Analyzing the Effects of Pretreatment Diversity on HCV Drug Treatment Responsiveness Using Bayesian Partition methods.

Yao Fu, Gang Chen, Xuan Guo, Jing Zhang, Yi Pan

Open access · hybridAbstract read

In one paragraph

Article in Journal of bioinformatics and proteomics review. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Yao FuDepartment of Mathematics and Statistics, Georgia State University.

Gang ChenProgram of Computational Biology and Bioinformatics, Yale University.

Xuan GuoDepartment of Statistics, Yale University.

Jing ZhangDepartment of Computer Science, Georgia State University, Atlanta, Georgia, USA.

Yi Pan

Georgia State University · USYale University · US

Funding

YALE BIOMEDICAL SUPERCOMPUTER: NEUROSCIENCES10RR019895 · NCRR · YALE UNIVERSITY · PI WILLIAMS, KENNETH ROBERT · 2004 to 2004

$1.6M

NCRR NIH HHS S10 RR019895

6 · The paper itself

Abstract

Traditional therapies for Hepatitis C Virus (HCV) often yield unsatisfactory results. The reason for this may lie in the mechanism of drug resistance of the HCV virus. Despite doing a plain vanilla comparison between the treated and untreated groups, this paper takes a detour and investigates the drug resistance mechanism to interferon plus ribavirin combined therapy by comparing pretreatment sequence data between response and non-response patients in the NS5A region for genotype 1a HCV virus. We use Bayesian probabilistic models to detect single mutation or mutation combinations, and infer interaction structures between these mutations, to investigate the drug resistance combinations differences between those patients. We hope to decipher, at least partially, the reason behind the unsatisfactory results received from interferon plus ribavirin therapy. AUTHOR SUMMARY: HCV treatment results have been historically suboptimal

Identifiers

PMID26457332

PMCPMC4597793

OpenAlexW2288407877

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.