Actively Recruiting
Deep Learning-Based Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
Led by Chinese Academy of Sciences · Updated on 2023-09-28
200
Participants Needed
22
Research Sites
278 weeks
Total Duration
On this page
Sponsors
C
Chinese Academy of Sciences
Lead Sponsor
P
Peking University Cancer Hospital & Institute
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are developing a deep learning model to predict how well patients with advanced gastric cancer will respond to neoadjuvant chemotherapy. This model uses data from patients' CT scans, biopsy pathology images, and clinical information to forecast the effectiveness of chemotherapy and the patient's prognosis. The study aims to assist personalized treatment decisions for gastric cancer patients by improving prediction accuracy. Participants diagnosed with advanced gastric cancer will undergo standard neoadjuvant chemotherapy according to clinical guidelines. Data collected include CT imaging taken within one month before treatment, pathology images from gastric tumor biopsies, and detailed clinical profiles such as tumor markers and staging. The study includes both retrospective data from 1,800 patients used for model training and validation, and prospective data from 200 patients for model performance evaluation. During the study, researchers will gather clinical, imaging, and pathology data to develop and test the AI model. The primary outcomes are the accuracy and area under the curve (AUC) for predicting tumor regression grade (TRG) within two months. Secondary outcomes include progression-free survival at three years and overall survival at five years. Participants' treatment details and prognosis will be closely monitored, with all study procedures designed to improve future personalized care for gastric cancer patients.
CONDITIONS
Brief Title
AI Prediction of Gastric Cancer Response to Neoadjuvant Chemotherapy
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age 18 years or older
- Pathologically diagnosed with advanced gastric cancer according to AJCC TNM staging
- No prior systemic anti-cancer treatments before neoadjuvant chemotherapy
- No surgery for local progression or distant metastasis before study
- Receiving standard neoadjuvant chemotherapy as per clinical guidelines with documented treatment details
- CT imaging and biopsy pathology images taken within one month before starting neoadjuvant treatment
- Comprehensive preoperative clinical information and post-operative tumor regression grade (TRG) available
You will not qualify if you...
- Unclear CT or pathology images preventing lesion assessment
- Diagnosis of any other concurrent tumors
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Varies according to specific chemotherapy regimen
Participants receive neoadjuvant chemotherapy according to established clinical guidelines to treat advanced gastric cancer.
Visits scheduled according to chemotherapy cycles as per clinical guidelines
Duration - Up to 2 months
Clinical, imaging, and pathology data are collected before and after neoadjuvant chemotherapy to develop and validate the AI prediction model.
1 visit for post-treatment assessment
Duration - Up to 5 years
Participants are monitored for progression-free survival and overall survival over several years to evaluate long-term outcomes.
Periodic follow-up visits over 3 to 5 years
Trial Site Locations
Total: 22 locations
1
Cancer Institute and Hospital, Chinese Academy of Medical Sciences
Beijing, China
Not Yet Recruiting
2
Peking Union Medical College Hospital
Beijing, China
Not Yet Recruiting
3
Peking University Cancer Hospital & Institute
Beijing, China
Actively Recruiting
4
Peking University People's Hospital
Beijing, China
Not Yet Recruiting
5
Xiangya Hospital of Central South University
Changsha, China
Not Yet Recruiting
6
Fujian Cancer Hospital
Fuzhou, China
Not Yet Recruiting
7
Fujian Medical University Union Hospital
Fuzhou, China
Actively Recruiting
8
Affiliated Cancer Hospital & Institute of Guangzhou Medical University
Guangzhou, China
Not Yet Recruiting
9
First Affiliated Hospital, Sun Yat-Sen University
Guangzhou, China
Not Yet Recruiting
10
Nanfang Hospital of Southern Medical University
Guangzhou, China
Not Yet Recruiting
11
Sixth Affiliated Hospital, Sun Yat-sen University
Guangzhou, China
Actively Recruiting
12
Yunnan Cancer Hospital
Kunming, China
Actively Recruiting
13
Cancer Hospital of Guangxi Medical University
Nanning, China
Not Yet Recruiting
14
The Affiliated Hospital of Qingdao University
Qingdao, China
Not Yet Recruiting
15
Ruijin Hospital
Shanghai, China
Not Yet Recruiting
16
First Hospital of China Medical University
Shenyang, China
Not Yet Recruiting
17
The First Affiliated Hospital of Soochow University
Suzhou, China
Not Yet Recruiting
18
Tianjin Medical University Cancer Institute and Hospital
Tianjin, China
Not Yet Recruiting
19
Henan Cancer Hospital
Zhengzhou, China
Actively Recruiting
20
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, China
Actively Recruiting
21
Zhenjiang First People's Hospital
Zhenjiang, China
Actively Recruiting
22
San Raffaele University Hospital, Italy
Milan, Italy
Actively Recruiting
Research Team
D
Di Dong, Ph.D.
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
1
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