Evidence map›Paper›PMID 42578828›Full record

ArticleBiometrics2026

Symmetric vaccine efficacy.

Lucy D'Agostino McGowan, Sarah C Lotspeich, Michael G Hudgens

Abstract read
In one paragraph

Article in Biometrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Lucy D'Agostino McGowanDepartment of Statistical Sciences, Wake Forest University, Winston-Salem, NC 27106, United States.ORCID 0000-0001-7297-9359
Sarah C LotspeichDepartment of Statistical Sciences, Wake Forest University, Winston-Salem, NC 27106, United States.ORCID 0000-0001-5380-2427
Michael G HudgensDepartment of Biostatistics University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.

Funding

Statistical Methods in HIV Vaccine Efficacy TrialsR37AI054165 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert · 2010 to 2026
$6.7M
National Institute of Allergy and Infectious DiseasesNIAID NIH HHS R37 AI054165NIH HHS R37 AI054165
6 · The paper itself

Abstract

Traditional measures of vaccine efficacy (VE) are inherently asymmetric, constrained above by 1 but unbounded below. As a result, VE estimates and corresponding confidence intervals (CIs) can extend far below zero, making interpretation difficult and potentially obscuring whether the apparent effect reflects true harm or simply statistical uncertainty. The proposed symmetric vaccine efficacy (SVE) is a bounded and interpretable alternative to VE that maintains desirable statistical properties while resolving these asymmetries. SVE is defined as a symmetric transformation of infection risks, with possible values within $[-1, 1]$, providing a common scale for both beneficial and harmful vaccine effects. This paper describes the relationship between SVE and traditional VE, considers inference about SVE, and illustrates the utility of the proposed measure by reanalyzing data from a randomized trial of a candidate HIV vaccine. Open-source tools for computing estimates of SVE and corresponding CIs are available in R through the sve package.

Indexed as

Models, StatisticalVaccine EfficacyAIDS VaccinesBiometryComputer SimulationHIV InfectionsHumansRandomized Controlled Trials as TopicVaccinationVaccinesAIDS VaccinesVaccinescommunicationinfectious diseasepublic healthrelative risksymmetric metricsvaccination

Identifiers

PMID42578828
PMCPMC13459110

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.