Quantitative HBeAg is a strong predictor of HBeAg loss among patients receiving pegylated interferon.

BACKGROUND: HBeAg loss is an important endpoint for antiviral therapy in chronic hepatitis B (CHB), however there are no reliable biomarkers to identify patients who will respond to the addition of pegylated interferon to nucleos(t)ide analogue (NA) therapy. AIM: To evaluate the use of serum biomarkers to predict HBeAg loss. METHODS: HBeAg positive CHB participants on NAs who switched-to or added-on 48 weeks pegylated interferon alpha2b (clinicaltrial.gov NCT01928511) were evaluated at week 72 for HBeAg loss. The predictive ability of qHBeAg, qHBsAg, HBV RNA and clinical variables for HBeAg loss were investigated. RESULTS: HBeAg loss occurred in 15/55 (27.3%) participants who completed 48 weeks of pegylated interferon. There was a lower baseline qHBeAg (1.18 IU/mL [2.27] versus 10.04 IU/mL [24.87], P = 0.007) among participants who lost HBeAg. Baseline qHBeAg (OR = 0.15, 95% CI 0.03-0.66, P = 0.01) and detectable HBV DNA at baseline (OR = 25.00, 95% CI 1.67-374.70, P = 0.02) were independent predictors of HBeAg loss. In addition, on-treatment qHBeAg was also a strong predictor of HBeAg loss (OR = 0.39, 95% CI 0.18-0.81, P = 0.012). The models combining detectable baseline HBV DNA with baseline (C-statistic 0.82) and on-treatment (C-statistic 0.83) had good accuracy for predicting HBeAg loss. A rise in qHBeAg ≥ 10 IU/ml was a predictor of flare (ALT ≥ 120 U/ml) on univariable analysis but not after adjustment for treatment arm. CONCLUSIONS: Baseline and on-treatment qHBeAg is a useful biomarker that can identify participants on NA therapy who may benefit from adding or switching to pegylated interferon.

Switching to or Add-on Peginterferon in Patients on Nucleos(t)ide Analogues for Chronic Hepatitis B: The SWAP RCT.

BACKGROUND & AIMS: The optimal therapeutic strategy in nucleoside analogue (NA) experienced chronic hepatitis B (CHB) using peginterferon is still unclear; hence we explored a switch to or add-on peginterferon strategy versus continued NA. METHODS: We conducted a randomized controlled trial of CHB patients on NA >12 months with HBV DNA(-) randomized to switch or add-on peginterferon-alpha2b (1.5 µg/kg/weekly) for 48 weeks versus continuing NA (controls) (allocation 2:2:1; Clinicaltrial.gov: NCT01928511) in tertiary Singapore hospitals. The primary composite endpoint at week 72 was hepatitis B e antigen (HBeAg) loss or quantitative HBsAg (qHBsAg) >1 log IU/mL reduction, and secondary endpoints were HBsAg loss, HBsAg seroconversion, qHBsAg <200 IU/mL, qHBsAg <100 IU/mL, HBV DNA(-), viral relapse, and safety. Analysis was by intention-to-treat (ITT). RESULTS: A total of 253 patients (controls 51, switch 103, add-on 99) were randomized. The primary ITT endpoint was achieved in 3.9% of controls, 33.3% of switch, and 26.7% of add-on (P < .0001, switch/add-on versus controls). HBsAg loss occurred in 0% of controls, 7.8% of switch, and 10.1% of add-on (ITT, P < .001, switch/add-on versus controls). HBeAg(+) patients on peginterferon had higher HBeAg loss than controls but poor HBsAg responses, whereas HBeAg(-) patients on peginterferon achieved better HBsAg responses than controls. Reduction in qHBsAg in HBeAg(+) was 0.14 log IU/mL versus 0.51 log IU/mL in HBeAg(-) (P < .0001) in peginterferon-treated patients. Clinical relapse was higher in switch (13.6% overall, 27% in HBeAg(+)) versus 1% add-on and 0% controls. Adverse events were typically interferon-related symptoms, with one death (myocardial infarction unrelated to therapy). CONCLUSIONS: ITT analysis showed that either peginterferon strategies were superior to NA for the primary endpoint and HBsAg loss, but add-on peginterferon is preferred to switch due to improved safety and similar efficacy. ClincialTrials.gov number: NCT01928511.

