Evidence map›Paper›PMID 31413172›Full record

ArticlemSphere2019

Field Test and Validation of the Multiplier Measles, Mumps, Rubella, and Varicella-Zoster Multiplexed Assay System in the Democratic Republic of the Congo by Using Dried Blood Spots.

Stephen G Higgins, Nicole A Hoff, Adva Gadoth, Andrew Fusellier, Patrick Mukadi, Vivian Alfonso, Christina Randall, Hayley Ashbaugh, Melanie Poncheri, Reena H Doshi and 7 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in mSphere, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 9 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

17 authors at 4 institutions in 2 countries.

Stephen G Higgins *Dynex Technologies Inc., Chantilly, Virginia, USA shhiggins@yahoo.com nhoff84@ucla.edu.
Nicole A Hoff *Department of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA shhiggins@yahoo.com nhoff84@ucla.edu.
Adva GadothDepartment of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA.
Andrew FusellierDynex Technologies Inc., Chantilly, Virginia, USA.
Patrick MukadiNational Institute of Biomedical Research (INRB), Kinshasa, Democratic Republic of the Congo.
Vivian AlfonsoDepartment of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA.
Christina RandallDynex Technologies Inc., Chantilly, Virginia, USA.
Hayley AshbaughDepartment of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA.
Melanie PoncheriDynex Technologies Inc., Chantilly, Virginia, USA.
Reena H DoshiDepartment of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA.
Sue GerberBill and Melinda Gates Foundation, Seattle, Washington, USA.
Roger BuddDynex Technologies Inc., Chantilly, Virginia, USA.
Robert WolfertDynex Technologies Inc., Chantilly, Virginia, USA.
Russell WilliamsUCLA-DRC Research Program, Kinshasa, Democratic Republic of the Congo.
Emile Okitolonda-WemakoyKinshasa School of Public Health, University of Kinshasa, Kinshasa, Democratic Republic of the Congo.
Jean-Jacque Muyembe-TamfumNational Institute of Biomedical Research (INRB), Kinshasa, Democratic Republic of the Congo.
Anne W RimoinDepartment of Epidemiology, University of California, Los Angeles, Fielding School of Public Health, Los Angeles, California, USA.
University of California, Los Angeles · USNational Institute of Biomedical Research · CDBill & Melinda Gates Foundation · USUniversity of Kinshasa · CD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here we describe baseline validation studies and field performance of a research-use-only chemiluminescent multiplex serology panel for measles, mumps, rubella, and varicella-zoster virus used with dried blood spots in support of the 2013-2014 Democratic Republic of the Congo Demographic and Health Survey. Characterization of the panel using U.S. FDA-cleared commercial kits shows good concordance for measles, mumps, rubella, and varicella-zoster with average sensitivity across assays of 94.9% and an average specificity of 91.4%. As expected, performance versus available standards validated for plaque-reduction assays does not provide a 1:1 correspondence with international units and yet demonstrates excellent linearity (average Hill's slope = 1.02) and ∼4 logs of dynamic range. In addition, for the four assays, the multiplexed format allowed for inclusion of three positive and two negative controls for each sample. A prototype Dynex Multiplier chemiluminescent automated immunoassay instrument with a charge-coupled device camera provided a rugged and robust processing and data acquisition platform. Performance of a multiplex instrument for serological testing in a substantially resource-limited environment shows excellent reproducibility, minimal cross-reactivity, and a clear discrimination between specific assays and should be considered a viable option for future serosurveys.

Indexed as

Antibodies, ViralAutomation, LaboratoryChickenpoxDemocratic Republic of the CongoDried Blood Spot TestingHumansImmunoassayLuminescent MeasurementsMeaslesMumpsReproducibility of ResultsRubellaSensitivity and SpecificityAntibodies, Viralassay validationDemocratic Republic of the CongoMMRVmultiplex assay

Identifiers

PMID31413172
PMCPMC6695516
OpenAlexW2967801573

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.