Evidence map›Paper›PMID 36962730›Full record

ArticlePLOS global public health2022

Adherence monitoring methods to measure virological failure in people living with HIV on long-term antiretroviral therapy in Uganda.

Stephen Okoboi, Joseph Musaazi, Rachel King, Sheri A Lippman, Andrew Kambugu, Andrew Mujugira, Jonathan Izudi, Rosalind Parkes-Ratanshi, Agnes N Kiragga, Barbara Castelnuovo

Open access · goldFull text read
In one paragraph

Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 21% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Review
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

10 authors at 3 institutions in 3 countries.

Stephen OkoboiInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.ORCID https://orcid.org/0000-0002-8738-0397
Joseph MusaaziInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Rachel KingDepartment of Global Health, University of California, San Francisco, San Francisco, CA, United States of America.
Sheri A LippmanDepartment of Medicine, Division of Prevention Science, University of California, San Francisco, San Francisco, CA, United States of America.ORCID https://orcid.org/0000-0003-3152-9372
Andrew KambuguInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Andrew MujugiraInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Jonathan IzudiInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Rosalind Parkes-RatanshiInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Agnes N KiraggaInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Barbara CastelnuovoInfectious Diseases Institute, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Infectious Diseases Institute · UGUniversity of California, San Francisco · USUniversity of Cambridge · GB

Funding

Ujima Mentoring ProgramP30MH062246 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MALLORY O JOHNSON · 2001 to 2026
$57.4M
University of California Launching Future Leaders in Global Health Research Training ProgramD43TW009343 · FIC · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CRAIG R COHEN, Sung-Jae Lee · 2017 to 2026
$14.7M
HIV Co-infections in Uganda: TB, Cryptococcus, and Viral Hepatitis.D43TW009771 · FIC · JOHNS HOPKINS UNIVERSITY · PI CASTELNUOVO, BARBARA, KAMBUGU, ANDREW DDUNGU · 2014 to 2023
$3.3M
FIC NIH HHS D43 TW009343FIC NIH HHS D43 TW009771NIMH NIH HHS P30 MH062246
6 · The paper itself

Abstract

Appointment keeping and self-report within 7-day or and 30-days recall periods are non-objective measures of antiretroviral treatment (ART) adherence. We assessed incidence of virological failure (VF), predictive performance and associations of these adherence measures with VF among adults on long-term ART. Data for persons initiated on ART between April 2004 and April 2005, enrolled in a long-term ART cohort at 10-years on ART (baseline) and followed until December 2021 was analyzed. VF was defined as two consecutives viral loads ≥1000 copies/ml at least within 3-months after enhanced adherence counselling. We estimated VF incidence using Kaplan-Meier and Cox-proportional hazards regression for associations between each adherence measure (analyzed as time-dependent annual values) and VF. The predictive performance of appointment keeping and self-reporting for identifying VF was assessed using receiver operating characteristic curves and reported as area under the curve (AUC). We included 900 of 1,000 participants without VF at baseline: median age was 47 years (Interquartile range: 41-51), 60% were women and 88% were virally suppressed. ART adherence was ≥95% for all three adherence measures. Twenty-one VF cases were observed with an incidence rate of 4.37 per 1000 person-years and incidence risk of 2.4% (95% CI: 1.6%-3.7%) over the 5-years of follow-up. Only 30-day self-report measure was associated with lower risk of VF, adjusted hazard ratio (aHR) = 0.14, 95% CI:0.05-0.37). Baseline CD4 count ≥200cells/ml was associated with lower VF for all adherence measures. The 30-day self-report measure demonstrated the highest predictive performance for VF (AUC = 0.751) compared to appointment keeping (AUC = 0.674), and 7-day self-report (AUC = 0.687). The incidence of virological failure in this study cohort was low. Whilst 30- day self-report was predictive, appointment keeping and 7-day self-reported adherence measures had low predictive performance in identifying VF. Viral load monitoring remains the gold standard for adherence monitoring and confirming HIV treatment response.

Identifiers

PMID36962730
PMCPMC10021796
OpenAlexW4313308148

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read89
identifiers read7
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.