Evidence map›Paper›PMID 27454561›Full record

ArticleAIDS (London, England)2016

Viral load criteria and threshold optimization to improve HIV incidence assay characteristics.

Reshma Kassanjee, Christopher D Pilcher, Michael P Busch, Gary Murphy, Shelley N Facente, Sheila M Keating, Elaine Mckinney, Kara Marson, Matthew A Price, Jeffrey N Martin and 5 more

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in AIDS (London, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 2 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

61 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  19. The HIV Epidemic in South Africa: Key Findings from 2017 National Population-Based Survey.International journal of environmental research and public health · 2022
    Article
  20. Article

1 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

15 authors.

Reshma KassanjeeaThe South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch bDepartment of Statistical Sciences, University of Cape Town, Cape Town, South Africa cUniversity of California dBlood Systems Research Institute, San Francisco, California, USA ePublic Health England, London, UK fInternational AIDS Vaccine Initiative (IAVI), Department of Medical Affairs, New York City, New York gDepartment of Medicine, University of California San Diego, San Diego, California, USA hDivision of Clinical Immunology and Allergy, School of Medicine, University of São Paulo, São Paulo, Brazil. *Christopher D. Pilcher and Alex Welte contributed equally to the writing of this article.
Christopher D Pilcher
Michael P Busch
Gary Murphy
Shelley N Facente
Sheila M Keating
Elaine Mckinney
Kara Marson
Matthew A Price
Jeffrey N Martin
Susan J Little
Frederick M Hecht
Esper G Kallas
Alex Welte
Consortium for the Evaluation and Performance of HIV Incidence Assays (CEPHIA)

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
Virology CoreP30AI027763 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEVEN Grant DEEKS · 1988 to 2026
$93.6M
VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Maile Ann Young Karris · 1994 to 2026
$78.4M
Transmission ProbabilityP01AI074621 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI RICHMAN, DOUGLAS D · 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
Transmission and Persistence of CTL and Drug Resistance MutationsP01AI071713 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HECHT, FREDERICK M · 2007 to 2011
$14.3M
Efficacy of ART to Interrupt HIV Transmission NetworksR01MH100974 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LITTLE, SUSAN JANET · 2014 to 2018
$3.2M
Host Factors Influencing HIV Viral Load and Infectivity in SemenR01HD074511 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PILCHER, CHRISTOPHER D · 2012 to 2016
$3.1M
A Pilot of Intervention to Promote Acute HIV Testing by Ambulatory Care ProvidersR34MH096606 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PILCHER, CHRISTOPHER D · 2012 to 2014
$693k
NIAID NIH HHS P01 AI071713NIAID NIH HHS P01 AI074621NIAID NIH HHS P30 AI027763NIAID NIH HHS P30 AI036214NIAID NIH HHS R24 AI067039NIAID NIH HHS R24 AI106039NIAID NIH HHS U01 AI043638NICHD NIH HHS R01 HD074511NIMH NIH HHS R01 MH100974NIMH NIH HHS R34 MH096606
6 · The paper itself

Abstract

objectiveAssays for classifying HIV infections as 'recent' or 'nonrecent' for incidence surveillance fail to simultaneously achieve large mean durations of 'recent' infection (MDRIs) and low 'false-recent' rates (FRRs), particularly in virally suppressed persons. The potential for optimizing recent infection testing algorithms (RITAs), by introducing viral load criteria and tuning thresholds used to dichotomize quantitative measures, is explored.

designThe Consortium for the Evaluation and Performance of HIV Incidence Assays characterized over 2000 possible RITAs constructed from seven assays (Limiting Antigen, BED, Less-sensitive Vitros, Vitros Avidity, BioRad Avidity, Architect Avidity, and Geenius) applied to 2500 diverse specimens.

methodsMDRIs were estimated using regression, and FRRs as observed 'recent' proportions, in various specimen sets. Context-specific FRRs were estimated for hypothetical scenarios. FRRs were made directly comparable by constructing RITAs with the same MDRI through the tuning of thresholds. RITA utility was summarized by the precision of incidence estimation.

resultsAll assays produce high FRRs among treated patients and elite controllers (10-80%). Viral load testing reduces FRRs, but diminishes MDRIs. Context-specific FRRs vary substantially by scenario - BioRad Avidity and Limiting Antigen provided the lowest FRRs and highest incidence precision in scenarios considered.

conclusionThe introduction of a low viral load threshold provides crucial improvements in RITAs. However, it does not eliminate nonzero FRRs, and MDRIs must be consistently estimated. The tuning of thresholds is essential for comparing and optimizing the use of assays. The translation of directly measured FRRs into context-specific FRRs critically affects their magnitudes and our understanding of the utility of assays.

Indexed as

HIV InfectionsHumansIncidenceViral Load

Identifiers

PMID27454561
PMCPMC5024345

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Registered trials

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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.