Evidence map›Paper›PMID 26869051›Full record

ArticleStatistics in medicine2016

Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model.

Rebecca Yates Coley, Elizabeth R Brown

Abstract read
In one paragraph

Article in Statistics in medicine, 2016. 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. 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

2 authors.

Rebecca Yates ColeyDepartment of Biostatistics, University of Washington, Seattle, WA, U.S.A.
Elizabeth R BrownDepartment of Biostatistics, University of Washington, Seattle, WA, U.S.A.

Funding

Statistical and Data Management Center (SDMC): Microbicide Trials NetworkUM1AI068615 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BROWN, ELIZABETH RENATA · 2011 to 2021
$66.5M
NIAID NIH HHS UM1 AI068615
6 · The paper itself

Abstract

Inconsistent results in recent HIV prevention trials of pre-exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population-level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood-based Bayesian hierarchical model that estimates the individual-level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson-distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. Copyright © 2016 John Wiley & Sons, Ltd.

Indexed as

Bayes TheoremLikelihood FunctionsFrailtyHIV InfectionsHumansResearch DesignBayesian analysisdata augmentationheterogeneitylatent variablesurvival analyisis

Identifiers

PMID26869051
PMCPMC5039019

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.