Evidence map›Paper›PMID 22686620›Full record

ReviewDrugs2012

HIV-1 antiretroviral resistance: scientific principles and clinical applications.

Michele W Tang, Robert W Shafer

Open access · bronzeAbstract readReview
In one paragraph

Review in Drugs, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 162 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
162citing papers in PubMed, 3 pooled it
15.6field-weighted citation impact, top 1% 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

162 citing papers in PubMed, 3 syntheses or guidelines pooled it, 321 citations in OpenAlex.

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

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

2 authors at 1 institution in 1 country.

Michele W TangStanford University, Division of Infectious Diseases, Stanford, CA 94305-5107, USA. micheletang@gmail.com
Robert W Shafer
Stanford University · US

Funding

PUBLIC HIV DRUG RESISTANCE DATABASER01AI068581 · NIAID · STANFORD UNIVERSITY · PI SHAFER, ROBERT WILLIAM · 2006 to 2017
$6.2M
PUBLIC HIV DRUG RESISTANCE DATABASER56AI068581 · NIAID · STANFORD UNIVERSITY · PI SHAFER, ROBERT WILLIAM · 2013 to 2013
$729k
NIAID NIH HHS AI068581NIAID NIH HHS R01 AI068581NIAID NIH HHS R56 AI068581
6 · The paper itself

Abstract

The efficacy of an antiretroviral (ARV) treatment regimen depends on the activity of the regimen's individual ARV drugs and the number of HIV-1 mutations required for the development of resistance to each ARV - the genetic barrier to resistance. ARV resistance impairs the response to therapy in patients with transmitted resistance, unsuccessful initial ARV therapy and multiple virological failures. Genotypic resistance testing is used to identify transmitted drug resistance, provide insight into the reasons for virological failure in treated patients, and help guide second-line and salvage therapies. In patients with transmitted drug resistance, the virological response to a regimen selected on the basis of standard genotypic testing approaches the responses observed in patients with wild-type viruses. However, because such patients are at a higher risk of harbouring minority drug-resistant variants, initial ARV therapy in this population should contain a boosted protease inhibitor (PI) - the drug class with the highest genetic barrier to resistance. In patients receiving an initial ARV regimen with a high genetic barrier to resistance, the most common reasons for virological failure are nonadherence and, potentially, pharmacokinetic factors or minority transmitted drug-resistant variants. Among patients in whom first-line ARVs have failed, the patterns of drug-resistance mutations and cross-resistance are often predictable. However, the extent of drug resistance correlates with the duration of uncontrolled virological replication. Second-line therapy should include the continued use of a dual nucleoside/nucleotide reverse transcriptase inhibitor (NRTI)-containing backbone, together with a change in the non-NRTI component, most often to an ARV belonging to a new drug class. The number of available fully active ARVs is often diminished with each successive treatment failure. Therefore, a salvage regimen is likely to be more complicated in that it may require multiple ARVs with partial residual activity and compromised genetic barriers of resistance to attain complete virological suppression. A thorough examination of the patient's ARV history and prior resistance tests should be performed because genotypic and/or phenotypic susceptibility testing is often not sufficient to identify drug-resistant variants that emerged during past therapies and may still pose a threat to a new regimen. Phenotypic testing is also often helpful in this subset of patients. ARVs used for salvage therapy can be placed into the following hierarchy: (i) ARVs belonging to a previously unused drug class; (ii) ARVs belonging to a previously used drug class that maintain significant residual antiviral activity; (iii) NRTI combinations, as these often appear to retain in vivo virological activity, even in the presence of reduced in vitro NRTI susceptibility; and rarely (iv) ARVs associated with previous virological failure and drug resistance that appear to have possibly regained their activity as a result of viral reversion to wild type. Understanding the basic principles of HIV drug resistance is helpful in guiding individual clinical decisions and the development of ARV treatment guidelines.

Indexed as

Anti-Retroviral AgentsAntiretroviral Therapy, Highly ActiveClinical Trials as TopicDrug Resistance, ViralGenotypeHIV-1HIV InfectionsHumansTreatment FailureViral LoadAnti-Retroviral Agents

Identifiers

PMID22686620
PMCPMC3689909
OpenAlexW2069388608

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.