Clin Mol Hepatol.
2023 Jul;29(3):747-762. 10.3350/cmh.2023.0121.
Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients
- Wu X1
- Xu X2
- Zhou J1
- Sun Y1
- Ding H3
- Xie W4
- Chen G5
- Ma A6
- Piao H7
- Wang B1
- Chen S1
- Meng T1
- Ou X1
- Yang HI8
- Jia J
1 - Kong Y2
- You H1
- Affiliations
-
- 1Liver Research Center, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Diseases, Beijing, Mainland of China
- 2Clinical Epidemiology and EBM Unit, Beijing Friendship Hospital, Capital Medical University, Beijing Clinical Research Institute, Beijing, Mainland of China
- 3Department of Gastroenterology, Beijing Youan Hospital, Capital Medical University, Beijing, Mainland of China
- 4Liver Research Center, Beijing Ditan Hospital, Capital Medical University, Beijing, Mainland of China
- 5Division of Liver Fibrosis, The Fifth Medical Center, General Hospital of the People’s Liberation Army, Beijing, Mainland of China
- 6Division of Infectious Diseases, China-Japan Friendship Hospital, Beijing, Mainland of China
- 7Office of Clinical Trials, Affiliated Hospital of Yanbian University, Jilin, Mainland of China
- 8Genomics Research Center, Academia Sinica, Taipei, Taiwan
- KMID: 2543992
- DOI: http://doi.org/10.3350/cmh.2023.0121
Abstract
- Background/Aims
Existing hepatocellular carcinoma (HCC) prediction models are derived mainly from pretreatment or early on-treatment parameters. We reassessed the dynamic changes in the performance of 17 HCC models in patients with chronic hepatitis B (CHB) during long-term antiviral therapy (AVT).
Methods
Among 987 CHB patients administered long-term entecavir therapy, 660 patients had 8 years of follow-up data. Model scores were calculated using on-treatment values at 2.5, 3, 3.5, 4, 4.5, and 5 years of AVT to predict threeyear HCC occurrence. Model performance was assessed with the area under the receiver operating curve (AUROC). The original model cutoffs to distinguish different levels of HCC risk were evaluated by the log-rank test.
Results
The AUROCs of the 17 HCC models varied from 0.51 to 0.78 when using on-treatment scores from years 2.5 to 5. Models with a cirrhosis variable showed numerically higher AUROCs (pooled at 0.65–0.73 for treated, untreated, or mixed treatment models) than models without (treated or mixed models: 0.61–0.68; untreated models: 0.51–0.59). Stratification into low, intermediate, and high-risk levels using the original cutoff values could no longer reflect the true HCC incidence using scores after 3.5 years of AVT for models without cirrhosis and after 4 years of AVT for models with cirrhosis.
Conclusions
The performance of existing HCC prediction models, especially models without the cirrhosis variable, decreased in CHB patients on long-term AVT. The optimization of existing models or the development of novel models for better HCC prediction during long-term AVT is warranted.
- Full Text Links
-
- Actions
-
Cited
- CITED
-
- Close
- Share
-
- Similar articles
-
- Decreasing performance of HCC prediction models during antiviral therapy for hepatitis B: what else to keep in mind: Editorial on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients”
- Reply to correspondence on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients”
- Correspondence to editorial on “Hepatocellular carcinoma prediction model performance decreases with long-term antiviral therapy in chronic hepatitis B patients”
- Anti-viral Treatment of Chronic Hepatitis B
- Hepatocellular Carcinoma Prediction Models for Patients with Chronic Hepatitis B Virus Infection in the Era of Potent Antiviral Therapy
