Evidence map›Paper›PMID 34980040›Full record

ArticleBMC cancer2022

Targeting CD33 for acute myeloid leukemia therapy.

Jingjing Liu, Jiayin Tong, Haiping Yang

Abstract readEvaluation Study
In one paragraph

Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
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

24 citing papers in PubMed.

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  11. Article
  12. CD33Journal for immunotherapy of cancer · 2025
    Article
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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

3 authors.

Jingjing Liu *Department of Hematology, First Affiliated Hospital of Henan University of Science and Technology, 636 Guanlin Road, Luoyang, Henan, 471000, P.R. China.
Jiayin TongDepartment of Hematology, First Affiliated Hospital of Henan University of Science and Technology, 636 Guanlin Road, Luoyang, Henan, 471000, P.R. China.
Haiping Yang *Department of Hematology, First Affiliated Hospital of Henan University of Science and Technology, 636 Guanlin Road, Luoyang, Henan, 471000, P.R. China. 1356166848@qq.com.ORCID http://orcid.org/0000-0003-4472-0694

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to analyze the level of CD33 expression in patients with newly diagnosed AML and determine its correlation with clinical characteristics.

methodsSamples were collected for analysis from AML patients at diagnosis. We evaluated the level of CD33 expression by flow cytometry analysis of bone marrow. Chi-square or t- tests were used to assess the association between the high and low CD33 expression groups. Survival curves were generated by the Kaplan-Meier and Cox regression model method.

resultsIn this study we evaluated the level of CD33 expression in de novo patients diagnosed from November 2013 until January 2019. The mean value of 73.4% was used as the cutoff for the two groups. Statistical analysis revealed that 53 of the 86 (61.2%) AML patients were above the mean. Although there was no statistical significance between CD33 expression level and gene mutation, FLT3 mutation (P = 0.002) and NPM1 mutation (P = 0.001) were more likely to be seen in the high CD33 group. The overall survival (OS) was worse in the high CD33 group (39.0 m vs. 16.7 m, x

conclusionsThese findings provide a strong rationale for targeting CD33 in combination with chemotherapy, which can be considered a promising therapeutic strategy for AML.

Indexed as

AdolescentAdultAgedAged, 80 and overBone MarrowChildFemaleFlow Cytometryfms-Like Tyrosine Kinase 3HumansKaplan-Meier EstimateLeukemia, Myeloid, AcuteMaleMiddle AgedMutationNucleophosminCD33 protein, humanFLT3 protein, humanfms-Like Tyrosine Kinase 3NPM1 protein, humanNucleophosminSialic Acid Binding Ig-like Lectin 3Acute myeloid leukemiaCD33Immunotherapy

Identifiers

PMID34980040
PMCPMC8722076

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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.