Evidence map›Paper›PMID 32046642›Full record

ArticleBMC bioinformatics2020

ushr: Understanding suppression of HIV in R.

Sinead E Morris, Luise Dziobek-Garrett, Andrew J Yates, In Collaboration With The Epiical Consortium

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Sinead E MorrisDepartment of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA. sinead.morris@columbia.edu.ORCID http://orcid.org/0000-0001-8626-1698
Luise Dziobek-GarrettDepartment of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
Andrew J YatesDepartment of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
In Collaboration With The Epiical ConsortiumDepartment of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHIV/AIDS is responsible for the deaths of one million people every year. Although mathematical modeling has provided many insights into the dynamics of HIV infection, there is still a lack of accessible tools for researchers unfamiliar with modeling techniques to apply them to their own clinical data.

resultsHere we present ushr, a free and open-source R package that models the decline of HIV during antiretroviral treatment (ART) using a popular mathematical framework. ushr can be applied to longitudinal data of viral load measurements, and provides processing tools to prepare it for computational analysis. By mathematically fitting the data, important biological parameters can then be estimated, including the lifespans of short and long-lived infected cells, and the time to reach viral suppression below a defined detection threshold. The package also provides visualization and summary tools for fast assessment of model results.

conclusionsushr enables researchers without a strong mathematical or computational background to model the dynamics of HIV using longitudinal clinical data. Increasing accessibility to such methods may facilitate quantitative analysis across a broader range of independent studies, so that greater insights on HIV infection and treatment dynamics may be gained.

Indexed as

SoftwareAnti-HIV AgentsHIVHIV InfectionsHumansModels, BiologicalViral LoadAnti-HIV AgentsARTBiphasic decayHIVMathematical modelR package

Identifiers

PMID32046642
PMCPMC7014720

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Registered trials

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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.