Evidence map›Paper›PMID 41185872›Full record

ReviewBioImpacts : BI2025

CAR-T cell therapy as an approach for pediatric hematological malignancies in regenerative therapy: Current status and clinical outcomes.

Xiaoman Guo, Xueyin Jiang, Juan Zhang

Abstract readReview
In one paragraph

Review in BioImpacts : BI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Concurrent MLL-AF4Frontiers in pediatrics · 2026
    Article
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.

Xiaoman GuoDepartment of Pediatrics, Yantaishan Hospital, No.10087, Keji Avenue, Laishan District, Yantai, 264003, Shandong Province, China.ORCID https://orcid.org/0009-0009-7600-6779
Xueyin JiangDepartment of Pediatrics, Yantaishan Hospital, No.10087, Keji Avenue, Laishan District, Yantai, 264003, Shandong Province, China.ORCID https://orcid.org/0009-0001-3621-5615
Juan ZhangDepartment of Pediatrics, Yantaishan Hospital, No.10087, Keji Avenue, Laishan District, Yantai, 264003, Shandong Province, China.ORCID https://orcid.org/0009-0007-2915-8185

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiation therapy, chemotherapy, and surgery have been the standard cancer treatment approaches for many years. Even with these treatments, the majority of tumors still have a dismal prognosis. With complete remission rates ranging from 65% to 90% in the crucial CD19-CART trials, chimeric antigen receptor T-cell (CART) therapy has revolutionized the treatment paradigm for pediatric patients with relapsed/refractory B-cell acute lymphoblastic leukemia (B-ALL). Hematological tumors have responded well to CART. The first CART was authorized by the FDA in 2017 to treat B-ALL. The FDA authorized CART to treat B-cell lymphoma in October of that year. In recent years, research has focused on CART to increase and improve the therapeutic effect. New toxicity profiles and treatment constraints have also surfaced with this new medicine, calling for cooperative group trials, new management strategies, and toxicity consensus grading systems. The introduction of CART treatment for pediatric B-cell ALL will be the main topic of this article, along with previous and ongoing trials. We will also talk about CART therapy trials for various pediatric cancers. Safe procedures and close observation are essential since CART treatment has the potential to cause serious toxicities.

Indexed as

Acute lymphoblastic leukemiaCARTCAR-T cell therapyClinical outcomesPediatric hematological malignancies

Identifiers

PMID41185872
PMCPMC12579741

What OpenQuestion holds

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LicenceCC BY-NC
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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.