Evidence map›Paper›PMID 27683427›Full record

ArticleEJIFCC2013

Prediction of Therapy Response and Prognosis in Leukemias by Flow Cytometric MDR Assays.

János Kappelmayer, Zsuzsa Hevessy, András Apjok, Katalin Tauberné Jakab

Open access · greenAbstract read
In one paragraph

Article in EJIFCC, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 72% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

János KappelmayerDepartment of Laboratory Medicine, Medical and Health Science Center, University of Debrecen , Hungary.
Zsuzsa HevessyDepartment of Laboratory Medicine, Medical and Health Science Center, University of Debrecen , Hungary.
András ApjokSolvo Biotechnology , Szeged, Hungary.
Katalin Tauberné JakabSolvo Biotechnology , Szeged, Hungary.
University of Debrecen · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multidrug resistance (MDR) is an unwanted phenomenon, that may cause therapy failure in several neoplasms including hematological malignancies. The purpose of any type of laboratory MDR assay is to reliably identify such patients and to provide useful data to clinicians with a relatively short turnaround time. MDR can be multicausal and several previous data identified a group of transmembrane proteins - the ATP-binding casette (ABC) proteins - that may be involved in MDR in various hematological malignancies. The prototype of these proteins is the P-glycoprotein (Pgp, MDR1, ABCB1) that is a seven-membrane spanning transmembrane protein capable of extruding several cytotoxic drugs that are of key importance in the treatment of hematological disorders. Similarly other ABC proteins - Multidrug resistance associated protein 1 (ABCC1) and breast cancer resistance protein (ABCG2) are both capable of pumping out cytotoxic drugs. Here, we present flow cytometric methods to identify MDR proteins by antigen and activity assays. The advantage of flow technology is the short turnaround time and its relative easiness compared to nucleic acid based technologies. However, for the activity assays, it should be noted, that these functional tests require live cells, thus adequate results can only be provided if the specimen transport can be completed within 6 hours of sample collection. Identification of MDR proteins provides prognostic information and may modulate therapy, thus signifies a clinically useful information in the evaluation of patients with leukemias.

Indexed as

drug-resistanceflow cytometryleukemia

Identifiers

PMID27683427
PMCPMC4975307
OpenAlexW2536551403

What OpenQuestion holds

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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.