METHODS: Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment.
FINDINGS: Our model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network.
INTERPRETATION: Successful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded.
FUNDING: National Institute on Drug Abuse.
METHODS: We conducted a cross-sectional study to assess the correlation between HCV Ag and HCV RNA and to identify the prevalence of active HCV infection among HCV seropositive HD patients from dialysis centres across West Malaysia from July 2019 to May 2020. Pre-dialysis blood was taken and tested for both HCV Ag and HCV RNA tests. HCV Ag was tested with Abbott ARCHITECT HCV Ag test.
RESULTS: We recruited 112 seropositive HD patients from 17 centres with mean age of 54.04 ± 11.62 years, HD vintage of 14.1 ± 9.7 years, and male constitute 59.8% (67) of the study population. HCV Ag correlates well with HCV RNA (Spearman test coefficient 0.833, p 3000 IU/mL, HCV Ag had a higher sensitivity of 95.1% and greater correlation (Spearman test coefficient 0.897, p
METHODS: A cross-sectional study was conducted to assess the correlation between HCV Ag and HCV RNA and the cost implications of different diagnostic algorithms to diagnose active HCV infection using Anti-HCV, HCV Ag, and HCV RNA. Pre-dialysis blood was tested for both HCV Ag and HCV RNA. HCV Ag was tested with Abbott ARCHITECT HCV Ag test.
RESULTS: Two-hundred twenty-seven haemodialysis patients were recruited from 20 centres with mean age of 57.68 ± 12.48 years, and male constitutes 56.8% (129) of the study population. HCV Ag correlated well with HCV RNA (Spearman test coefficient 0.943, p
METHODS: In this single-arm, open-label, phase 3 trial, we recruited patients from 38 sites across China, Thailand, Vietnam, Singapore, and Malaysia, who were chronically infected with HCV genotypes 1-6, and were HCV treatment-naive or treatment-experienced, either without cirrhosis or with compensated cirrhosis. Patients self-administered a combined sofosbuvir (400 mg) and velpatasvir (100 mg) tablet once daily for 12 weeks. The primary efficacy endpoint was sustained virological response, defined as HCV RNA less than 15 IU/mL at 12 weeks after completion of treatment (SVR12), assessed in all patients who received at least one dose of study drug. The primary safety endpoint was the proportion of adverse events leading to premature discontinuation of study drug. This trial is registered with ClinicalTrials.gov, number NCT02671500, and is completed.
FINDINGS: Between April 14, 2016, and June 30, 2017, 375 patients were enrolled in the study, of whom 374 completed the full treatment course and one discontinued treatment. Overall, 362 (97% [95% CI 94-98]) of 375 patients achieved SVR12. Among 42 patients with HCV genotype 3b, all of whom had baseline resistance-associated substitutions in NS5A, 25 (89% [95% CI 72-98]) of 28 patients without cirrhosis and seven (50% [23-77]) of 14 patients with cirrhosis achieved SVR12. The most common adverse events were upper respiratory tract infection (36 [10%] patients) and headache (18 [5%] patients). There were no discontinuations due to adverse events. Serious adverse events were reported in three (1%) patients, none of which was judged to be related to sofosbuvir-velpatasvir treatment.
INTERPRETATION: Consistent with data from other phase 3 studies, single-tablet sofosbuvir-velpatasvir for 12 weeks is an efficacious and safe treatment for Asian patients with chronic HCV infection, but might have lower efficacy in those infected with HCV genotype 3b and with cirrhosis.
FUNDING: Gilead Sciences.
METHODS: Cytokines were measured using a commercial Bio-plex Pro Human Cytokine Grp I Panel 17-plex kit (BioRad, Hercules, CA, USA). Inflammation was assessed by measuring an array of plasma cytokines, and phenotypic alterations in CD4+ T cells including circulating Tfh cells, CD8+ T cells, and TCR iVα7.2+ MAIT cells in chronic HBV, HCV, and HIV-infected patients and healthy controls. The cells were characterized based on markers pertaining to immune activation (CD69, ICOS, and CD27) proliferation (Ki67), cytokine production (TNF-α, IFN-γ) and exhaustion (PD-1). The cytokine levels and T cell phenotypes together with cell markers were correlated with surrogate markers of disease progression.
