Retreatment with sofosbuvir/ledipasvir with or without lead‐in interferon‐β injections in patients infected with genotype 1b hepatitis C virus after unsuccessful daclatasvir/asunaprevir therapy

Uemura, Hayato; Uchida, Yuzo; Kouyama, Jun‐ichi; Naiki, Kayoko; Yamaba, Shinpei; Fuchigami, A; Saito, Yoichi; Shiokawa, Keisuke; Fujii, Yohei; Uchiya, Hiroshi; Nakazawa, Masatoshi; Ando, Satsuki; Nakazato, Masamitsu; Motoya, Daisuke; Sugawara, Kayoko; Inao, Mie; Imai, Yumiko; Nakayama, Nobuaki; Tomiya, Tomoaki; Mochida, Satoshi

doi:10.1111/hepr.12980

Cited by 7 publications

(4 citation statements)

References 28 publications

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“…In patients receiving daclatasvir plus asunaprevir, the therapeutic efficacy was inferior in patients infected with HCV carrying resistance‐associated substitutions in the NS5A regions, especially the NS5A‐Y93H substitution, than in those with the wild‐type HCV strains . The problems regarding HCV strains carrying various resistance‐associated substitutions were mostly resolved after the launch of pangenotype DAAs. SVR was achieved in almost all patients after pangenotype DAA therapy with combination tablets of glecaprevir and pibrentasvir, except in patients infected with genotype 1b HCV strains carrying the NS5A‐P32 deletion and in those infected with genotype 3 HCV strains .…”

Section: Introductionmentioning

confidence: 94%

Involvement of portosystemic shunts in impaired improvement of liver function after direct‐acting antiviral therapies in cirrhotic patients with hepatitis C virus

Tsuji

Uchida

Uemura

et al. 2020

Hepatology Research

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Aim: Factors responsible for impaired improvement of liver function despite sustained viral response after direct-acting antiviral agents therapies in cirrhotic patients with hepatitis C virus need to be elucidated.Methods: Liver function and the extent of portosystemic shunting were evaluated for 79 patients with compensated cirrhosis, in whom sustained viral response had been achieved after direct-acting antiviral agents therapies for hepatitis C virus at least 3 years earlier. Conclusions:A large size of portosystemic shunts was found to be a crucial determinant of impaired improvement of liver function, as well as of the development of portal hypertensionrelated events, even after sustained viral response in patients with compensated cirrhosis.

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Section: Introductionmentioning

confidence: 94%

Involvement of portosystemic shunts in impaired improvement of liver function after direct‐acting antiviral therapies in cirrhotic patients with hepatitis C virus

Tsuji

Uchida

Uemura

et al. 2020

Hepatology Research

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“…Adjustment to the duration and combination of therapy was the most common optimisation strategy (52 arms – 50%), followed by duration (39 arms – 37.5%). Only one (1%) treatment arm adjusted the dosing schedule 83 .…”

Section: Resultsmentioning

confidence: 99%

“…Uemura et al . 83 studied a 2-week lead-in period of daily IFN-beta injections before 12 weeks’ sofosbuvir/ledipasvir in DAA-experienced individuals. Only six participants were recruited (SVR 66.7%).…”

Section: Discussionmentioning

confidence: 99%

Treatment optimisation for hepatitis C in the era of combination direct-acting antiviral therapy: a systematic review and meta-analysis