Comparative biomarkers for HBsAg loss with antiviral therapy shows dominant influence of quantitative HBsAg (qHBsAg).

BACKGROUND: Biomarkers such as quantitative HBsAg (qHBsAg), quantitative hepatitis B virus (HBV) core-related antigen (qHBcrAg) and HBV RNA may be useful in predicting HBsAg loss in patients with chronic hepatitis B (CHB) undergoing antiviral therapy. AIM(S): Our study evaluated qHBsAg, HBV RNA and qHBcrAg as a posthoc analysis of a randomized clinical trial of peginterferon±NA to determine their utility in predicting HBsAg loss. METHODS: CHB patients who completed therapy with 48weeks peginterferon alpha2b ± nucleoside analogue therapy (clinicaltrial.gov NCT01928511) were evaluated at week 72 for HBsAg loss. The predictive ability of qHBsAg, qHBcrAg, HBV RNA and other variables were investigated by univariate and multivariate logistic models for HBeAg-negative patients by odds ratios, area under the curve (AUC), sensitivity, specificity, and positive and negative likelihood ratios (LR). RESULTS: HBsAg loss occurred in 15/114(13%) HBeAg-negative CHB patients who completed 48 weeks of peginterferon. At baseline, qHBsAg was superior to HBcrAg and HBV RNA with AUC 0.916, 0.649 and 0.542, respectively. Using multivariate analysis, the model comprising treatmentarm, age, gender, baseline qHBsAg, HBcrAg and HBV RNA, weeks 4 & 8 qHBsAg had the highest AUC(0.98), but the univariate model with week 8 qHBsAg <70 IU/mL had AUC 0.96. Hence, the contributions of variables other than qHBsAg were marginal. HBV RNA and qHBcrAg were weak predictors of HBsAg loss. Kinetics of the novel markers showed only qHBsAg had a good relationship with HBsAg loss while HBV RNA had a marginal relationship and HBcrAg did not change at all, and none had a good relationship with viral rebound. CONCLUSIONS: On-treatment biomarker predictors were better than baseline ones, and the best predictor of HBsAg loss at 72 weeks was week 8 qHBsAg <70 IU/mL.

Validation of genetic variants associated with metabolic dysfunction-associated fatty liver disease in an ethnic Chinese population.

BACKGROUND: Genetic factors play an important role in the pathogenesis and development of metabolic dysfunction-associated fatty liver disease (MAFLD). AIM: To study the association of single nucleotide polymorphisms (SNPs), previously identified in Western populations, with the risk of MAFLD in a Singapore Chinese population and their interactions with environmental and medical risk factors. METHODS: A retrospective case-control study was conducted with 72 MAFLD cases and 72 controls with no hepatic steatosis on computed tomography, magnetic resonance imaging, or controlled attenuation parameter score. Subjects were recruited from two tertiary hospitals. Genetic alleles such as NCAN, GCKR, LYPLAL1, PNPLA3, PPP1R3B, FDFT1, COL13A1, EFCAB4B, PZP, and TM6SF2 were genotyped using the TaqMan® Predesigned SNP Genotyping Assay. RESULTS: Weight and body mass index (BMI) were 1.2-times higher in patients (70.6 kg, 95% confidence interval [CI]: 57.1-84.1 vs 60.8 kg, 95%CI: 48.5-73.1, P < 0.001 and 26.9 kg, 95%CI: 23-40.8 vs 23.3 kg 95%CI: 19-27.6, P < 0.001 respectively). The prevalence of diabetes mellitus in patients was 40.3% and 20.8% in controls (P = 0.011). Patients had higher mean triglycerides than controls (P < 0.001). PNPLA3 GG was more likely to be associated with MAFLD (43.4% CC vs 69.7% GG, P = 0.017, and 44.8% CG vs 69.7% GG, P = 0.022). In multivariable analysis, hypertriglyceridemia (odds ratio [OR]: 2.04 95%CI: 1.3-3.1, P = 0.001), BMI (OR: 1.2 95%CI: 1.1-1.4, P < 0.001) and PNPLA3 GG (OR: 3.4 95%CI: 1.3-9.2, P = 0.014) were associated with MAFLD (area under the receiver operating characteristic curve of 0.823). CONCLUSION: Among the Chinese population of Singapore, PNPLA3 homozygous GG allele is a strong predictor of MAFLD, whereas LYPLAL1, GCKR, FDFT1, COL13A1, PZP, and TM6SF2 are not significantly associated. Hypertriglyceridemia, high BMI, and PNPLA3 GG are independent predictors of MAFLD.

