Evidence map›Paper›PMID 31809340›Full record

ArticleEpidemiology (Cambridge, Mass.)2020

Assessment of Bias in Estimates of Sexual Network Degree using Prospective Cohort Data.

Stephen Uong, Eli S Rosenberg, Steven M Goodreau, Nicole Luisi, Patrick Sullivan, Samuel M Jenness

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
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  3. Article
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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

6 authors.

Stephen UongFrom the Department of Epidemiology, Emory University, Atlanta, GA, USA.
Eli S RosenbergDepartment of Epidemiology and Biostatistics, University at Albany School of Public Health, SUNY, Albany, NY, USA.
Steven M GoodreauDepartment of Anthropology, University of Washington, Seattle, WA, USA.
Nicole LuisiFrom the Department of Epidemiology, Emory University, Atlanta, GA, USA.
Patrick SullivanFrom the Department of Epidemiology, Emory University, Atlanta, GA, USA.
Samuel M JennessFrom the Department of Epidemiology, Emory University, Atlanta, GA, USA.

Funding

Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Carlos del Rio · 2002 to 2026
$74.0M
EpiModel 2.0: Integrated Network Models for HIV/STI Prevention ScienceR01AI138783 · NIAID · EMORY UNIVERSITY · PI JENNESS, SAMUEL · 2018 to 2021
$3.0M
Explaining Differences in HIV Prevalence and Incidence in Black and White MSMR01MH085600 · NIMH · EMORY UNIVERSITY · PI SULLIVAN, PATRICK SEAN · 2009 to 2013
$2.9M
Modeling Antiretroviral-Based Prevention among MSM in the USR21MH112449 · NIMH · EMORY UNIVERSITY · PI JENNESS, SAMUEL · 2017 to 2018
$442k
Using Sexual Network Transmission Models to Explain HIV Disparities Between BlackR21HD075662 · NICHD · UNIVERSITY OF WASHINGTON · PI GOODREAU, STEVEN M. · 2013 to 2014
$418k
NIAID NIH HHS P30 AI050409NIAID NIH HHS R01 AI138783NICHD NIH HHS R21 HD075662NIMH NIH HHS R01 MH085600NIMH NIH HHS R21 MH112449
6 · The paper itself

Abstract

backgroundSexual network degree, a count of ongoing partnerships, plays a critical role in the transmission dynamics of human immunodeficiency virus and other sexually transmitted infections. Researchers often quantify degree using self-reported cross-sectional data on the day of survey, which may result in bias because of uncertainty about future sexual activity.

methodsWe evaluated the bias of a cross-sectional degree measure with a prospective cohort study of men who have sex with men (MSM). At baseline, we asked men about whether recent sexual partnerships were ongoing. We confirmed the true, ongoing status of those partnerships at baseline at follow-up. With logistic regression, we estimated the partnership-level predictors of baseline measure accuracy. With Poisson regression, we estimated the longitudinally confirmed degree as a function of baseline predicted degree.

resultsAcross partnership types, the baseline ongoing status measure was 70% accurate, with higher negative predictive value (91%) than positive predictive value (39%). Partnership exclusivity and racial pairing were associated with higher accuracy. Baseline degree generally overestimated confirmed degree. Bias, or number of ongoing partners different than predicted at baseline, was -0.28 overall, ranging from -1.91 to -0.41 for MSM with any ongoing partnerships at baseline. Comparing MSM of the same baseline degree, the level of bias was stronger for black compared with white MSM, and for younger compared with older MSM.

conclusionsResearch studies may overestimate degree when it is quantified cross-sectionally. Adjustment and structured sensitivity analyses may account for bias in studies of human immunodeficiency virus or sexually transmitted infection prevention interventions.

Indexed as

BiasHomosexuality, MaleSexual PartnersAdolescentAdultCross-Sectional StudiesHIV InfectionsHumansMaleProspective StudiesSexually Transmitted DiseasesYoung Adult

Identifiers

PMID31809340
PMCPMC7002246

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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.