Low anti-HBc levels are associated with lower risk of virological relapse after nucleos(t)ide analogue cessation in HBe antigen-negative patients.

BACKGROUND AND AIMS: Low anti-HBc serum levels at the time of therapy cessation were linked to a higher relapse risk in predominantly HBeAg-positive cohorts. We investigated the association of anti-HBc levels with relapse in HBeAg-negative patients. METHODS: Serum levels of anti-HBc, HBsAg and HBcrAg were determined in 136 HBeAg-negative patients, participating in a vaccination trial (ABX-203, NCT02249988), before treatment cessation or vaccination. Importantly, vaccination showed no impact on relapse. The correlation between the biomarkers and their predictive value for relapse (HBV DNA >2000 IU/ml ± ALT >2xULN) was investigated. RESULTS: After therapy cessation 50% (N = 68) of patients relapsed. Median anti-HBc prior to treatment stop was significantly higher among relapsers compared to off-treatment responders (520 IU/ml vs. 330 IU/mL, p = .0098). The optimal anti-HBc cut-off to predict relapse was 325 IU/ml according to the Youden-Index. About 35% of patients with anti-HBc level < 325 IU/ml versus 60% of those with values ≥325 IU/mL relapsed (p = .0103; sensitivity 50%, specificity 75%). Combining the optimal cut-offs of HBsAg (>3008 IU/mL) or HBcrAg (≥1790 U/ml) with anti-HBc increased the proportion of patients with relapse to 80% (p < .0001) and 74% (p = .0006), respectively. CONCLUSION: In contrast to predominantly HBeAg-positive cohorts, in our cohort of HBeAg-negative patients lower anti-HBc levels are associated with a significantly lower relapse risk after nucleos(t)ide analogue cessation. The vast majority of included patients were either genotype B or C and the applicability to other genotypes has to be further evaluated. However, anti-HBc level as an indicator of the host response might be prospectively further explored for prediction models.

Impact of the COVID-19 pandemic on patients with liver cirrhosis-the experience of a tertiary center in Germany.

BACKGROUND: The COVID-19 pandemic has caused a significant impact on the medical care of many diseases and has led to reduced presentations to the emergency department. Reduced presentations may be due to overwhelmed capacities of hospitals or collateral damage from fear of infection, lockdown regulations, or other reasons. The effect on patients with liver cirrhosis is not established. OBJECTIVE: We aim to assess the impact on the care of patients with liver cirrhosis in a tertiary center in Northern Germany. METHODS: All patients presenting to the emergency department with a diagnosis of cirrhosis between March 1 and May 31 from 2015-2020 were included. Reasons for presentation, duration of symptoms, the severity of liver disease, and 30-day mortality were assessed and compared between patients presenting during the COVID-19 pandemic and pre-COVID-19. RESULTS: Overall, 235 patients were included. Despite an overall decline in presentations to the emergency department by 11.7%, the frequency of patients presenting with liver cirrhosis has remained stable (non-significant increase by 19.5%). No significant difference could be detected for the MELD score, the CLIF-organ failure subscores, and the 30-day mortality before and during the COVID-19 pandemic. Up to 75% of patients with liver cirrhosis had symptoms >24 h before presenting to the emergency department. CONCLUSION: Despite the overall trend of reduced emergency presentations during the COVID-19 pandemic, the frequency of presentations of patients with liver cirrhosis did not decline. Morbidity and mortality were not affected in a setting of disposable healthcare resources. The late presentation to the emergency department in many cirrhotic patients may open opportunities for interventions (i.e., with early telemedicine intervention).

Pilot Study Using Machine Learning to Identify Immune Profiles for the Prediction of Early Virological Relapse After Stopping Nucleos(t)ide Analogues in HBeAg-Negative CHB.

Treatment with nucleos(t)ide analogues (NAs) may be stopped after 1-3 years of hepatitis B virus DNA suppression in hepatitis B e antigen (HBeAg)-negative patients according to Asian Pacific Association for the Study of Liver and European Association for the Study of Liver guidelines. However, virological relapse (VR) occurs in most patients. We aimed to analyze soluble immune markers (SIMs) and use machine learning to identify SIM combinations as predictor for early VR after NA discontinuation. A validation cohort was used to verify the predictive power of the SIM combination. In a post hoc analysis of a prospective, multicenter therapeutic vaccination trial (ABX-203, NCT02249988), hepatitis B surface antigen, hepatitis B core antigen, and 47 SIMs were repeatedly determined before NA was stopped. Forty-three HBeAg-negative patients were included. To detect the highest predictive constellation of host and viral markers, a supervised machine learning approach was used. Data were validated in a different cohort of 49 patients treated with entecavir. VR (hepatitis B virus DNA ≥ 2,000 IU/mL) occurred in 27 patients. The predictive value for VR of single SIMs at the time of NA stop was best for interleukin (IL)-2, IL-17, and regulated on activation, normal T cell expressed and secreted (RANTES/CCL5) with a maximum area under the curve of 0.65. Hepatitis B core antigen had a higher predictive power than hepatitis B surface antigen but lower than the SIMs. A supervised machine-learning algorithm allowed a remarkable improvement of early relapse prediction in patients treated with entecavir. The combination of IL-2, monokine induced by interferon γ (MIG)/chemokine (C-C motif) ligand 9 (CCL9), RANTES/CCL5, stem cell factor (SCF), and TNF-related apoptosis-inducing ligand (TRAIL) was reliable in predicting VR (0.89; 95% confidence interval: 0.5-1.0) and showed viable results in the validation cohort (0.63; 0.1-0.99). Host immune markers such as SIMs appear to be underestimated in guiding treatment cessation in HBeAg-negative patients. Machine learning can help find predictive SIM patterns that allow a precise identification of patients particularly suitable for NA cessation.

Frequency of Potential Drug-Drug Interactions in the Changing Field of HCV Therapy.

BACKGROUND: With the introduction of direct-acting antivirals (DAAs) for hepatitis C virus (HCV) infection, drug-drug interactions (DDIs) emerged as significant challenge. Since then, HCV therapy and the infected population have rapidly changed. So far, very limited data are available regarding the clinical relevance of DDIs when using most modern DAA regimens. We aimed to assess how the importance of DDIs has evolved over time. METHODS: From January 2014 to July 2018, 668 consecutive HCV patients were evaluated for their outpatient medication and assessed for DDIs with DAAs. Different time periods were defined based on market approval of key DAAs: A (01/2014-11/2014), B (11/2014-08/2016), and C (08/2016-07/2018). RESULTS: The frequency of patients with real-world DDIs was highest in period B (A: 37.1%, B: 49.6%, C: 38.8%). The recently approved DAAs (period C) theoretically showed a lower DDI risk profile. However, real-world DDIs were still comparable to period A, as HCV patients' characteristics changed (eg, age ≥75 years: A: 3.1%, B: 9.8%, C: 5.6%; polypharmacy/patients with ≥8 drugs: A: 11.1%, B: 15.2%, C: 17.2%). Furthermore, although DDIs via CYP 3A4 became less important for some modern regimens, other mechanisms like an altered pH value in the stomach, causing reduced bioavailability, evolved. Relevant DDIs most frequently occurred with proton pump inhibitors, metamizole, statins, and carvedilol. CONCLUSIONS: DDIs during antiviral treatment still affect about 40% of HCV patients. The lower DDI potential of modern DAA regimens is partly counteracted by changing patient characteristics. Therefore, DDIs should not be underestimated.