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A male-ABCD algorithm for hepatocellular carcinoma risk prediction in HBsAg carriers
Yuting Wang1, Minjie Wang2, He Li3
1State Key Lab of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
Insights
A new Male-ABCD algorithm predicts hepatocellular carcinoma (HCC) risk in men with hepatitis B. This tool aids in precise HCC surveillance for carriers.
Area of Science:
- Hepatology
- Oncology
- Epidemiology
Background:
- Hepatocellular carcinoma (HCC) development in hepatitis B surface antigen (HBsAg) carriers exhibits gender disparity.
- Underlying liver diseases influencing HCC risk show variations in laboratory test results.
Purpose of the Study:
- To construct a risk-stratified HCC prediction model specifically for HBsAg-positive adult males.
- To develop a precise surveillance tool for identifying individuals at high risk of HCC.
Main Methods:
- A multi-center, population-based liver cancer screening study included 6,153 HBsAg-positive males aged 35-69.
- Logistic regression models identified risk factors, leading to a point-based Male-ABCD algorithm using age, GGT, platelets, white blood cells, DCP, and AFP.
- The model's operating characteristics were evaluated using training and validation cohorts over a 2-year follow-up period with HCC screening.
Main Results:
- The Male-ABCD algorithm, incorporating age, GGT, platelets, white cells, DCP, and AFP, achieved an area under the receiver operating characteristic curve of 0.91.
- The algorithm demonstrated high sensitivity for HCC identification, reaching 100% at a risk score of 1.5 points.
- Different risk score thresholds allowed for effective stratification, identifying low-risk groups while maintaining high sensitivity for HCC detection.
Conclusions:
- The developed Male-ABCD algorithm effectively predicts individual HCC risk in HBsAg-positive males within a short term.
- This algorithm facilitates precision surveillance strategies for hepatocellular carcinoma in this specific population.
Objective:
Hepatocellular carcinoma (HCC) development among hepatitis B surface antigen (HBsAg) carriers shows gender disparity, influenced by underlying liver diseases that display variations in laboratory tests. We aimed to construct a risk-stratified HCC prediction model for HBsAg-positive male adults.
Methods:
HBsAg-positive males of 35-69 years old (N=6,153) were included from a multi-center population-based liver cancer screening study. Randomly, three centers were set as training, the other three centers as validation. Within 2 years since initiation, we administrated at least two rounds of HCC screening using B-ultrasonography and α-fetoprotein (AFP). We used logistic regression models to determine potential risk factors, built and examined the operating characteristics of a point-based algorithm for HCC risk prediction.
Results:
With 2 years of follow-up, 302 HCC cases were diagnosed. A male-ABCD algorithm was constructed including participant's age, blood levels of GGT (γ-glutamyl-transpeptidase), counts of platelets, white cells, concentration of DCP (des-γ-carboxy-prothrombin) and AFP, with scores ranging from 0 to 18.3. The area under receiver operating characteristic was 0.91 (0.90-0.93), larger than existing models. At 1.5 points of risk score, 26.10% of the participants in training cohort and 14.94% in validation cohort were recognized at low risk, with sensitivity of identifying HCC remained 100%. At 2.5 points, 46.51% of the participants in training cohort and 33.68% in validation cohort were recognized at low risk with 99.06% and 97.78% of sensitivity, respectively. At 4.5 points, only 20.86% of participants in training cohort and 23.73% in validation cohort were recognized at high risk, with positive prediction value of 22.85% and 12.35%, respectively.
Conclusions:
Male-ABCD algorithm identified individual's risk for HCC occurrence within short term for their HCC precision surveillance.
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