Evidence map›Paper›PMID 34679541›Full record

ArticleDiagnostics (Basel, Switzerland)2021

Spectrum Bias and Individual Strengths of SARS-CoV-2 Serological Tests-A Population-Based Evaluation.

Sebastian Einhauser, David Peterhoff, Hans Helmut Niller, Stephanie Beileke, Felix Günther, Philipp Steininger, Ralph Burkhardt, Iris M Heid, Annette B Pfahlberg, Klaus Überla and 2 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

15 citing papers in PubMed, 18 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

12 authors at 5 institutions in 1 country.

Sebastian EinhauserInstitute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.ORCID 0000-0003-4177-4451
David PeterhoffInstitute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.ORCID 0000-0001-5911-6233
Hans Helmut NillerInstitute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.
Stephanie BeilekeInstitute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany.
Felix GüntherDepartment of Statistics, Statistical Consulting Unit StaBLab, LMU Munich, Geschwister-Scholl-Platz 1, 80539 Munich, Germany.
Philipp SteiningerInstitute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany.
Ralph BurkhardtInstitute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.
Iris M HeidDepartment of Genetic Epidemiology, University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.
Annette B PfahlbergDepartment of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Waldstr. 6, 91054 Erlangen, Germany.ORCID 0000-0002-2234-1215
Klaus ÜberlaInstitute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Schlossgarten 4, 91054 Erlangen, Germany.ORCID 0000-0001-7822-3835
Olaf GefellerDepartment of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Waldstr. 6, 91054 Erlangen, Germany.ORCID 0000-0002-8985-7582
Ralf WagnerInstitute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg, Franz-Josef-Strauß-Allee 11, 93053 Regensburg, Germany.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversity Hospital Regensburg · DEInstitute of Medical Microbiology and Hygiene · DEStatistisches Bundesamt · DEUniversity of Regensburg · DE

Funding

Bavarian States Ministry of Science and Arts no grant numberNational Research Network of the University Medicine 497 (NUM; applied surveillance and testing; B-FAST) no grant number
6 · The paper itself

Abstract

Antibody testing for determining the SARS-CoV-2 serostatus was rapidly introduced in early 2020 and since then has been gaining special emphasis regarding correlates of protection. With limited access to representative samples with known SARS-CoV-2 infection status during the initial period of test development and validation, spectrum bias has to be considered when moving from a "test establishment setting" to population-based settings, in which antibody testing is currently implemented. To provide insights into the presence and magnitude of spectrum bias and to estimate performance measures of antibody testing in a population-based environment, we compared SARS-CoV-2 neutralization to a battery of serological tests and latent class analyses (LCA) in a subgroup (

Indexed as

ECLIAELISAneutralizationSARS-CoV-2sensitivityserologyspecificityspectrum biastest accuracy

Identifiers

PMID34679541
PMCPMC8534748
OpenAlexW3204690099

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.