Evidence map›Paper›PMID 31205481›Full record

ArticleComputational and mathematical methods in medicine2019

Continuous Readout versus Titer-Based Assays of Influenza Vaccine Trials: Sensitivity, Specificity, and False Discovery Rates.

Dongmei Li, Jiong Wang, Jessica Garigen, John J Treanor, Martin S Zand

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
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

5 authors at 1 institution in 1 country.

Dongmei Li *Informatics Core, Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY, USA.ORCID 0000-0001-9140-2483
Jiong Wang *Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY, USA.ORCID 0000-0002-4938-5074
Jessica GarigenDepartment of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY, USA.
John J TreanorDepartment of Medicine, Division of Infectious Diseases, University of Rochester Medical Center, Rochester, NY, USA.
Martin S ZandInformatics Core, Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY, USA.ORCID 0000-0002-7095-8682
University of Rochester Medical Center · US

Funding

The University of Rochester's Clinical and Translational Science InstituteUL1TR002001 · NCATS · UNIVERSITY OF ROCHESTER · PI WILSON, KAREN M., ZAND, MARTIN S · 2016 to 2024
$34.6M
Modeling B Cell Vaccine Responses in Transplant RecipientsR01AI069351 · NIAID · UNIVERSITY OF ROCHESTER · PI HYRIEN, OLLIVIER, ZAND, MARTIN S · 2007 to 2016
$3.7M
Modeling Mechanisms of Adjuvanted Influenza Vaccine Induced IgG Repertoire Diversity and Heterosubtypic ImmunityR01AI129518 · NIAID · UNIVERSITY OF ROCHESTER · PI HYRIEN, OLLIVIER, ZAND, MARTIN S · 2017 to 2021
$3.5M
Modeling Immune Desensitization in Renal TransplantationR01AI098112 · NIAID · UNIVERSITY OF ROCHESTER · PI ZAND, MARTIN S · 2012 to 2016
$1.9M
Predictive Modeling of Multidimensional Anti-Influenza IgG RepertoiresR21AI138500 · NIAID · UNIVERSITY OF ROCHESTER · PI ZAND, MARTIN S · 2018 to 2019
$424k
NCATS NIH HHS UL1 TR002001NIAID NIH HHS HHSN266200700008CNIAID NIH HHS R01 AI069351NIAID NIH HHS R01 AI098112NIAID NIH HHS R01 AI129518NIAID NIH HHS R21 AI138500
6 · The paper itself

Abstract

The current gold standard for measuring antibody-based immunity to influenza viruses relies on the hemagglutinin inhibition assay (HAI), an 80-year-old technology, and the microneutralization assay (MN). Both assays use serial dilution to provide a discrete, ranked readout of 8-14 categorical titer values for each sample. In contrast to other methods of measuring vaccine antibody levels that produce a continuous readout (i.e., mPLEX-Flu and ELISA), titering methods introduce imprecision and increase false discovery rates (FDR). In this paper, we assess the degree of such statistical errors, first with simulation studies comparing continuous data with titer data in influenza vaccine study group comparison analyses and then by analyzing actual sample data from an influenza vaccine trial. Our results show the superiority of using continuous, rather than discrete, readout assays. Compared to continuous readout assays, titering assays have a lower statistical precision and a higher FDR. The results suggested that traditional titering assays could lead to increased Type-II errors in the comparison of different therapeutic arms of an influenza vaccine trial. These statistical issues are related to the mathematical nature of titer-based assays, which we examine in detail in the simulation studies. Continuous readout assays are free of this issue, and thus it is possible that comparisons of study groups could provide different results with these two methods as we have shown in our case study.

Indexed as

AlgorithmsClinical Trials as TopicComputer SimulationEnzyme-Linked Immunosorbent AssayFalse Positive ReactionsHemagglutinin Glycoproteins, Influenza VirusHumansInfluenza, HumanInfluenza VaccinesModels, StatisticalNeutralization TestsRegression AnalysisReproducibility of ResultsResearch DesignSensitivity and SpecificityVaccinationHemagglutinin Glycoproteins, Influenza Virushemagglutinin, human influenza A virusInfluenza Vaccines

Identifiers

PMID31205481
PMCPMC6530215
OpenAlexW2944584222

What OpenQuestion holds

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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.