Evidence map›Paper›PMID 30858955›Full record

ArticleMediterranean journal of hematology and infectious diseases2019

Spectrum and Immunophenotypic Profile of Acute Leukemia: A Tertiary Center Flow Cytometry Experience.

Nishit Gupta, Ravikiran Pawar, Sambhunath Banerjee, Subhajit Brahma, Asish Rath, Sundar Shewale, Mayur Parihar, Manish Singh, S R Arun, Shekhar Krishnan and 9 more

Open access · goldAbstract read
In one paragraph

Article in Mediterranean journal of hematology and infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 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

19 authors at 1 institution in 1 country.

Nishit GuptaDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Ravikiran PawarDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Sambhunath BanerjeeDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Subhajit BrahmaDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Asish RathDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Sundar ShewaleDepartment of Laboratory Hematology, Tata Medical Center, Kolkata.
Mayur PariharDepartment of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.
Manish SinghDepartment of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.
S R ArunDepartment of Laboratory Hematology and Cytogenetics, Tata Medical Center, Kolkata.
Shekhar KrishnanDepartment of Pediatric Oncology, Tata Medical Center, Kolkata.
Arpita BhatacharyyaDepartment of Pediatric Oncology, Tata Medical Center, Kolkata.
Anirban DasDepartment of Pediatric Oncology, Tata Medical Center, Kolkata.
Jeevan KumarDepartment of Clinical Hematology, Tata Medical Center, Kolkata.
Saurabh BhaveDepartment of Clinical Hematology, Tata Medical Center, Kolkata.
Vivek RadhakrishnanDepartment of Clinical Hematology, Tata Medical Center, Kolkata.
Reena NairDepartment of Clinical Hematology, Tata Medical Center, Kolkata.
Mammen ChandyDepartment of Clinical Hematology, Tata Medical Center, Kolkata.
Neeraj AroraDepartment of Laboratory Hematology and Molecular Genetics, Tata Medical Center, Kolkata.
Deepak MishraDepartment of Laboratory Hematology and Molecular Genetics, Tata Medical Center, Kolkata.
Tata Medical Center · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor diagnosis, sub-categorization and follow up of Acute Leukemia (AL), phenotypic analysis using flow cytometry is mandatory. MATERIAL AND

methodsWe retrospectively analyzed immunophenotypic data along with cytogenetics/molecular genetics data (wherever available) from 631 consecutive cases of AL diagnosed at our flow cytometry laboratory from January 2014 to August 2017.

resultsOf the total 631 cases, 52.9% (n=334) were acute lymphoblastic leukemia (ALL), 43.9% (n=277) acute myeloid leukemia (AML), 2.2% (n=14) mixed phenotypic acute leukemia (MPAL), 0.5% (n=3) acute undifferentiated leukemia (AUL) and 0.5% (n=3) chronic myeloid leukemia in blast crisis (CML-BC). ALL cases comprised of 81.7% (n=273/334) B-cell ALLs (95.2%, n=260/273 common B-ALLs and 4.8%, n=13/273 Pro B-ALLs). CD13 was the commonest cross lineage antigen, expressed in B-ALL (25.6%, n=70/273), followed by CD33 (17.9%, n=49) and combined CD13/CD33 (11.3%, n=31/273) expression. T-ALLs constituted 18.3% (n=61/334) of total ALLs and included 27.9% (n=17/61) cortical T- ALLs. CD13 was commonest (32.7%, n=20/61) aberrantly expressed antigen in T-ALLs, followed by CD117 (19.1%, n=9/47). AML cases included 32.1% (n=89/277) AML with recurrent genetic abnormalities, 9.0% (n=25/277) with FLT3/NPM1c mutation and 58.9% (n=163/277) AML NOS including 14.7% (n=24/163) AML M4/M5, 1.8% (n=3/163) AML M6 and 3.7% (n=6/163) AML M7. In AMLs, CD19 aberrancy was the most common (20.2%, n=56/277) followed by CD56 (15.8%, n=42/265).

conclusionsIn this study, we document the spectrum, correlate the immunophenotype with genetic data of all leukemias, especially concerning T-ALL where the data from India is scarce.

Indexed as

AMLAULB-ALLFLT3/NPM1cMPALT-ALL

Identifiers

PMID30858955
PMCPMC6402547
OpenAlexW2917700400

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.