Evidence map›Paper›PMID 37090729›Full record

ArticleFrontiers in immunology2023

H3N2 influenza hemagglutination inhibition method qualification with data driven statistical methods for human clinical trials.

Sheetal Sawant, Sarah Anne Gurley, R Glenn Overman, Angelina Sharak, Sarah V Mudrak, Thomas Oguin, Gregory D Sempowski, Marcella Sarzotti-Kelsoe, Emmanuel B Walter, Hang Xie and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 17% 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.

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

7 citing papers in PubMed, 7 citations in OpenAlex.

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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

13 authors at 4 institutions in 1 country.

Sheetal SawantCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Sarah Anne GurleyCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
R Glenn OvermanCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Angelina SharakCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Sarah V MudrakCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Thomas OguinDuke Human Vaccine Institute, Duke University, Durham, NC, United States.
Gregory D SempowskiDuke Human Vaccine Institute, Duke University, Durham, NC, United States.
Marcella Sarzotti-KelsoeCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Emmanuel B WalterDuke Human Vaccine Institute, Duke University, Durham, NC, United States.
Hang XieDivision of Viral Products, Office of Vaccines Research and Review, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, United States.
Marcela F PasettiDepartment of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, United States.
M Anthony MoodyDuke Human Vaccine Institute, Duke University, Durham, NC, United States.
Georgia D TomarasCenter for Human Systems Immunology, Department of Surgery, Duke University, Durham, NC, United States.
Duke University · USCenter for Biologics Evaluation and Research · USDuke Institute for Health Innovation · USUniversity of Maryland, Baltimore · US

Funding

Collaborative Influenza Vaccine Innovation Centers (CIVICs): Component A: Vaccine Center75N93019C00050 · NIAID · DUKE UNIVERSITY · PI MOODY, TONY · 2019 to 2025
$69.1M
Virology CoreP01AI089618 · NIAID · BOSTON CHILDREN'S HOSPITAL · PI Sarah M Valencia · 2011 to 2026
$40.0M
COLLABORATIVE INFLUENZA VACCINE INNOVATION CENTERS: CLINICAL CORE 75N93019C00054 · NIAID · DUKE UNIVERSITY · PI BERES, WENDELL · 2019 to 2025
$31.7M
Regional Biocontainment Laboratory (RBL)UC6AI058607 · NIAID · DUKE UNIVERSITY · PI WILLIAMS, R SANDERS · 2003 to 2005
$16.3M
Regional Biocontainment Laboratories Facility and Building System Upgrades SupportG20AI167200 · NIAID · DUKE UNIVERSITY · PI STAATS, HERMAN F · 2021 to 2022
$6.6M
NIAID NIH HHS 75N93019C00050NIAID NIH HHS 75N93019C00054NIAID NIH HHS G20 AI167200NIAID NIH HHS P01 AI089618NIAID NIH HHS UC6 AI058607
6 · The paper itself

Abstract

Introduction: Hemagglutination inhibition (HAI) antibody titers to seasonal influenza strains are important surrogates for vaccine-elicited protection. However, HAI assays can be variable across labs, with low sensitivity across diverse viruses due to lack of standardization. Performing qualification of these assays on a strain specific level enables the precise and accurate quantification of HAI titers. Influenza A (H3N2) continues to be a predominant circulating subtype in most countries in Europe and North America since 1968 and is thus a focus of influenza vaccine research. Methods: As a part of the National Institutes of Health (NIH)-funded Collaborative Influenza Vaccine Innovation Centers (CIVICs) program, we report on the identification of a robust assay design, rigorous statistical analysis, and complete qualification of an HAI assay using A/Texas/71/2017 as a representative H3N2 strain and guinea pig red blood cells and neuraminidase (NA) inhibitor oseltamivir to prevent NA-mediated agglutination. Results: This qualified HAI assay is precise (calculated by the geometric coefficient of variation (GCV)) for intermediate precision and intra-operator variability, accurate calculated by relative error, perfectly linear (slope of -1, R-Square 1), robust (<25% GCV) and depicts high specificity and sensitivity. This HAI method was successfully qualified for another H3N2 influenza strain A/Singapore/INFIMH-16-0019/2016, meeting all pre-specified acceptance criteria. Discussion: These results demonstrate that HAI qualification and data generation for new influenza strains can be achieved efficiently with minimal extra testing and development. We report on a qualified and adaptable influenza serology method and analysis strategy to measure quantifiable HAI titers to define correlates of vaccine mediated protection in human clinical trials.

Indexed as

Influenza, HumanInfluenza VaccinesAnimalsAntibodies, ViralGuinea PigsHemagglutinationHumansInfluenza A Virus, H3N2 SubtypeUnited StatesAntibodies, ViralInfluenza Vaccinesantibodyclinical trialsdata pipelinehemagglutination inhibition (HAI)humaninfluenzaqualificationstatistical analysis

Identifiers

PMID37090729
PMCPMC10117676
OpenAlexW4362671957

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.