Literature DB >> 20954834

Determination of mean recency period for estimation of HIV type 1 Incidence with the BED-capture EIA in persons infected with diverse subtypes.

Bharat S Parekh1, Debra L Hanson, John Hargrove, Bernard Branson, Timothy Green, Trudy Dobbs, Niel Constantine, Julie Overbaugh, J Steven McDougal.   

Abstract

The IgG capture BED enzyme immunoassay (BED-CEIA) was developed to detect recent HIV-1 infection for the estimation of HIV-1 incidence from cross-sectional specimens. The mean time interval between seroconversion and reaching a specified assay cutoff value [referred to here as the mean recency period (ω)], an important parameter for incidence estimation, is determined for some HIV-1 subtypes, but testing in more cohorts and new statistical methods suggest the need for a revised estimation of ω in different subtypes. A total of 2927 longitudinal specimens from 756 persons with incident HIV infections who had been enrolled in 17 cohort studies was tested by the BED-CEIA. The ω was determined using two statistical approaches: (1) linear mixed effects regression (ω(1)) and (2) a nonparametric survival method (ω(2)). Recency periods varied among individuals and by population. At an OD-n cutoff of 0.8, ω(1) was 176 days (95% CL 164-188 days) whereas ω(2) was 162 days (95% CL 152-172 days) when using a comparable subset of specimens (13 cohorts). When method 2 was applied to all available data (17 cohorts), ω(2) ranged from 127 days (Thai AE) to 236 days (subtypes AG, AD) with an overall ω(2) of 197 days (95% CL 173-220). About 70% of individuals reached a threshold OD-n of 0.8 by 197 days (mean ω) and 95% of people reached 0.8 OD-n by 480 days. The determination of ω with more data and new methodology suggests that ω of the BED-CEIA varies between different subtypes and/or populations. These estimates for ω may affect incidence estimates in various studies.

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Year:  2010        PMID: 20954834     DOI: 10.1089/aid.2010.0159

Source DB:  PubMed          Journal:  AIDS Res Hum Retroviruses        ISSN: 0889-2229            Impact factor:   2.205


  56 in total

1.  Factors associated with incorrect identification of recent HIV infection using the BED capture immunoassay.

Authors:  Oliver Laeyendecker; Ron Brookmeyer; Amy E Oliver; Caroline E Mullis; Kevin P Eaton; Amy C Mueller; Lisa P Jacobson; Joseph B Margolick; Joelle Brown; Charles R Rinaldo; Thomas C Quinn; Susan H Eshleman
Journal:  AIDS Res Hum Retroviruses       Date:  2011-12-01       Impact factor: 2.205

2.  Strengthening HIV surveillance: measurements to track the epidemic in real time.

Authors:  Usangiphile E Buthelezi; Candace L Davidson; Ayesha Bm Kharsany
Journal:  Afr J AIDS Res       Date:  2016-07       Impact factor: 1.300

3.  Specificity of four laboratory approaches for cross-sectional HIV incidence determination: analysis of samples from adults with known nonrecent HIV infection from five African countries.

Authors:  Oliver Laeyendecker; Ron Brookmeyer; Caroline E Mullis; Deborah Donnell; Jairam Lingappa; Connie Celum; Jared M Baeten; Mary S Campbell; Max Essex; Guy de Bruyn; Carey Farquhar; Thomas C Quinn; Susan H Eshleman
Journal:  AIDS Res Hum Retroviruses       Date:  2012-10       Impact factor: 2.205

4.  Refined identification of neutralization-resistant HIV-1 CRF02_AG viruses.

Authors:  Rajesh Abraham Jacob; Fatima Abrahams; Marcel Tongo; Michael Schomaker; Paul Roux; Eitel Mpoudi Ngole; Wendy A Burgers; Jeffrey R Dorfman
Journal:  J Virol       Date:  2012-05-09       Impact factor: 5.103

5.  Impact of HIV subtype on performance of the limiting antigen-avidity enzyme immunoassay, the bio-rad avidity assay, and the BED capture immunoassay in Rakai, Uganda.

Authors:  Andrew F Longosz; David Serwadda; Fred Nalugoda; Godfrey Kigozi; Veronica Franco; Ronald H Gray; Thomas C Quinn; Susan H Eshleman; Oliver Laeyendecker
Journal:  AIDS Res Hum Retroviruses       Date:  2013-10-25       Impact factor: 2.205

6.  Poor performance of the determine HIV-1/2 Ag/Ab combo fourth-generation rapid test for detection of acute infections in a National Household Survey in Swaziland.

Authors:  Yen T Duong; Yvonne Mavengere; Hetal Patel; Carole Moore; Julius Manjengwa; Dumile Sibandze; Christopher Rasberry; Charmaine Mlambo; Zhi Li; Lynda Emel; Naomi Bock; Jan Moore; Rejoice Nkambule; Jessica Justman; Jason Reed; George Bicego; Dennis L Ellenberger; John N Nkengasong; Bharat S Parekh
Journal:  J Clin Microbiol       Date:  2014-08-13       Impact factor: 5.948

7.  Assessment of ambiguous base calls in HIV-1 pol population sequences as a biomarker for identification of recent infections in HIV-1 incidence studies.

Authors:  Karolin Meixenberger; Andrea Hauser; Klaus Jansen; Kaveh Pouran Yousef; Stefan Fiedler; Max von Kleist; Stephen Norley; Sybille Somogyi; Osamah Hamouda; Norbert Bannert; Barbara Bartmeyer; Claudia Kücherer
Journal:  J Clin Microbiol       Date:  2014-06-11       Impact factor: 5.948

8.  Lower-sensitivity and avidity modifications of the vitros anti-HIV 1+2 assay for detection of recent HIV infections and incidence estimation.

Authors:  Sheila M Keating; Debra Hanson; Mila Lebedeva; Oliver Laeyendecker; N'ko L Ali-Napo; S Michele Owen; Susan L Stramer; Richard D Moore; Philip J Norris; Michael P Busch
Journal:  J Clin Microbiol       Date:  2012-10-03       Impact factor: 5.948

9.  Immune responses in Ugandan women infected with subtypes A and D HIV using the BED capture immunoassay and an antibody avidity assay.

Authors:  Andrew F Longosz; Charles S Morrison; Pai-Lien Chen; Eric Arts; Immaculate Nankya; Robert A Salata; Veronica Franco; Thomas C Quinn; Susan H Eshleman; Oliver Laeyendecker
Journal:  J Acquir Immune Defic Syndr       Date:  2014-04-01       Impact factor: 3.731

10.  Evaluation of sequence ambiguities of the HIV-1 pol gene as a method to identify recent HIV-1 infection in transmitted drug resistance surveys.

Authors:  Emmi Andersson; Wei Shao; Irene Bontell; Fatim Cham; Do Duy Cuong; Amogne Wondwossen; Lynn Morris; Gillian Hunt; Anders Sönnerborg; Silvia Bertagnolio; Frank Maldarelli; Michael R Jordan
Journal:  Infect Genet Evol       Date:  2013-04-11       Impact factor: 3.342

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