scholarly journals Low-level viremia and cirrhotic complications in patients with chronic hepatitis B according to adherence to entecavir

2020 ◽  
Vol 26 (3) ◽  
pp. 364-375 ◽  
Author(s):  
Seung Bum Lee ◽  
Joonho Jeong ◽  
Jae Ho Park ◽  
Seok Won Jung ◽  
In Du Jeong ◽  
...  

Background/Aims: Low-level viremia (LLV) after nucleos(t)ide analog treatment was presented as a possible cause of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). However, detailed information on patients’ adherence in the real world was lacking. This study aimed to evaluate the effects of LLV on HCC development, mortality, and cirrhotic complications among patients according to their adherence to entecavir (ETV) treatment.Methods: We performed a retrospective observational analysis of data from 894 consecutive adult patients with treatment-naïve CHB undergoing ETV treatment. LLV was defined according to either persistent or intermittent episodes of <2,000 IU/mL detectable hepatitis B virus DNA during the follow-up period. Good adherence to medication was defined as a cumulative adherence ≥90% per study period.Results: Without considering adherence in the entire cohort (n=894), multivariate analysis of the HCC incidence showed that LLV was an independent prognostic factor in addition to other traditional risk factors in the entire cohort (<i>P</i>=0.031). Good adherence group comprised 617 patients (69.0%). No significant difference was found between maintained virologic response and LLV groups in terms of the incidence of liver-related death or transplantation, HCC, and hepatic decompensation in good adherence group, according to multivariate analyses.Conclusions: In patients with treatment-naïve CHB and good adherence to ETV treatment in the real world, LLV during treatment is not a predictive factor for HCC and cirrhotic complications. It may be unnecessary to adjust their antiviral agent for patients with good adherence who experience LLV during ETV treatment.

2014 ◽  
Vol 146 (5) ◽  
pp. S-963-S-964
Author(s):  
Wai-Kay Seto ◽  
Yuk-Fai Lam ◽  
Sze Hang Kevin Liu ◽  
Lung-Yi Mak ◽  
Kwan-Lung Michael Ko ◽  
...  

2019 ◽  
Vol 221 (3) ◽  
pp. 389-399 ◽  
Author(s):  
Hwai-I Yang ◽  
Ming-Lun Yeh ◽  
Grace L Wong ◽  
Cheng-Yuan Peng ◽  
Chien-Hung Chen ◽  
...  

Abstract Background Patients on oral antiviral (OAV) therapy remain at hepatocellular carcinoma (HCC) risk. Risk prediction tools distinguishing treated patients with residual HCC risk are limited. The aim of this study was to develop an accurate, precise, simple-to-use HCC risk score using routine clinical variables among a treated Asian cohort. Methods Adult Asian chronic hepatitis B (CHB) patients on OAV were recruited from 25 centers in the United States and the Asia-Pacific region. Excluded persons were coinfected with hepatitis C, D, or human immunodeficiency virus, had HCC before or within 1 year of study entry, or their follow-up was &lt;1 year. Patients were randomized to derivation and validation cohorts on a 2:1 ratio. Statistically significant predictors from multivariate modeling formed the Real-world Effectiveness from the Asia Pacific Rim Liver Consortium for HBV (REAL-B) score. Results A total of 8048 patients were randomized to the derivation (n = 5365) or validation group (n = 2683). The REAL-B model included 7 variables (male gender, age, alcohol use, diabetes, baseline cirrhosis, platelet count, and alpha fetoprotein), and scores were categorized as follows: 0–3 low risk, 4–7 moderate risk, and 8–13 high risk. Area under receiver operating characteristics were &gt;0.80 for HCC risk at 3, 5, and 10 years, and these were significantly higher than other risk models (p &lt; .001). Conclusions The REAL-B score provides 3 distinct risk categories for HCC development in Asian CHB patients on OAV guiding HCC surveillance strategy.


2016 ◽  
Vol 43 (7) ◽  
pp. 847-848
Author(s):  
J. Ahn ◽  
M. H. Nguyen ◽  
J. K. Lim ◽  
H. M. Lee ◽  
C. Q. Pan ◽  
...  

2017 ◽  
Vol 130 (18) ◽  
pp. 2190-2197 ◽  
Author(s):  
Yan-Di Xie ◽  
Hui Ma ◽  
Bo Feng ◽  
Lai Wei

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