Evidence map›Paper›PMID 23350534›Full record

ArticleAIDS research and human retroviruses2013

Comparison of population and 454 "deep" sequence analysis for HIV type 1 tropism versus the original trofile assay in non-B subtypes.

Guinevere Q Lee, P Richard Harrigan, Winnie Dong, Art F Y Poon, Jayvant Heera, James Demarest, Alex Rinehart, Doug Chapman, Hernan Valdez, Simon Portsmouth

Abstract readComparative Study
In one paragraph

Article in AIDS research and human retroviruses, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Deep sequencing: becoming a critical tool in clinical virology.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2014
    Review
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Guinevere Q LeeBC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada.
P Richard Harrigan
Winnie Dong
Art F Y Poon
Jayvant Heera
James Demarest
Alex Rinehart
Doug Chapman
Hernan Valdez
Simon Portsmouth

Funding

Canadian Institutes of Health Research 201009HOP-235256
6 · The paper itself

Abstract

HIV-1 tropism can be predicted using V3 genotypic algorithms. The performance of these prediction algorithms for non-B subtypes is poorly characterized. Here, we use these genotypic algorithms to predict viral tropism of HIV-1 subtype A, B, C, and D to find apparent sensitivity, specificity, and concordance against a recombinant phenotypic assay, the original Trofile assay. This is a substudy of an epidemiological study (Pfizer A4001064). Plasma samples were selected to represent a large number of DM/X4 and R5 viruses. The HIV-1 env gene V3 loop was genotyped by Sanger sequencing (N=260) or 454 "deep" sequencing (N=280). Sequences were scored with g2p[coreceptor], PSSM X4/R5, PSSM SI/NSI, and PSSM subtype C matrices. Overall, non-B subtypes tropism prediction had similar concordance and apparent sensitivity and specificity as subtype B in predicting Trofile's results in both population sequencing (81.3%, 65.6%, and 90.5% versus 84.2%, 78.5%, and 88.2%) and 454 "deep" sequencing (82.3%, 80.0%, and 83.6% versus 86.8%, 92.0%, and 82.6%) using g2p[coreceptor]. By population sequencing, subtype A had lower sensitivity, whereas subtype D had lower specificity for non-R5 predictions, both in comparison to subtype B. 454 "deep" sequencing improved subtype A sensitivity but not subtype D. Subtype C had greater concordance than subtype B regardless of sequencing methods. In conclusion, genotypic tropism prediction algorithms may be applied to non-B HIV-1 subtypes with caution. Collective analysis of non-B subtypes revealed a performance similar to subtype B, whereas a subtype-specific analysis revealed overestimation (subtype D) or underestimation (subtype A).

Indexed as

AlgorithmsGenotypeHIV-1HIV Envelope Protein gp120Peptide FragmentsPhenotypeSensitivity and SpecificitySequence Analysis, DNAViral TropismHIV Envelope Protein gp120HIV envelope protein gp120 (305-321)Peptide Fragments

Identifiers

PMID23350534
PMCPMC3653393

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