Evidence map›Paper›PMID 28124579›Full record

ArticleClinical trials (London, England)2017

Using a network-based approach and targeted maximum likelihood estimation to evaluate the effect of adding pre-exposure prophylaxis to an ongoing test-and-treat trial.

Laura Balzer, Patrick Staples, Jukka-Pekka Onnela, Victor DeGruttola

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in Clinical trials (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01864603 (Sustainable East Africa Research in Community Health), which is not on this map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 43% 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.

NCT01864603 nacompletednot on this map

Sustainable East Africa Research in Community Health

TypeinterventionalSponsorUniversity of California, San FranciscoRan2013 to 2021Enrolled150,395ConditionsHIV, Tuberculosis, Hypertension, DiabetesArmsUniversal ART in a streamlined care model, Annual Community Health Campaigns, Targeted PrEP and Targeted testing interventions, Baseline community-based HIV and multi-disease testing
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025
    Pooled it
  2. Article
  3. Article
  4. 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

4 authors at 1 institution in 1 country.

Laura BalzerDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Patrick StaplesDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Jukka-Pekka OnnelaDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Victor DeGruttolaDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Harvard University · US

Funding

BIOSTATISTICS/EPIDEMIOLOGY TRAINING GRANTS IN AIDST32AI007358 · NIAID · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Michael David Hughes · 1989 to 2026
$12.4M
GRADUATE TRAINING IN BIOSTATISTICST32ES007142 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Brent Andrew Coull · 1985 to 2026
$11.9M
Methods to Advance the HIV Prevention Research AgendaR37AI051164 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI DEGRUTTOLA, VICTOR GERARD · 2012 to 2019
$3.3M
NIAID NIH HHS R37 AI051164NIAID NIH HHS T32 AI007358NIEHS NIH HHS T32 ES007142
6 · The paper itself

Abstract

backgroundSeveral cluster-randomized trials are underway to investigate the implementation and effectiveness of a universal test-and-treat strategy on the HIV epidemic in sub-Saharan Africa. We consider nesting studies of pre-exposure prophylaxis within these trials. Pre-exposure prophylaxis is a general strategy where high-risk HIV- persons take antiretrovirals daily to reduce their risk of infection from exposure to HIV. We address how to target pre-exposure prophylaxis to high-risk groups and how to maximize power to detect the individual and combined effects of universal test-and-treat and pre-exposure prophylaxis strategies.

methodsWe simulated 1000 trials, each consisting of 32 villages with 200 individuals per village. At baseline, we randomized the universal test-and-treat strategy. Then, after 3 years of follow-up, we considered four strategies for targeting pre-exposure prophylaxis: (1) all HIV- individuals who self-identify as high risk, (2) all HIV- individuals who are identified by their HIV+ partner (serodiscordant couples), (3) highly connected HIV- individuals, and (4) the HIV- contacts of a newly diagnosed HIV+ individual (a ring-based strategy). We explored two possible trial designs, and all villages were followed for a total of 7 years. For each village in a trial, we used a stochastic block model to generate bipartite (male-female) networks and simulated an agent-based epidemic process on these networks. We estimated the individual and combined intervention effects with a novel targeted maximum likelihood estimator, which used cross-validation to data-adaptively select from a pre-specified library the candidate estimator that maximized the efficiency of the analysis.

resultsThe universal test-and-treat strategy reduced the 3-year cumulative HIV incidence by 4.0% on average. The impact of each pre-exposure prophylaxis strategy on the 4-year cumulative HIV incidence varied by the coverage of the universal test-and-treat strategy with lower coverage resulting in a larger impact of pre-exposure prophylaxis. Offering pre-exposure prophylaxis to serodiscordant couples resulted in the largest reductions in HIV incidence (2% reduction), and the ring-based strategy had little impact (0% reduction). The joint effect was larger than either individual effect with reductions in the 7-year incidence ranging from 4.5% to 8.8%. Targeted maximum likelihood estimation, data-adaptively adjusting for baseline covariates, substantially improved power over the unadjusted analysis, while maintaining nominal confidence interval coverage.

conclusionOur simulation study suggests that nesting a pre-exposure prophylaxis study within an ongoing trial can lead to combined intervention effects greater than those of universal test-and-treat alone and can provide information about the efficacy of pre-exposure prophylaxis in the presence of high coverage of treatment for HIV+ persons.

Indexed as

Pre-Exposure ProphylaxisAfrica South of the SaharaAnti-HIV AgentsComputer SimulationFemaleHIV InfectionsHumansLikelihood FunctionsMaleMass ScreeningRandomized Controlled Trials as TopicResearch DesignRisk AssessmentAnti-HIV AgentsAdaptive pre-specificationcluster-randomized trialsHIVnetworkspre-exposure prophylaxistargeted maximum likelihood estimation

Identifiers

PMID28124579
PMCPMC5377920
OpenAlexW2582401314

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Registered trials

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.