Evidence map›Paper›PMID 38560185›Full record

ReviewHeliyon2024

Improving cell reinfusion to enhance the efficacy of chimeric antigen receptor T-cell therapy and alleviate complications.

Zhihao Han, Xiaoqin Ma, Guiyue Ma

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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 at 1 institution in 1 country.

Zhihao HanDepartment of Nursing, Zhejiang Chinese Medical University, Hangzhou City, Zhejiang Province, China.
Xiaoqin MaDepartment of Nursing, Zhejiang Chinese Medical University, Hangzhou City, Zhejiang Province, China.
Guiyue MaDepartment of Nursing, Zhejiang Chinese Medical University, Hangzhou City, Zhejiang Province, China.
Zhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adoptive cell therapy (ACT) is a rapidly expanding area within the realm of transfusion medicine, focusing on the delivery of lymphocytes to trigger responses against tumors, viruses, or inflammation. This area has quickly evolved from its initial promise in immuno-oncology during preclinical trials to commercial approval of chimeric antigen receptor (CAR) T-cell therapies for leukemia and lymphoma (Jun and et al., 2018) [1]. CAR T-cell therapy has demonstrated success in treating hematological malignancies, particularly relapsed/refractory B-cell acute lymphoblastic leukemia and non-Hodgkin's lymphoma (Qi and et al., 2022) [2]. However, its success in treating solid tumors faces challenges due to the short-lived presence of CAR-T cells in the body and diminished T cell functionality (Majzner and Mackall, 2019) [3]. CAR T-cell therapy functions by activating immune effector cells, yet significant side effects and short response durations remain considerable obstacles to its advancement. A prior study demonstrated that the therapeutic regimen can induce systemic inflammatory reactions, such as cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), tumor lysis syndrome (TLS), off-target effects, and other severe complications. This study aims to explore current research frontiers in this area.

Indexed as

Cell reinfusionChimeric antigen receptor T cellsComplicationsCytokine release syndromeLymphomaPretreatment

Identifiers

PMID38560185
PMCPMC10981037
OpenAlexW4392881265

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.