Evidence map›Paper›PMID 26147742›Full record

ArticleJournal of medical virology2016

Comparison of genotypic and virtual phenotypic drug resistance interpretations with laboratory-based phenotypes among CRF01_AE and subtype B HIV-infected individuals.

Awachana Jiamsakul, Romanee Chaiwarith, Nicolas Durier, Sunee Sirivichayakul, Sasisopin Kiertiburanakul, Peter Van Den Eede, Rossana Ditangco, Adeeba Kamarulzaman, Patrick C K Li, Winai Ratanasuwan and 2 more

Abstract readComparative Study
In one paragraph

Article in Journal of medical virology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

12 authors.

Awachana JiamsakulThe Kirby Institute, UNSW Australia, Sydney, Australia.
Romanee ChaiwarithResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.
Nicolas DurierTREAT Asia, amfAR - The Foundation for AIDS Research, Bangkok, Thailand.
Sunee SirivichayakulFaculty of Medicine, Chulalongkorn University and HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand.
Sasisopin KiertiburanakulFaculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Peter Van Den EedeJanssen Diagnostics BVBA, Beerse, Belgium.
Rossana DitangcoResearch Institute for Tropical Medicine, Manila, Philippines.
Adeeba KamarulzamanUniversity of Malaya Medical Center, Kuala Lumpur, Malaysia.
Patrick C K LiDepartment of Medicine, Queen Elizabeth Hospital, Hong Kong, China.
Winai RatanasuwanFaculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Thira SirisanthanaResearch Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand.
TREAT Asia Studies to Evaluate Resistance--Monitoring Study TASER-M

Funding

The Asia-Pacific HIV Research CollaborationU01AI069907 · NIAID · FOUNDATION FOR AIDS RESEARCH · PI ANNETTE H SOHN · 2006 to 2026
$44.8M
NIAID NIH HHS U01 AI069907NIAID NIH HHS U01AI069907
6 · The paper itself

Abstract

HIV drug resistance assessments and interpretations can be obtained from genotyping (GT), virtual phenotyping (VP) and laboratory-based phenotyping (PT). We compared resistance calls obtained from GT and VP with those from PT (GT-PT and VP-PT) among CRF01_AE and subtype B HIV-1 infected patients. GT predictions were obtained from the Stanford HIV database. VP and PT were obtained from Janssen Diagnostics BVBA's vircoType(TM) HIV-1 and Antivirogram®, respectively. With PT assumed as the "gold standard," the area under the curve (AUC) and the Bland-Altman plot were used to assess the level of agreement in resistance interpretations. A total of 80 CRF01_AE samples from Asia and 100 subtype B from Janssen Diagnostics BVBA's database were analysed. CRF01_AE showed discordances ranging from 3 to 27 samples for GT-PT and 1 to 20 samples for VP-PT. The GT-PT and VP-PT AUCs were 0.76-0.97 and 0.81-0.99, respectively. Subtype B showed 3-61 discordances for GT-PT and 2-75 discordances for VP-PT. The AUCs ranged from 0.55 to 0.95 for GT-PT and 0.55 to 0.97 for VP-PT. Didanosine had the highest proportion of discordances and/or AUC in all comparisons. The patient with the largest didanosine FC difference in each subtype harboured Q151M mutation. Overall, GT and VP predictions for CRF01_AE performed significantly better than subtype B for three NRTIs. Although discrepancies exist, GT and VP resistance interpretations in HIV-1 CRF01_AE strains were highly robust in comparison with the gold-standard PT.

Indexed as

Drug Resistance, ViralGenotypePhenotypeAnti-HIV AgentsAsiaGenotyping TechniquesHIV-1HIV InfectionsHumansMicrobial Sensitivity TestsAnti-HIV Agentsalgorithmdrug resistancesubtype

Identifiers

PMID26147742
PMCPMC4698354

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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.