Impact of nonalcoholic fatty liver disease status change on antiviral efficacy of nucleos(t)ide analogues in HBeAg-positive chronic hepatitis B

Effectiveness and safety of tenofovir amibufenamide in chronic hepatitis B patients

This letter to the editor relates to the study entitled "Tenofovir amibufenamide vs tenofovir alafenamide for treating chronic hepatitis B: A real-world study", which was recently published by Peng et al. Hepatitis B virus infection represents a significant health burden worldwide and can lead to cirrhosis and even liver cancer. The antiviral drugs currently used to treat patients with chronic hepatitis B infection still have many side effects, so it is crucial to identify safe and effective drugs to inhibit viral replication.

Antiviral therapy response in patients with chronic hepatitis B and fatty liver: A systematic review and meta-analysis

The impact of concurrent fatty liver (FL) on response to antiviral therapy in chronic hepatitis B (CHB) patients has not been well characterized. We aimed to systematically review and analyse antiviral treatment response in CHB patients with and without FL. We searched PubMed, Embase, Web of Science and the Cochrane Library databases from inception to 31 May 2023 for relevant studies. Biochemical response (BR), complete viral suppression (CVS) and hepatitis B e antigen (HBeAg) seroconversion in CHB patients with FL (CHB-FL) and without FL (non-FL CHB) were compared. In an initial pool of 2101 citations, a total of 10 studies involving 2108 patients were included. After 12 weeks of treatment, CHB-FL patients as compared with non-FL CHB patients had lower BR rate (48.37% [108/227] vs. 72.98% [126/174], p = .04) but similar trend for CVS (36.86% [80/227] vs. 68.81% [114/174], p = .05) and similar rates of HBeAg seroconversion (6.59% [7/103] vs. 7.40% [7/110], p = .89). However, at week 48, there were no statistically significant differences between CHB-FL and non-FL CHB patients in any of the outcomes, including BR (60.03% [213/471] vs. 69.37% [314/717], p = .67), CVS (65.63% [459/746] vs. 73.81% [743/1132], p = .27) and HBeAg seroconversion (10.01% [30/275] vs. 14.06% [65/453], p = .58) with similar findings for week 96. BR rate was lower in CHB-FL patients after 12 weeks of antiviral treatment. However, after a longer follow-up of either 48 or 96 weeks, no statistically significant differences were observed in BR, CVS or HBeAg seroconversion rates between CHB patients with and without FL.

Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis: a cohort study

Background

With increasingly prevalent coexistence of chronic hepatitis B (CHB) and hepatic steatosis (HS), simple, non-invasive diagnostic methods to accurately assess the severity of hepatic inflammation are needed. We aimed to build a machine learning (ML) based model to detect hepatic inflammation in patients with CHB and concurrent HS.

Methods

We conducted a multicenter, retrospective cohort study in China. Treatment-naive CHB patients with biopsy-proven HS between April 2004 and September 2022 were included. The optimal features for model development were selected by SHapley Additive explanations, and an ML algorithm with the best accuracy to diagnose moderate to severe hepatic inflammation (Scheuer's system ≥ G3) was determined and assessed by decision curve analysis (DCA) and calibration curve. This study is registered with ClinicalTrials.gov (NCT05766449).

Findings

From a pool of 1,787 treatment-naive patients with CHB and HS across eleven hospitals, 689 patients from nine of these hospitals were chosen for the development of the diagnostic model. The remaining two hospitals contributed to two independent external validation cohorts, comprising 509 patients in validation cohort 1 and 589 in validation cohort 2. Eleven features regarding inflammation, hepatic and metabolic functions were identified. The gradient boosting classifier (GBC) model showed the best performance in predicting moderate to severe hepatic inflammation, with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.83-0.88) in the training cohort, and 0.89 (95% CI 0.86-0.92), 0.76 (95% CI 0.73-0.80) in the first and second external validation cohorts, respectively. A publicly accessible web tool was generated for the model.

Interpretation

Using simple parameters, the GBC model predicted hepatic inflammation in CHB patients with concurrent HS. It holds promise for guiding clinical management and improving patient outcomes.

Funding

This research was supported by the National Natural Science Foundation of China (No. 82170609, 81970545), Natural Science Foundation of Shandong Province (Major Project) (No. ZR2020KH006), Natural Science Foundation of Jiangsu Province (No.BK20231118), Tianjin Key Medical Discipline (Specialty), Construction Project, TJYXZDXK-059B, Tianjin Health Science and Technology Project key discipline special, TJWJ2022XK034, and Research project of Chinese traditional medicine and Chinese traditional medicine combined with Western medicine of Tianjin municipal health and Family Planning Commission (2021022).