Research on Risk Assessment and Intervention of HBV-Related Liver Cancer Based on Multimodal Data Fusion
Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
SUMMARY
Liver cancer is a severe disease worldwide. The incidence and mortality rates of liver cancer in China is the highest in the world. This project aims to perform a prospective, multi-center, large sample cohort study for HBV related high-risk individuals. Based on multimodal data fusion and AI technique, stratified management and follow-up system are conducted for HBV-related high-risk populations of liver cancer, in order to improve the early diagnosis rate of liver cancer.
Eligibility
Participation Requirements
Sex: All
Minimum Age: 30
Maximum Age: 75
Healthy Volunteers: f
View:
• (a).Positive for Hepatitis B surface antigen; (b).Ultrasound/CT/MR indicates liver cirrhosis; (c). Type II diabetes; (d). Has family history of liver cirrhosis/ liver cancer; (e). Long term alcohol consumption history (\>5 years), equivalent to alcohol consumption of ≥ 40g/d for males and ≥ 20g/d for females; (f). Liver histology Metavir fibrosis score F3 or above; (g). Fibroscan value (LSM) ≥ 8.0kPa.
Locations
Other Locations
China
Third Affiliated Hospital of Sun Yat-sen University
RECRUITING
Guangzhou
Contact Information
Primary
Bingliang Prof. Lin
linbingl@mail.sysu.edu.cn
+86-20-85252081
Time Frame
Start Date:2025-05-10
Estimated Completion Date:2032-12-30
Participants
Target number of participants:6000
Treatments
Routine follow-up group
Patients in this cohor will be followed up every 24 weeks (or every 8-12 weeks for extremely high-risk population) routinely. Alpha fetoprotein, PIVKA-II, liver imaging examination, liver function, et al will be performed for these patients at each follow-up point.
AI system follow-up group
Patients in this cohor will be followed up every 24 weeks (or every 8-12 weeks for extremely high-risk population). Alpha fetoprotein, PIVKA-II, liver imaging examination, liver function, et al will be performed for these patients at each follow up point. An AI system will be used to manage follow-up patients.