Evidence map›Paper›PMID 33717047›Full record

ArticleFrontiers in microbiology2021

Predicting Post-treatment HIV Remission: Does Size of the Viral Reservoir Matter?

Alexander O Pasternak, Christina K Psomas, Ben Berkhout

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  4. Review
  5. Review
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 at 1 institution in 1 country.

Alexander O PasternakLaboratory of Experimental Virology, Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
Christina K PsomasDepartment of Infectious Diseases and Internal Medicine, European Hospital, Marseille, France.
Ben BerkhoutLaboratory of Experimental Virology, Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
Amsterdam University Medical Centers · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combination antiretroviral therapy (ART) suppresses human immunodeficiency virus (HIV) replication and improves immune function. However, due to the persistence of long-lived HIV reservoirs, therapy interruption almost inevitably leads to a fast viral rebound. A small percentage of individuals who are able to control HIV replication for extended periods after therapy interruption are of particular interest because they may represent a model of long-term HIV remission without ART. These individuals are characterized by a limited viral reservoir and low reservoir measures can predict post-treatment HIV remission. However, most individuals with a low reservoir still experience fast viral rebound. In this Perspective, we discuss the possible reasons behind this and propose to develop an integral profile, composed of viral and host biomarkers, that could allow the accurate prediction of post-treatment HIV remission. We also propose to incorporate information on the chromatin context of the proviral integration sites into the characterization of the HIV reservoir, as this likely influences the reactivation capacity of latent proviruses and, together with the actual number of intact proviruses, contributes to the replication competence of the reservoir.

Indexed as

antiretroviral therapybiomarkerHIVpost-treatment controllerspredictive markerprofileviral reservoir

Identifiers

PMID33717047
PMCPMC7952863
OpenAlexW3134806277

What OpenQuestion holds

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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.