{"title":"Prediction Model for Risk of Hepatocellular Carcinoma After Hepatitis C Viral Eradication.","authors":"Wei-Fan Hsu, Ching-Chu Lo, Kuo-Chih Tseng, Hsueh-Chou Lai, Chi-Yi Chen, Cheng-Yuan Peng","doi":"10.2147/JHC.S548870","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The predictors of hepatocellular carcinoma (HCC) in patients with chronic hepatitis C (CHC) and a sustained virologic response after direct-acting antiviral therapy are not well known.</p><p><strong>Patients and methods: </strong>Between September 2012 and March 2022, this retrospective study enrolled 4426 consecutive patients from 4 hospitals in Taiwan. The patients were divided into derivation (n = 3178) and validation (n = 1248) groups.</p><p><strong>Results: </strong>In the derivation group, age, diabetes mellitus, platelet, albumin, and alpha-fetoprotein at 12 weeks after antiviral therapy were independent predictors of hepatocellular carcinoma. We incorporated these predictors into a novel risk prediction model called the AAAPD-C score (<b>a</b>ge, <b>a</b>lbumin, <b>a</b>lpha-fetoprotein level, <b>p</b>latelet count, and <b>d</b>iabetes mellitus status), with total risk scores ranging from 0 to 12. The AAAPD-C score had an area under the receiver operating characteristic curve of 0.867 for the validation group at the end of follow-up. The risk score accurately classified patients in both groups into those with low, medium, and high risks. Patients without advanced liver fibrosis with medium-high AAAPD-C risk scores (4-12) had an annual incidence of HCC >4 per 1000 person-years.</p><p><strong>Conclusion: </strong>The AAAPD-C score can predict the risk of HCC in patients with chronic hepatitis C and a sustained virologic response after direct-acting antiviral therapy. The tool is accurate and inexpensive, and clinicians can use it to identify patients with chronic hepatitis C at risk of HCC following viral eradication.</p>","PeriodicalId":15906,"journal":{"name":"Journal of Hepatocellular Carcinoma","volume":"12 ","pages":"2327-2339"},"PeriodicalIF":3.4000,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12533496/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hepatocellular Carcinoma","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/JHC.S548870","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: The predictors of hepatocellular carcinoma (HCC) in patients with chronic hepatitis C (CHC) and a sustained virologic response after direct-acting antiviral therapy are not well known.
Patients and methods: Between September 2012 and March 2022, this retrospective study enrolled 4426 consecutive patients from 4 hospitals in Taiwan. The patients were divided into derivation (n = 3178) and validation (n = 1248) groups.
Results: In the derivation group, age, diabetes mellitus, platelet, albumin, and alpha-fetoprotein at 12 weeks after antiviral therapy were independent predictors of hepatocellular carcinoma. We incorporated these predictors into a novel risk prediction model called the AAAPD-C score (age, albumin, alpha-fetoprotein level, platelet count, and diabetes mellitus status), with total risk scores ranging from 0 to 12. The AAAPD-C score had an area under the receiver operating characteristic curve of 0.867 for the validation group at the end of follow-up. The risk score accurately classified patients in both groups into those with low, medium, and high risks. Patients without advanced liver fibrosis with medium-high AAAPD-C risk scores (4-12) had an annual incidence of HCC >4 per 1000 person-years.
Conclusion: The AAAPD-C score can predict the risk of HCC in patients with chronic hepatitis C and a sustained virologic response after direct-acting antiviral therapy. The tool is accurate and inexpensive, and clinicians can use it to identify patients with chronic hepatitis C at risk of HCC following viral eradication.