Evidence map›Paper›PMID 25710171›Full record

ArticlePloS one2015

Recalibration of the limiting antigen avidity EIA to determine mean duration of recent infection in divergent HIV-1 subtypes.

Yen T Duong, Reshma Kassanjee, Alex Welte, Meade Morgan, Anindya De, Trudy Dobbs, Erin Rottinghaus, John Nkengasong, Marcel E Curlin, Chonticha Kittinunvorakoon and 14 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing 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

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

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13 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

24 authors.

Yen T DuongInternational Laboratory Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Reshma KassanjeeThe South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch, Stellenbosch, South Africa; School of Computational and Applied Mathematics, University of the Witwatersrand, Johannesburg, South Africa.
Alex WelteThe South African DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch, Stellenbosch, South Africa.
Meade MorganEpidemiology and Strategic Information Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Anindya DeEpidemiology and Strategic Information Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Trudy DobbsInternational Laboratory Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Erin RottinghausInternational Laboratory Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
John NkengasongInternational Laboratory Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Marcel E CurlinThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Chonticha KittinunvorakoonThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Boonyos RaengsakulrachThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Michael MartinThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Kachit ChoopanyaThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Suphak VanichseniThailand Ministry of Public Health-US CDC Collaboration, Bangkok, Thailand.
Yan JiangNational AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Maofeng QiuNational AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Haiying YuNational AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yan HaoNational AIDS Reference Laboratory, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Neha ShahCalifornia Department of Public Health, Richmond, California, United States of America.
Linh-Vi LeDivision of Global HIV/AIDS, Centers for Disease Control and Prevention, Hanoi, Vietnam.
Andrea A KimCDC-Kenya, Nairobi, Kenya.
Tuan Anh NguyenNational Institute of Hygiene and Epidemiology, Hanoi, Vietnam.
William AmpofoNoguchi Memorial Institute for Medical Research, Accra, Ghana.
Bharat S ParekhInternational Laboratory Branch, Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.

Funding

PEPFAR
6 · The paper itself

Abstract

backgroundMean duration of recent infection (MDRI) and misclassification of long-term HIV-1 infections, as proportion false recent (PFR), are critical parameters for laboratory-based assays for estimating HIV-1 incidence. Recent review of the data by us and others indicated that MDRI of LAg-Avidity EIA estimated previously required recalibration. We present here results of recalibration efforts using >250 seroconversion panels and multiple statistical methods to ensure accuracy and consensus.

methodsA total of 2737 longitudinal specimens collected from 259 seroconverting individuals infected with diverse HIV-1 subtypes were tested with the LAg-Avidity EIA as previously described. Data were analyzed for determination of MDRI at ODn cutoffs of 1.0 to 2.0 using 7 statistical approaches and sub-analyzed by HIV-1 subtypes. In addition, 3740 specimens from individuals with infection >1 year, including 488 from patients with AIDS, were tested for PFR at varying cutoffs.

resultsUsing different statistical methods, MDRI values ranged from 88-94 days at cutoff ODn = 1.0 to 177-183 days at ODn = 2.0. The MDRI values were similar by different methods suggesting coherence of different approaches. Testing for misclassification among long-term infections indicated that overall PFRs were 0.6% to 2.5% at increasing cutoffs of 1.0 to 2.0, respectively. Balancing the need for a longer MDRI and smaller PFR (<2.0%) suggests that a cutoff ODn = 1.5, corresponding to an MDRI of 130 days should be used for cross-sectional application. The MDRI varied among subtypes from 109 days (subtype A&D) to 152 days (subtype C).

conclusionsBased on the new data and revised analysis, we recommend an ODn cutoff = 1.5 to classify recent and long-term infections, corresponding to an MDRI of 130 days (118-142). Determination of revised parameters for estimation of HIV-1 incidence should facilitate application of the LAg-Avidity EIA for worldwide use.

Indexed as

Antibody AffinityCalibrationHIV-1HIV AntigensHIV SeropositivityHumansImmunoenzyme TechniquesSerologic TestsHIV Antigens

Identifiers

PMID25710171
PMCPMC4339840

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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.