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Exploring resistance pathways for first-generation NS3/4A protease inhibitors boceprevir and telaprevir using Bayesian network learning.

Author: Ceccherini-SilbersteinFrancesca, CentoValeria, CuypersLize, Di MaioVelia Chiara, LibinPieter, LunarMaja M, NevensFrederik, NowéAnn, PoljakMario, SchrootenYoeri, TheysKristof, Van LaethemKristel, VandammeAnne-Mieke

Journal ArticleAn article published in an academic or professional journal that reports original research or scholarly analysis.
Multicenter StudyResearch conducted in collaboration with multiple research institutions. It aims to collect a wide range of data and obtain more generalizable results.

Overview

Resistance-associated variants (RAVs) can influence treatment response to direct-acting antivirals (DAAs) for hepatitis C virus (HCV). This study used Bayesian network analysis to identify RAVs associated with resistance to protease inhibitors in HCV subtypes 1a and 1b.
Paper Details　
Original Abstract of the Article :
Resistance-associated variants (RAVs) have been shown to influence treatment response to direct-acting antivirals (DAAs) and first generation NS3/4A protease inhibitors (PIs) in particular. Interpretation of hepatitis C virus (HCV) genotypic drug resistance remains a challenge, especially in patient...See full text at original site
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引用元：
https://doi.org/10.1016/j.meegid.2017.05.007

データ提供：米国国立医学図書館（NLM）

Mapping Resistance Pathways in Hepatitis C Treatment

This study dives into the dynamic landscape of hepatitis C treatment, exploring the complex interplay between viral resistance and direct-acting antivirals (DAAs). Hepatitis C, like a desert disease, can be challenging to treat, especially with the emergence of drug resistance.

Unraveling Resistance Patterns

This study uses a Bayesian network (BN) learning approach, like creating a detailed map of a desert, to analyze HCV sequence data from patients treated with DAAs, particularly first-generation NS3/4A protease inhibitors (PIs). The researchers identified specific NS3 substitutions associated with PI resistance, providing valuable insights into the mechanisms of resistance.

Implications for Treatment Strategies

This study highlights the importance of understanding resistance pathways to optimize treatment strategies for hepatitis C. It's like learning the best routes to navigate a desert – understanding the terrain of resistance allows clinicians to choose the most effective paths to combat the virus.

Dr. Camel's Conclusion

This study contributes to the ongoing quest to conquer hepatitis C. By mapping the intricate landscape of viral resistance, this study provides valuable information for developing more effective treatment strategies and guiding individualized care for patients.
Date :
  1. Date Completed 2018-03-29
  2. Date Revised 2019-12-10
Further Info :

Pubmed ID

28499845

DOI: Digital Object Identifier

10.1016/j.meegid.2017.05.007

Related Literature

Article Analysis
・Effects of telaprevir
SNS
PICO Info
in preparation
Languages

English

Positive IndicatorAn AI analysis index that serves as a benchmark for how positive the results of the study are. Note that it is a benchmark and requires careful interpretation and consideration of different perspectives.

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