Evidence map›Paper›PMID 29890944›Full record

ArticleBMC cancer2018

Detection of intracellular IgD using flow cytometry could be a novel and supplementary method to diagnose IgD multiple myeloma.

Wei Wang, Chun-Xia Zhang, Zhen-Ling Li, Ming Gong, Yi-Gai Ma

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2018. 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
0.2field-weighted citation impact, top 48% 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, 6 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

5 authors at 1 institution in 1 country.

Wei WangHematology Department, China-Japan Friendship Hospital, Ying-Hua-Yuan East Street, No. 2, Beijing, 100029, China.
Chun-Xia ZhangHematology Department, China-Japan Friendship Hospital, Ying-Hua-Yuan East Street, No. 2, Beijing, 100029, China.
Zhen-Ling LiHematology Department, China-Japan Friendship Hospital, Ying-Hua-Yuan East Street, No. 2, Beijing, 100029, China.
Ming GongHematology Department, China-Japan Friendship Hospital, Ying-Hua-Yuan East Street, No. 2, Beijing, 100029, China.
Yi-Gai MaHematology Department, China-Japan Friendship Hospital, Ying-Hua-Yuan East Street, No. 2, Beijing, 100029, China. dr_myg@163.com.
China-Japan Friendship Hospital · CN

Funding

National Natural Science Foundation of China 81300450
6 · The paper itself

Abstract

backgroundWe examined whether detecting the heavy chain of cytoplasmic immunoglobulin D (IgD) by flow cytometry could be used as a supplemental method to diagnose IgD multiple myeloma (MM).

methodsBone marrow (BM) samples of thirty-five patients with MM were collected. Five of them were IgD MM, the rest of thirty were other subtypes of MM. Antibodies to four types of heavy chains of immunoglobulin (e.g., IgA, IgG, IgM, and IgD) were analyzed by flow cytometry in each patient's BM sample.

resultsThe five IgD MM patients were all positive for cytoplasmic IgD. The percentage of IgD positive MM cells among nucleated cells varied from 0.4 to 12.9%. Cytoplasmic IgG was positive in eight patients with IgG MM (n = 9); cytoplasmic IgA was positive in all patients with IgA MM (n = 10); cytoplasmic IgM was positive in one patient with IgM MM (n = 1). No heavy chain was detected in light chain MM (n = 9) and non-secretory subtype (n = 1).

conclusionsDetection of cytoplasmic IgD by flow cytometry is a convenient, sensitive and supplemental method to diagnose IgD MM.

Indexed as

AgedAged, 80 and overCytoplasmFemaleFlow CytometryHumansImmunoglobulin DImmunoglobulin Heavy ChainsMaleMiddle AgedMultiple MyelomaImmunoglobulin DImmunoglobulin Heavy ChainsCytoplasmic IgDDiagnosisFlow cytometryIgDMultiple myeloma

Identifiers

PMID29890944
PMCPMC5996556
OpenAlexW2807990694

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.