Advances in treatment and prevention of hepatitis B

Machine Learning-Based Model Used for Predicting the Risk of Hepatocellular Carcinoma in Patients with Chronic Hepatitis B

Object

Currently, predictive models that effectively stratify the risk levels for hepatocellular carcinoma (HCC) are insufficient. Our study aimed to assess the 10-year cumulative risk of HCC among patients suffering from chronic hepatitis B (CHB) by employing an artificial neural network (ANN).

Methods

This research involved 1717 patients admitted to Beijing Ditan Hospital of Capital Medical University and the People's Liberation Army Fifth Medical Center. The training group included 1309 individuals from Beijing Ditan Hospital of Capital Medical University, whereas the validation group contained 408 individuals from the People's Liberation Army Fifth Medical Center. By performing a univariate analysis, we pinpointed factors that had an independent impact on the development of HCC, which were subsequently employed to create the ANN model. To evaluate the ANN model, we analyzed its predictive accuracy, discriminative performance, and clinical net benefit through measures including the area under the receiver operating characteristic curve (AUC), concordance index (C-index), and calibration curves.

Results

The cumulative incidence rates of HCC over a decade were observed to be 3.59% in the training cohort and 4.41% in the validation cohort. We incorporated nine distinct independent risk factors into the ANN model's development. Notably, in the training group, the area under the receiver operating characteristic (AUROC) curve for the ANN model was reported as 0.929 (95% CI 0.910-0.948), and the C-index was 0.917 (95% CI 0.907-0.927). These results were significantly superior to those of the mREACHE-B(0.700, 95% CI 0.639-0.761), mPAGE-B(0.800, 95% CI 0.757-0.844), HCC-RESCUE(0.787, 95% CI 0.732-0.837), CAMD(0.760, 95% CI 0.708-0.812), REAL-B(0.767, 95% CI 0.719-0.816), and PAGE-B(0.760, 95% CI 0.712-0.808) models (p < 0.001). The ANN model proficiently categorized patients into low-risk and high-risk groups based on their 10-year projections. In the training cohort, the positive predictive value (PPV) for the incidence of liver cancer in low-risk individuals was 92.5% (95% CI 0.921-0.939), whereas the negative predictive value (NPV) stood at 88.2% (95% CI 0.870-0.894). Among high-risk patients, the PPV reached 94.6% (95% CI 0.936-0.956) and the NPV was 90.2% (95% CI 0.897-0.917). These results were also confirmed in the independent validation cohort.

Conclusion

The model utilizing artificial neural networks demonstrates strong performance in personalized predictions and could assist in assessing the likelihood of a 10-year risk of HCC in patients suffering from CHB.

Metformin in Antiviral Therapy: Evidence and Perspectives

Metformin, a widely used antidiabetic medication, has emerged as a promising broad-spectrum antiviral agent due to its ability to modulate cellular pathways essential for viral replication. By activating AMPK, metformin depletes cellular energy reserves that viruses rely on, effectively limiting the replication of pathogens such as influenza, HIV, SARS-CoV-2, HBV, and HCV. Its role in inhibiting the mTOR pathway, crucial for viral protein synthesis and reactivation, is particularly significant in managing infections caused by HIV, CMV, and EBV. Furthermore, metformin reduces oxidative stress and reactive oxygen species (ROS), which are critical for replicating arboviruses such as Zika and dengue. The drug also regulates immune responses, cellular differentiation, and inflammation, disrupting the life cycle of HPV and potentially other viruses. These diverse mechanisms suppress viral replication, enhance immune system functionality, and contribute to better clinical outcomes. This multifaceted approach highlights metformin's potential as an adjunctive therapy in treating a wide range of viral infections.

The wide spectrum of cryoglobulinemic vasculitis and an overview of therapeutic advancements

Immunoglobulins that reversibly precipitate at temperatures below 37 °C are called cryoglobulins (CGs). Cryoglobulinemia often manifests as cryoglobulinemic vasculitis (CV), whose symptoms range in severity from purpuric eruptions to life-threatening features. The majority of CV patients are infected with hepatitis C virus (HCV), whereas lymphoproliferative disorders or connective tissue diseases (CTD) are commonly diagnosed among patients with CV of non-infectious origin. In the absence of detectable associated disease, cryoglobulinemia is classified as "essential" (EMC). All HCV-positive CV patients should be given direct-acting antiviral agents (DAAs) that are consistently able to induce a sustained virologic response (SVR). Glucocorticoids (GCs) can mitigate CV-associated vasculitis, but they have no role as maintenance therapy. Cyclophosphamide restrains the hyperactive phase(s) of the disease and the post-apheresis rebound of newly synthesized CGs. Its use has been largely replaced by rituximab (RTX) in patients unresponsive to DAAs, patients progressing to B-cell non-Hodgkin lymphoma (B-NHL) and patients in whom CV persists or reappears after clearance of HCV. Therapeutic apheresis is an emergency treatment for CV patients with hyperviscosity syndrome. HCV-positive CV patients are at an increased risk of developing NHL, but the achievement of SVR can effectively prevent HCV-related NHL or induce the remission of an already established lymphoma, even without chemotherapy. The treatment of patients with IgM or IgG monoclonal cryoglobulins and an underlying immunoproliferative disorder is based on the regimens adopted for patients with the same B-cell malignancies but without circulating CGs. For patients with CTD, GCs plus alkylating agents or RTX are similarly effective as first-line therapy and in the relapse/refractory setting. In patients with EMC, treatment should consist of GCs plus RTX, with the dose of GCs tapered as soon as possible to reduce the risk of infectious complications.

Effects of antiviral therapy and drug withdrawal on postpartum hepatitis in pregnant women with chronic HBV infection

OBJECTIVE

To investigate the effect of antiviral therapy and drug withdrawal on the incidence of hepatitis B after delivery in pregnant women with chronic hepatitis B virus (CHB) infection who received tenofovir disoproxil fumarate (TDF) treatment.

METHODS

Eligible CHB pregnant women were enrolled, and received TDF at 32 weeks gestation. The drug was stopped immediately or at 6 weeks after delivery. The HBV biomarkers and clinical biochemical parameters were monitored during gestation and 24 weeks after delivery.

RESULTS

There were 264 women completed the observation, including 96 untreated subjects in control group. Among 168 treated subjects, 131 cases stopped drug immediately after delivery and 37 cases delayed the drug withdrawal at 6 weeks after delivery. The incidence of postpartum hepatitis in control, immediate drug withdrawal, and delayed drug withdrawal were 28.1% (27/96), 23.7% (31/131), and 24.3% (9/37), showing no significant difference (χ² = 0.607, p = 0.738). No factor was found to be associated with the occurrence of postpartum hepatitis. It's noteworthy that 96.3% of postpartum hepatitis in control group and 92.3% of postpartum hepatitis in immediate drug withdrawal group occurred within 12 weeks after delivery. While in delayed drug withdrawal group, the rate of postpartum hepatitis occurred within 12 weeks after delivery was 77.7%.

CONCLUSION

Withdrawing antiviral drug immediately or at 6 weeks after delivery did not affect the incidence of postpartum hepatitis in CHB women, but delaying drug withdrawal might delay the onset of postpartum hepatitis.

CLINICAL TRIAL REGISTRATION NUMBER

NCT03214302.