Findings from a large Asian chronic hepatitis C real-life study.

There is a paucity of information on chronic hepatitis C (CHC) patients treated with direct antiviral agents (DAAs) in Asia. We invited Asia-Pacific physicians to collate databases of patients enrolled for CHC treatment, recording baseline clinical, virologic and biochemical characteristics, sustained virologic response at week 12 (SVR12) and virologic failure. SVR12 outcome was based on intention to treat (ITT). Multivariate analysis was used to assess independent risk factors for SVR12 using SPSS version 20. A total of 2171 patients from India (n = 977), Myanmar (n = 552), Pakistan (n = 406), Thailand (n = 139), Singapore (n = 72) and Malaysia (n = 25) were collected. At baseline, mean age was 49 years, 50.2% were males, and 41.8% had cirrhosis. Overall, SVR12 was 89.5% and by genotype (GT) based on ITT and treatment completion, respectively, was 91% and 92% for GT1, 100% and 100% for GT2, 91% and 97% for GT3, 64% and 95% for GT4, 87% and 87% for GT6 and 79% and 91% for GT untested. Patients with cirrhosis had SVR12 of 85% vs 93% for noncirrhosis (P < 0.001) (RR 2.1, 95% CI 1.4-3.1, P = 0.0002). Patients with GT1 and GT3 treated with sofosbuvir/ribavirin (SR) had 88% and 89% SVR12, respectively, but those GT6 treated with sofosbuvir/ledipasvir (SL) had only 77.6% SVR12. Multivariate analysis showed absence of cirrhosis was associated with higher SVR12 (OR 2.0, 95% CI 1.3-3.1, P = 0.002). In conclusion, patients with GT1 and GT3 with/without cirrhosis had surprisingly high efficacy using SR, suggesting that Asians may respond better to some DAAs. However, poor GT6 response to SL suggests this regimen is suboptimal for this genotype.

Alpha-interferon treatment in hepatitis B.

Pegylated interferon-α (PEG-IFN-α) is a first line option in the treatment of chronic hepatitis B. Compared with nucleos(t)ide analogues (NAs), therapy with PEG-IFN-α has the advantages of finite treatment duration and higher rates of hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) seroconversion, but the disadvantage of greater adverse effects. Choosing PEG-IFN-α requires careful evaluation of the likelihood of achieving a sustained off-treatment response. Sustained off-treatment response with PEG-IFN-α can be predicted by baseline factors in HBeAg positive disease. These include genotype A or B, low viral load, high alanine aminotransferase (ALT), older age and female gender. On the other hand, no pre-treatment factors have been identified that can reliably predict response in HBeAg negative disease. Using on-treatment quantitative HBsAg levels, failure of a long term response can be identified with high negative predictive value (NPV). However, no combination of on treatment parameters have been identified so far that can precisely forecast successful treatment. Up until recently, there was little evidence supporting the use of combining PEG-IFN with NAs. The addition of PEG-IFN in patients who already have viral suppression with NAs therapy appears superior to continuing NAs alone in achieving a sustained response. Also, tenofovir disoproxil fumarate (TDF) in combination with PEG-IFN has been reported to enable significantly higher HBsAg loss than with either monotherapy alone. This occurred in both HBeAg positive and negative patients across all genotypes. In spite of recent developments, rates of HBsAg loss are still only in the order of 10% and so cure remains elusive. Further research is required to identify the optimal combination or sequential therapy regimen, and the subgroups with the highest rates of response so that they can be targeted.