were included in this study. The tumor response was assessed by local MDT group. Based on tumor response, almost 100 CRLM patients were classified into two groups (Clinician drived regimen vs Multi-omics model drived regimen). They will be the prospective cohort to validate our deep learning model for predicting Cetuximab efficacy.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
100
AEM A:The specialist's decision to add cetuximab to chemotherapy will be based on their own judgment ARM B:The patient's CT imaging,genetic mutation information were input into the signature, and the FOLFOX+cetuximab regimen was selected when the output label was 1. FOLFOX+bevacizumab chemotherapy regimen was selected when the output label was 0
Zhongshan Hospital, Fudan University
Shanghai, Shanghai Municipality, China
Zhongshan hosptial, Fudan University
Shanghai, China
response rate
response rate will be assessed by local MDT
Time frame: 6 months
progression free survival
progression free survival will be assessed by local MDT every two months during treatment, and telephone follow-up every three month after treatment
Time frame: 3 years
overall survival
overall survival will be assessed by researchers every two months during treatment, and telephone follow-up every three month after treatment
Time frame: 3 years
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