Evidence map›Paper›PMID 35080038›Full record

ArticleStatistics in medicine2022

Combining information to estimate adherence in studies of pre-exposure prophylaxis for HIV prevention: Application to HPTN 067.

James P Hughes, Brian D Williamson, Chloe Krakauer, Gordon Chau, Brayan Ortiz, Jon Wakefield, Craig Hendrix, K Rivet Amico, Timothy H Holtz, Linda-Gail Bekker and 1 more

Abstract read
In one paragraph

Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
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

11 authors.

James P HughesDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.ORCID 0000-0001-5034-3157
Brian D WilliamsonVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.ORCID 0000-0002-7024-548X
Chloe KrakauerDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.
Gordon ChauVaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Brayan OrtizModeling and Optimization, Amazon, Bellevue, Washington, USA.
Jon WakefieldDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.
Craig HendrixSchool of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
K Rivet AmicoSchool of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Timothy H HoltzDivision of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Linda-Gail BekkerThe Desmond Tutu HIV Centre, University of Cape Town, Cape Town, South Africa.
Robert GrantGladstone Institutes, University of California, San Francisco, San Francisco, California, USA.

Funding

LOC: HIV Prevention Trials NetworkUM1AI068619 · NIAID · FAMILY HEALTH INTERNATIONAL · PI Sinead Delany-Moretlwe, RAPHAEL J LANDOVITZ · 2011 to 2026
$779.5M
SDMC: HPTN 084 Pregnancy SupplementUM1AI068617 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Elizabeth Renata Brown, Deborah J Donnell · 2011 to 2026
$204.9M
LC: HIV Prevention Trials Network - Laboratory Support for the SARS-CoV-2 Seroprevalence Study (CoVPN 5002)UM1AI068613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SUSAN H ESHLEMAN, Mark A Marzinke · 2011 to 2026
$100.2M
Emory HIV/AIDS Clinical Trials UnitUM1AI069418 · NIAID · EMORY UNIVERSITY · PI Moises Arturo Huaman Joo, Colleen F Kelley · 2012 to 2026
$46.0M
Neuro HPA Project 1U54AG062334 · NIA · EMORY UNIVERSITY · PI Cecile Delille Lahiri, Vasiliki Michopoulos · 2018 to 2026
$12.2M
STATISTICAL ISSUES IN AIDS RESEARCHR37AI029168 · NIAID · UNIVERSITY OF WASHINGTON · PI JAMES P HUGHES · 1999 to 2026
$9.8M
STATISTICAL ISSUES IN AIDS RESEARCHR01AI029168 · NIAID · UNIVERSITY OF WASHINGTON · PI HUGHES, JAMES P · 1989 to 2018
$5.3M
NIAID NIH HHS R01 AI029168NIAID NIH HHS R37 AI029168NIAID NIH HHS UM1 AI068613NIAID NIH HHS UM1 AI068617NIAID NIH HHS UM1 AI068619NIAID NIH HHS UM1 AI069418NIA NIH HHS U54 AG062334
6 · The paper itself

Abstract

In trials of oral HIV pre-exposure prophylaxis (PrEP), multiple approaches have been used to measure adherence, including self-report, pill counts, electronic dose monitoring devices, and biological measures such as drug levels in plasma, peripheral blood mononuclear cells, hair, and/or dried blood spots. No one of these measures is ideal and each has strengths and weaknesses. However, accurate estimates of adherence to oral PrEP are important as drug efficacy is closely tied to adherence, and secondary analyses of trial data within identified adherent/non-adherent subgroups may yield important insights into real-world drug effectiveness. We develop a statistical approach to combining multiple measures of adherence and show in simulated data that the proposed method provides a more accurate measure of true adherence than self-report. We then apply the method to estimate adherence in the ADAPT study (HPTN 067) in South African women.

Indexed as

Anti-HIV AgentsHIV InfectionsPre-Exposure ProphylaxisFemaleHumansLeukocytes, MononuclearMedication AdherenceAnti-HIV AgentsadherenceHIVlatent variablepharmacokinetic modelpre-exposure prophylaxis

Identifiers

PMID35080038
PMCPMC8881405

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.