About this trial
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 criteria
This trial does not accept healthy volunteersQualifiers
(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.
Disqualifiers
(a).Diagnosed with malignant tumors; (b). Post liver transplantation; (c). Infected with HIV; (d). Expected survival time<1 year; (e). With marked organ dysfunctions(heart, brain, kidney, lung, endocrine system, blood, etc.) or psychiatric patients.
Trial population
The diagnostic rate of stage I liver cancer in China (AJCC-7 TNM staging system) is 17.5%. It is planned to increase the diagnostic rate of stage I liver cancer by 50% through this project, reaching 26.3%, power=0.9, a=0.05. PASS software calculated that a total of 958 liver cancer patients need to be enrolled in both groups. It is known that the annual incidence of liver cancer in patients with hepatitis B cirrhosis is 3% -6%. If calculated by 4%, it is estimated that the patients will be enrolled in one year, followed up for five years, and the lost rate is 10%, 5470 patients will need to be enrolled. Ultimately, this study plans to enroll 6000 patients.
Trial design
Cohort
Prospective
Treatments tested in this trial
AI folow-up system
Other interventionIn AI follow-up group, patients will be followed up by an AI system.
Treatment groups
Trial outcomes
Primary outcomes
Number and specific time of participants progressing to liver cancer
Number and specific time of participants progressing to liver cancer
Secondary outcomes
Survival time
Participants' survival time after being diagnosed with liver cancer.
Other outcomes
Incidence of adverse events for the participants
Incidence of ascite, hepatorenal system, hepatic encephalopathy, gastrointestinal bleeding, etc. for all the participants.
Sponsors and contacts
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