Evidence map›Paper›PMID 30109179›Full record

ReviewActa pharmaceutica Sinica. B2018

The application of CAR-T cell therapy in hematological malignancies: advantages and challenges.

Zijun Zhao, Yu Chen, Ngiambudulu M Francisco, Yuanqing Zhang, Minhao Wu

Abstract readReview
In one paragraph

Review in Acta pharmaceutica Sinica. B, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 134 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
134citing papers in PubMed, 2 pooled it
–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

134 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  5. Technical review of artificial intelligence in TCR-T therapy.Journal of the National Cancer Center · 2026
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  6. Acta pharmaceutica Sinica. B · 2026
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74 more citing papers are in PubMed but not listed here.

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.

Zijun ZhaoZhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
Yu ChenZhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
Ngiambudulu M FranciscoZhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
Yuanqing ZhangSchool of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou 510006, China.
Minhao WuZhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor T cell (CAR-T cell) therapy is a novel adoptive immunotherapy where T lymphocytes are engineered with synthetic receptors known as chimeric antigen receptors (CAR). The CAR-T cell is an effector T cell that recognizes and eliminates specific cancer cells, independent of major histocompatibility complex molecules. The whole procedure of CAR-T cell production is not well understood. The CAR-T cell has been used predominantly in the treatment of hematological malignancies, including acute lymphoblastic leukemia, chronic lymphocytic leukemia, lymphoma, and multiple myeloma. Solid tumors including melanoma, breast cancer and sarcoma offer great promise in CAR-T cell research and development. CD19 CAR-T cell is most commonly used, and other targets, including CD20, CD30, CD38 and CD138 are being studied. Although this novel therapy is promising, there are several disadvantages. In this review we discuss the applications of CAR-T cells in different hematological malignancies, and pave a way for future improvement on the effectiveness and persistence of these adoptive cell therapies.

Indexed as

Chimeric antigen receptor T cellClinical applicationsImmunotherapyMalignancies

Identifiers

PMID30109179
PMCPMC6090008

What OpenQuestion holds

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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.