Evidence map›Paper›PMID 10884399›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2000

Production of resistant HIV mutants during antiretroviral therapy.

R M Ribeiro, S Bonhoeffer

Open access · greenAbstract readComparative Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
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

91 citing papers in PubMed, 1 synthesis or guideline pooled it, 230 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Compartmental structure in the secondary lymphoid tissue can slow downJournal of the Royal Society, Interface · 2025
    Article
  6. Article
  7. Modelling HIV-1 control and remission.NPJ systems biology and applications · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

31 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

R M RibeiroWellcome Trust Centre for the Epidemiology of Infectious Diseases, Department of Zoology, University of Oxford, South Parks Road, OX1 3PS, Oxford, United Kingdom.
S Bonhoeffer
Friedrich Miescher Institute · CHWellcome Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

HIV drug therapy often fails because of the appearance of multidrug-resistant virus. There are two possible scenarios for the outgrowth of multidrug-resistant virus in response to therapy. Resistant virus may preexist at low frequencies in drug-naive patients and is rapidly selected in the presence of drugs. Alternatively, resistant virus is absent at the start of therapy but is generated by residual viral replication during therapy. Currently available experimental methods are generally too insensitive to distinguish between these two scenarios. Here we use deterministic and stochastic models to investigate the origin of multidrug resistance. We quantify the probabilities that resistant mutants preexist, and that resistant mutants are generated during therapy. The models suggest that under a wide range of conditions, treatment failure is most likely caused by the preexistence of resistant mutants.

Indexed as

Models, GeneticMutationAnti-HIV AgentsComputer SimulationDrug Resistance, MicrobialHIVHIV InfectionsStochastic ProcessesTreatment FailureAnti-HIV Agents

Identifiers

PMID10884399
PMCPMC16603
OpenAlexW2060701294

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.