Evidence map›Paper›PMID 22417909›Full record

ArticleJournal of the Royal Society, Interface2012

Assessing the impact of adherence to anti-retroviral therapy on treatment failure and resistance evolution in HIV.

Dominique Cadosch, Sebastian Bonhoeffer, Roger Kouyos

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Trial
  2. Article
  3. HIV-1 Transcription Inhibition Using Small RNA-Binding Molecules.Pharmaceuticals (Basel, Switzerland) · 2023
    Article
  4. Review
  5. Review
  6. Article
  7. Article
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  12. Article
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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

3 authors.

Dominique CadoschInstitute of Integrative Biology, ETH Zurich, 8092 Zurich, Switzerland. dominique.cadosch@env.ethz.ch
Sebastian Bonhoeffer
Roger Kouyos

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adherence of patients to therapy is a crucial factor for successful HIV anti-retroviral therapy. Imperfect adherence may lead to treatment failure, which can cause the emergence of resistance within viral populations. We have developed a stochastic model that incorporates compartments of latently infected cells and virus genotypes with different susceptibilities to three simultaneously used drugs. With this model, we study the impact of several key parameters on the probability of treatment failure, i.e. insufficient viral suppression, and the emergence of resistance. Specifically, we consider the impact of drug dosage, drug half-lives, fitness costs for resistance, different basic reproductive numbers of the virus and the influence of pre-existing mutations under various levels of adherence. Furthermore, we also investigate the influence of different temporal distributions of non-adherent days (drug holidays) during a treatment. Factors that promote resistance evolution include a high reproductive number, extended drug holidays and poor adherence. Pre-existing mutations only have a substantial effect if they confer resistance against more than one drug. Overall, our study highlights the importance of the interactions between imperfect adherence, pharmacodynamics, pharmacokinetics and latently infected cells for our understanding of drug resistance and therapy failure in HIV anti-retroviral therapy.

Indexed as

Antiretroviral Therapy, Highly ActiveDrug Resistance, Multiple, ViralEvolution, MolecularHIV-1HIV InfectionsMedication AdherenceModels, BiologicalHumansMutationTreatment Failure

Identifiers

PMID22417909
PMCPMC3405760

What OpenQuestion holds

Textmetadata
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.