Evidence map›Paper›PMID 29573142›Full record

ArticleCytometry. Part B, Clinical cytometry2018

Development of an unbiased, semi-automated approach for classifying plasma cell immunophenotype following multicolor flow cytometry of bone marrow aspirates.

Steven R Post, Ginell R Post, Dejan Nikolic, Rebecca Owens, Giovanni Insuasti-Beltran

Open access · bronzeAbstract read
In one paragraph

Article in Cytometry. Part B, Clinical cytometry, 2018. 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
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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 2 institutions in 1 country.

Steven R PostDepartment of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Ginell R PostDepartment of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Dejan NikolicDepartment of Pathology, Copper University Hospital, Camden, New Jersey.
Rebecca OwensDepartment of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Giovanni Insuasti-BeltranDepartment of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
University of Arkansas for Medical Sciences · USCooper University Hospital · US

Funding

Fibroblast-macrophage interactions induce a tumor-promoting microenvironmentR21CA185691 · NCI · UNIV OF ARKANSAS FOR MED SCIS · PI KELLY, THOMAS JOSEPH, POST, STEVEN · 2016 to 2017
$356k
NCI NIH HHS R21 CA185691
6 · The paper itself

Abstract

backgroundDespite increased usage of multiparameter flow cytometry (MFC) to assess diagnosis, prognosis, and therapeutic efficacy (minimal residual disease, MRD) in plasma cell neoplasms (PCNs), standardization of methodology and data analysis is suboptimal. We investigated the utility of using the mean and median fluorescence intensities (FI) obtained from MFC to objectively describe parameters that distinguish plasma cell (PC) phenotypes.

methodsIn this retrospective study, flow cytometry results from bone marrow aspirate specimens from 570 patients referred to the Myeloma Institute at UAMS were evaluated. Mean and median FI data were obtained from 8-color MFC of non-neoplastic, malignant, and mixed PC populations using antibodies to CD38, CD138, CD19, CD20, CD27, CD45, CD56, and CD81.

resultsOf 570 cases, 252 cases showed only non-neoplastic PCs, 168 showed only malignant PCs, and 150 showed mixed PC populations. Statistical analysis of median FI data for each CD marker showed no difference in expression intensity on non-neoplastic and malignant PCs, between pure and mixed PC populations. ROC analysis of the median FI of CD expression in non-neoplastic and malignant PCs was used to develop an algorithm to convert quantitative FI values to qualitative assessments including "negative," "positive," "dim," and "heterogeneous" expression.

conclusionsFI data derived from 8-color MFC can be used to define marker expression on PCs. Translation of FI data from Infinicyt software to an Excel worksheet streamlines workflow and eliminates transcriptional errors when generating flow reports. © 2018 International Clinical Cytometry Society.

Indexed as

AutomationColorFlow CytometryImmunophenotypingBone MarrowHumansPlasma CellsRetrospective Studiesmultiparameter flow cytometryplasma cell immunophenotypeplasma cell neoplasm

Identifiers

PMID29573142
PMCPMC6150794
OpenAlexW2790624509

What OpenQuestion holds

Textmetadata
LicenceTDM
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.