RESULTS: The activation marker CD69 was significantly increased in CD4+hi T cells, while CD8+ MAIT cells producing IFN-γ were significantly increased in chronic HBV, HCV and HIV infections. Six cell phenotypes, viz., TNF-α+CD4+lo T cells, CD69+CD8+ T cells, CD69+CD4+ MAIT cells, PD-1+CD4+hi T cells, PD-1+CD8+ T cells, and Ki67+CD4+ MAIT cells, were independently associated with decelerating the plasma viral load (PVL). TNF-α levels showed a positive correlation with increase in cytokine levels and decrease in PVL.
CONCLUSION: Chronic viral infection negatively impacts the quality of peripheral MAIT cells and Tfh cells via differential expression of both activating and inhibitory receptors.
METHODS: Retrospective data pertaining to 713 patients from January 2009 to December 2013 were retrieved from hospital and disease notification records for analysis. The risk factors for hepatitis C virus (HCV) infection were grouped into IVDU and non-IVDU risk factors for analysis using multiple logistic regression.
RESULTS: Of the hepatitis C patients included in this study, the most common age group was 31 to 40 years (30.2%), and male patients (91.2%) made up the overwhelming majority. Ethnic Malays constituted approximately 80.4% of the patients, and IVDU was the main risk factor (77.8%) for HCV infection. Multiple logistic regression showed that male patients were 59 times more likely to have IVDU as a risk factor for HCV infection. Single patients were 2.5 times more likely to have IVDU as a risk factor. Patients aged ≥71 years were much less likely than patients aged ≤30 years to have IVDU as a risk factor for HCV infection.
CONCLUSIONS: IVDU was found to be an important risk factor for HCV infection among patients in the KS district. The factors associated with IVDU included age, sex, and marital status. Appropriate preventive measures should be developed to target the groups in which IVDU is most likely to be a risk factor for HCV infection.
METHODS: A retrospective review of consecutive HCV patients treated with PegIFN/RBV in 2004 to 2012.
RESULTS: A total of 273 patients received treatment. The mean age was 44.16 ± 10.5 years and 76% were male. The top 2 self-reported risks were blood or blood product transfusion before 1994 and injection drug use, found in 57.1% of patients. The predominant HCV genotype (GT) was 3 at 60.6%, second was GT1 at 36.1% and other GTs were uncommon at about 1% or less. About half of our patients have high baseline viral load (>800,000 iu/ml), 18.3% had liver cirrhosis and 22.3% had HIV co-infection. Co-morbid illness was found in 42.9%, hypertension and type 2 diabetes were the two most common. The overall sustained virological response (SVR) by intention-to-treat analysis were 54.9% (n=150/273), 41.2% (40/97) for GT1, 100% (5/5) for GT2 and 62% (101/163) for GT3. Subgroup analysis for HCV monoinfected, treatment naïve showed SVR of 49.2% (31/63) for GT1, 100% (5/5) for GT2 and 67% (69/103) for GT3. In HCV mono-infected and treatment experienced (n=29), the SVR was 28.6% (4/14) for GT1, 21.4% (69/103) for GT3. In the HIV/HCV co-infected, treatment naïve (n=56), the SVR was 28.6% (4/14) for GT1 and 64.3% (27/42) for GT3. Treatment naïve GT3 mono-infected patients had a statistically significant higher SVR compared to treatment experienced patients (P=0.001). In GT3 patients who achieved rapid virological response, the SVR was significantly higher at 85.2% (P< 0.001). The SVR for cirrhotics were low especially for GT1 at 21% (4/19) and 31% (4/13) based on all patients and treatment naïve HCV monoinfected respectively. In GT3 cirrhotics the corresponding SVR were 57.1% (16/28) and 60.9% (14/23). Premature discontinuation rate was 21.2% with the majority due to intolerable adverse events at 12.1%.
CONCLUSIONS: In our routine clinical practice, the HCV patients we treated were young, predominantly of GT3 and many had difficult-to-treat clinical characteristics. The SVR of our patients were below those reported in Asian clinical trials but in keeping with some "real world" data.