Jones¹,

Flower²,

Barber³

et al. 2019

Wellcome Open Res

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Background: Prior to direct-acting antiviral (DAA) therapy, personalised medicine played an important role in the treatment of hepatitis C virus (HCV). Whilst simplified treatment strategies are central to treatment scale-up, some patients will benefit from treatment optimisation. This systematic review and meta-analysis explores treatment optimisation strategies in the DAA era. Methods: We systematically searched Medline, Embase, and Web of Science for studies that adopted a stratified or personalised strategy using a licensed combination DAA regimen, alone or with additional agents. We performed a thematic analysis to classify optimisation strategies and a meta-analysis of sustained virologic response rates (SVR), exploring heterogeneity with subgroup analyses and meta-regression. Results: We included 64 studies (9450 participants). Thematic analysis found evidence of three approaches: duration, combination, and/or dose optimisation. We separated strategies into those aiming to maintain SVR in the absence of predictors of failure, and those aiming to improve SVR in the presence of predictors of failure. Shortened duration regimens achieve pooled SVR rates of 94.2% (92.3-95.9%) for 8 weeks, 81.1% (75.1-86.6%) for 6 weeks, and 63.1% (39.9-83.7%) for ≤4 weeks. Personalised strategies (100% vs 87.6%; p<0.001) and therapy shortened according to ≥3 host/viral factors (92.9% vs 81.4% or 87.2% for 1 or 2 host/viral factors, respectively; p=0.008) offer higher SVR rates when shortening therapy. Hard-to-treat HCV genotype 3 patients suffer lower SVR rates despite treatment optimisation (92.6% vs 98.2%; p=0.001). Conclusions: Treatment optimisation for individuals with multiple predictors of treatment failure can offer high SVR rates. More evidence is needed to identify with confidence those individuals in whom SVR can be achieved with shortened duration treatment.

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“…In the prediction model using the training data set, a good prediction model with a accuracy rate of 90% or more was obtained by both SVM and NN ( Table 2). The HCV genomic variants identified by the prediction model tended to be those that have been previously reported to be associated with successful DAA, such as the NS5A p.L28M mutation [14] and the p.R566H mutation [15]. The number of predictors provided by SVM, NN, KNN, LR, RF, FDA, GBM, DT, and NB were 81,…”

Section: Plos Onementioning

confidence: 90%

A machine learning-based treatment prediction model using whole genome variants of hepatitis C virus

et al. 2020

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In recent years, the development of diagnostics using artificial intelligence (AI) has been remarkable. AI algorithms can go beyond human reasoning and build diagnostic models from a number of complex combinations. Using next-generation sequencing technology, we identified hepatitis C virus (HCV) variants resistant to directing-acting antivirals (DAA) by whole genome sequencing of full-length HCV genomes, and applied these variants to various machine-learning algorithms to evaluate a preliminary predictive model. HCV genomic RNA was extracted from serum from 173 patients (109 with subsequent sustained virological response [SVR] and 64 without) before DAA treatment. HCV genomes from the 109 SVR and 64 non-SVR patients were randomly divided into a training data set (57 SVR and 29 non-SVR) and a validation-data set (52 SVR and 35 non-SVR). The training data set was subject to nine machine-learning algorithms selected to identify the optimized combination of functional variants in relation to SVR status following DAA therapy. Subsequently, the prediction model was tested by the validation-data set. The most accurate learning method was the support vector machine (SVM) algorithm (validation accuracy, 0.95; kappa statistic, 0.90; F-value, 0.94). The second-most accurate learning algorithm was Multi-layer perceptron. Unfortunately, Decision Tree, and Naive Bayes algorithms could not be fitted with our data set due to low accuracy (< 0.8). Conclusively, with an accuracy rate of 95.4% in the generalization performance evaluation, SVM was identified as the best algorithm. Analytical methods based on genomic analysis and the construction of a predictive model by machine-learning may be applicable to the selection of the optimal treatment for other viral infections and cancer.

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Retreatment with sofosbuvir/ledipasvir with or without lead‐in interferon‐β injections in patients infected with genotype 1b hepatitis C virus after unsuccessful daclatasvir/asunaprevir therapy

Cited by 7 publications

References 28 publications

Involvement of portosystemic shunts in impaired improvement of liver function after direct‐acting antiviral therapies in cirrhotic patients with hepatitis C virus

Involvement of portosystemic shunts in impaired improvement of liver function after direct‐acting antiviral therapies in cirrhotic patients with hepatitis C virus

Treatment optimisation for hepatitis C in the era of combination direct-acting antiviral therapy: a systematic review and meta-analysis

A machine learning-based treatment prediction model using whole genome variants of hepatitis C virus

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