Evidence map›Paper›PMID 29090394›Full record

ArticleAIDS and behavior2018

Utility of Different Adherence Measures for PrEP: Patterns and Incremental Value.

Andrew Abaasa, Craig Hendrix, Monica Gandhi, Peter Anderson, Anatoli Kamali, Freddie Kibengo, Eduard J Sanders, Gaudensia Mutua, Namandjé N Bumpus, Frances Priddy and 1 more

Abstract read
In one paragraph

Article in AIDS and behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

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

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  10. A Cross-Biomeasure Study to Optimize Antiretroviral Adherence Estimation.Journal of acquired immune deficiency syndromes (1999) · 2025
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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.

Andrew AbaasaMRC/UVRI Uganda Research Unit on AIDS, P.O Box 49, Entebbe, Uganda. Andrew.Abaasa@mrcuganda.org.
Craig HendrixDivision of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, ME, USA.
Monica GandhiDivisions of HIV, Infectious Diseases and Global Medicine, Department of Medicine, University of California, San Francisco, CA, USA.
Peter AndersonDepartment of Pharmaceutical Sciences, University of Colorado, Aurora, CO, USA.
Anatoli KamaliInternational AIDS Vaccine Initiative, New York, NY, USA.
Freddie KibengoMRC/UVRI Uganda Research Unit on AIDS, P.O Box 49, Entebbe, Uganda.
Eduard J SandersKenya Medical Research Institute, University of Oxford, Kilifi, Kenya.
Gaudensia MutuaKenya AIDS Vaccine Initiative, University of Nairobi, Nairobi, Kenya.
Namandjé N BumpusDivision of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, ME, USA.
Frances PriddyInternational AIDS Vaccine Initiative, New York, NY, USA.
Jessica E HabererMassachusetts General Hospital Global Health and Harvard Medical School, Boston, MA, USA.

Funding

Virology CoreP30AI027763 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEVEN Grant DEEKS · 1988 to 2026
$93.6M
Plugging Hair ARV Levels as Adherence Biomarkers into HIV Prevention TrialsR01AI098472 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GANDHI, MONICA · 2012 to 2021
$5.6M
“Hair Lengthening”: Using Hair Levels to Interpret Long-Acting PrEP Studies.R37AI098472 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Monica Gandhi · 2023 to 2026
$3.2M
NIAID NIH HHS P30 AI027763NIAID NIH HHS R01 AI098472NIAID NIH HHS R37 AI098472
6 · The paper itself

Abstract

Measuring PrEP adherence remains challenging. In 2009-2010, the International AIDS Vaccine Initiative randomized phase II trial participants to daily tenofovir disoproxil fumarate/emtricitabine or placebo in Uganda and Kenya. Adherence was measured by electronic monitoring (EM), self-report (SR), and drug concentrations in plasma and hair. Each adherence measure was categorised as low, moderate, or high and also considered continuously; the incremental value of combining measures was determined. Forty-five participants were followed over 4 months. Discrimination for EM adherence by area under receiver operating curves (AROC) was poor for SR (0.53) and best for hair (AROC 0.85). When combining hair with plasma or hair with self-report, discrimination was improved (AROC > 0.9). Self-reported adherence was of low utility by itself. Hair level was the single best PK measure to predict EM-assessed adherence; the other measurements had lower discrimination values. Combining short-term (plasma) and long-term (hair) metrics could be useful to assess patterns of drug-taking in the context of PrEP.

Indexed as

Medication AdherenceSelf ReportAdministration, OralAdultAnti-HIV AgentsEmtricitabineFemaleHairHIV InfectionsHumansKenyaMalePre-Exposure ProphylaxisTenofovirUgandaAnti-HIV AgentsEmtricitabineTenofovirHairPlasmaPrEP drug-taking patterns of adherence electronic monitoring

Identifiers

PMID29090394
PMCPMC5878836

What OpenQuestion holds

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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.