Evidence map›Paper›PMID 40129703›Full record

ArticleRisk management and healthcare policy2025

A Multiplex Bead Serology Panel For Vaccine-Preventable Diseases Using Dried Blood Spots.

Paul D Olivo, Sudip Ghatak, Randolph Rasch

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Paul D OlivoDepartment of Microbiology and Microbial Pathogenesis, Washington University Medical School, St. Louis, MO, USA.ORCID 0009-0005-8363-8468
Sudip GhatakImmunoprofile, LLC, Naples, FL, USA.
Randolph RaschCollege of Nursing, Michigan State University, East Lansing, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Vaccines are effective tools to improve public health. The effectiveness of vaccines is, however, dependent on the overall level of protection in a population. Antibodies to vaccine-related antigens are good biomarkers of protection and serosurveillance can help target vaccination programs. An integrated approach to perform serosurveillance on multiple vaccine-preventable diseases (VPDs) has been advocated and would be facilitated by a standardized multiplex immunoassay. In this report, we describe the evaluation of the performance of a multi-lyte bead-based serology panel for 12 VPDs which uses a dried blood spot sample from a finger prick ( Methods: Verification/validation studies were performed at a CLIA-certified clinical laboratory (BioAgilytix Labs, Boston, MA) on blood collected from dried blood spot (DBS) card samples from adults and children. In addition, proof-of-principle pilot serosurveillance studies were performed to demonstrate the potential of this test to identify protection gaps in adult and pediatric populations. Results: This study demonstrates that the ImmunoProfile Antibody Test System has the requisite analytical performance to be a reliable tool for determining levels of protection to VPDs. The pilot serosurveillance studies demonstrate that this test reveals gaps in protection comparable to what has been shown using immunoassays for individual antibodies using serum samples. Conclusion: Serological survey data obtained with the validated ImmunoProfile Antibody Test System could provide a wealth of information on levels of protection and could unearth vaccination gaps that may not have been anticipated.

Indexed as

antibodyprotective levelsserologyvaccine-preventable disease

Identifiers

PMID40129703
PMCPMC11932034

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LicenceCC BY-NC
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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.