Evidence map›Paper›PMID 24417811›Full record

ArticleHIV medicine2014

Community HIV-1 drug resistance is associated with transmitted drug resistance.

M W Tilghman, J Pérez-Santiago, G Osorio, S J Little, D D Richman, W C Mathews, R H Haubrich, D M Smith

Abstract read
In one paragraph

Article in HIV medicine, 2014. 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. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Trends and predictors of HIV-1 acquired drug resistance in Minas Gerais, Brazil: 2002-2012.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases
    Article
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

8 authors.

M W TilghmanDepartment of Medicine, University of California San Diego, La Jolla, CA, USA.
J Pérez-Santiago
G Osorio
S J Little
D D Richman
W C Mathews
R H Haubrich
D M Smith

Funding

Unsolicited R24 for the CFAR-Network of Integrated Clinical Sciences, CNICSR24AI067039 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Michael S. Saag · 2006 to 2026
$99.4M
VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUSAN JANET LITTLE · 1994 to 2026
$78.4M
UCSD Department of Medicine HIV/AIDS Clinical Trials UnitUM1AI069432 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TIMOTHY J. WILKIN · 2012 to 2026
$50.4M
STRUCTURAL NEUROIMAGING COREP30MH062512 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DAVID J MOORE · 2001 to 2026
$50.4M
Using NK Cells to eliminate the latent HIV reservoirU19AI096113 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WOELK, CHRISTOPHER H · 2011 to 2015
$39.5M
Transmission ProbabilityP01AI074621 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LITTLE, SUSAN JANET · 2008 to 2012
$23.1M
Primary Infection Resource Consortium (PIRC)R24AI106039 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LITTLE, SUSAN JANET · 2013 to 2021
$23.1M
Southern California Primary Infection ProgramU01AI043638 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RICHMAN, DOUGLAS D · 1998 to 2010
$21.3M
UCSD Department of Medicine HIV/AIDS Clinical Trials UnitU01AI069432 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BENSON, CONSTANCE ANN · 2007 to 2011
$19.3M
HOPE Training GrantT32AI007384 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Sara Gianella Weibel, Scott L Letendre · 1990 to 2026
$9.7M
Molecular Epidemiology for HIV Prevention for Drug Users and Other Risk Groups DP1DA034978 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SMITH, DAVID MITCHELL · 2012 to 2016
$4.1M
Biomathematical analysis of viral dynamics/evolutionR01AI047745 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RICHMAN, DOUGLAS D · 2001 to 2011
$3.2M
NIAID NIH HHS AI007384NIAID NIH HHS AI043638NIAID NIH HHS AI047745NIAID NIH HHS AI064086NIAID NIH HHS AI067039NIAID NIH HHS AI077304NIAID NIH HHS AI080193NIAID NIH HHS AI080353NIAID NIH HHS AI080397NIAID NIH HHS AI096113NIAID NIH HHS AI100665NIAID NIH HHS AI36214NIAID NIH HHS AI69432NIAID NIH HHS AI74621NIAID NIH HHS K24 AI064086NIAID NIH HHS K24 AI100665NIAID NIH HHS P01 AI074621NIAID NIH HHS P01 AI080193NIAID NIH HHS P30 AI036214NIAID NIH HHS R01 AI047745NIAID NIH HHS R21 AI047745NIAID NIH HHS R21 AI077304NIAID NIH HHS R21 AI080353NIAID NIH HHS R21 AI080397NIAID NIH HHS R24 AI067039NIAID NIH HHS R24 AI106039NIAID NIH HHS R56 AI047745NIAID NIH HHS T32 AI007384NIAID NIH HHS U01 AI043638NIAID NIH HHS U01 AI069432NIAID NIH HHS U19 AI096113NIAID NIH HHS UM1 AI069432NIDA NIH HHS DA034978NIDA NIH HHS DP1 DA034978NIMH NIH HHS MH62512NIMH NIH HHS P30 MH062512
6 · The paper itself

Abstract

objectivesAs community viral load (CVL) measurements are associated with the incidence of new HIV-1 infections in a population, we hypothesized that similarly measured community drug resistance (CDR) could predict the prevalence of transmitted drug resistance (TDR).

methodsBetween 2001 and 2011, the prevalences of HIV-1 drug resistance for patients with established infection receiving HIV care (i.e. CDR) and TDR in recently infected patients were determined in San Diego. At each position in HIV-1 reverse transcriptase (RT) and protease (pro), drug resistance was evaluated both as the overall prevalence of resistance-associated mutations and by weighting each resistance position to the concurrent viral load of the patient and its proportion to the total viral load of the clinic (CVL). The weighting was the proportion of the CVL associated with patients identified with resistance at each residue. Spearman ranked correlation coefficients were used to determine associations between CDR and TDR.

resultsWe analysed 1088 resistance tests for 971 clinic patients and baseline resistance tests for 542 recently infected patients. CDR at positions 30, 46, and 88 in pro was associated with TDR between 2001 and 2011. When CDR was weighted by the viral load of patients, CDR was associated with TDR at position 103 in RT. Each of these associations was corroborated at least once using shorter measurement intervals.

conclusionsDespite evaluation of a limited percentage of chronically infected patients in San Diego, CDR correlated with TDR at key resistance positions and therefore may be a useful tool with which to predict the prevalence of TDR.

Indexed as

Drug Resistance, ViralAdultAnalysis of VarianceAnti-HIV AgentsCaliforniaCD4 Lymphocyte CountCohort StudiesFemaleHIV-1HIV InfectionsHIV ProteaseHumansMaleMiddle AgedMutationPrevalenceAnti-HIV AgentsHIV ProteaseRNA-Directed DNA PolymeraseRNA, Viralgenotypehighly active antiretroviral therapyHIVmutationviral drug resistanceviral load

Identifiers

PMID24417811
PMCPMC4055747

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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.