Evidence map›Paper›PMID 30640216›Full record

ArticleEpidemiology (Cambridge, Mass.)2019

Estimating Human Immunodeficiency Virus (HIV) Prevention Effects in Low-incidence Settings.

Jacqueline E Rudolph, Stephen R Cole, Joseph J Eron, Angela D Kashuba, Adaora A Adimora

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. SIMULATION IN PRACTICE: THE BALANCING INTERCEPT.American journal of epidemiology · 2021
    Article
  3. Article
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

5 authors.

Jacqueline E RudolphFrom the Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Stephen R ColeFrom the Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Joseph J EronSchool of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Angela D KashubaSchool of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Adaora A AdimoraFrom the Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC.

Funding

LOC: HIV Prevention Trials NetworkUM1AI068619 · NIAID · FAMILY HEALTH INTERNATIONAL · PI MYRON Scott COHEN, Sinead Delany-Moretlwe · 2011 to 2026
$779.5M
Virology, Immunology, and Microbiology CoreP30AI050410 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DAVID M. MARGOLIS · 2001 to 2026
$76.9M
Biostatstics for Research in Environmental HealthT32ES007018 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Stephanie Engel, Rebecca Fry · 1985 to 2026
$31.3M
UNC MACS/WIHS Combined Cohort Study Clinical Research SiteU01HL146194 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael Bradley Drummond, Michelle Floris-Moore · 2019 to 2026
$23.2M
University of North Carolina Womens Interagency HIV Study UNC WIHSU01AI103390 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADIMORA, ADAORA A · 2013 to 2018
$11.0M
Structural models for treatment and exposure effects in clinical HIV cohortsR01AI100654 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COLE, STEPHEN R · 2013 to 2016
$1.6M
NHLBI NIH HHS U01 HL146194NIAID NIH HHS P30 AI050410NIAID NIH HHS R01 AI100654NIAID NIH HHS U01 AI103390NIAID NIH HHS UM1 AI068619NIEHS NIH HHS T32 ES007018
6 · The paper itself

Abstract

backgroundRandomized controlled trials (RCTs) for determining efficacy of preexposure prophylaxis (PrEP) in preventing human immunodeficiency virus (HIV) infection have not been conducted among US women because their lower HIV incidence requires impractically large studies. Results from higher-incidence settings, like Sub-Saharan Africa, may not apply to US women owing to differences in age, sexual behavior, coinfections, and adherence.

methodsWe propose a novel strategy for evaluating PrEP efficacy in the United States using data from both settings to obtain four parameters: (1) intention-to-treat (ITT) and (2) per-protocol effects in the higher-incidence setting, (3) per-protocol effect generalized to the lower-incidence setting, and (4) back-calculated ITT effect using adherence data from the lower-incidence setting. To illustrate, we simulated two RCTs comparing PrEP against placebo: one in 4000 African women and another in 500 US women. We estimated all parameters using g-computation and report risk ratios averaged over 2000 simulations, alongside the 2.5th and 97.5th percentiles of the simulation results.

resultsTwelve months after randomization, the African ITT and per-protocol risk ratios were 0.65 (0.47, 0.88) and 0.20 (0.08, 0.34), respectively. The US ITT and per-protocol risk ratios were 0.42 (0.20, 0.62) and 0.17 (0.03, 0.38), respectively. These results matched well the simulated true effects.

conclusionsOur simple demonstration informs the design of future studies seeking to estimate the effectiveness of a treatment (like PrEP) in lower-incidence settings where a traditional RCT would not be feasible. See video abstract at, http://links.lww.com/EDE/B506.

Indexed as

Pre-Exposure ProphylaxisAfrica South of the SaharaFemaleHIV InfectionsHumansIncidenceRandomized Controlled Trials as TopicTreatment OutcomeUnited States

Identifiers

PMID30640216
PMCPMC6456405

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.