Evidence map›Paper›PMID 31977556›Full record

ReviewChinese medical journal2020

Advances in the development of chimeric antigen receptor-T-cell therapy in B-cell acute lymphoblastic leukemia.

Xian Zhang, Jing-Jing Li, Pei-Hua Lu

Open access · goldAbstract readReview
In one paragraph

Review in Chinese medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 22% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Biomimetic nanoparticles for tumor immunotherapy.Frontiers in bioengineering and biotechnology · 2022
    Review
  4. Article
  5. Review
  6. 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.

Xian ZhangDepartment of Hematology, Lu Daopei Hospital, Langfang, Hebei 065201, China.
Jing-Jing LiDepartment of Hematology, Lu Daopei Hospital, Langfang, Hebei 065201, China.
Pei-Hua LuDepartment of Hematology, Lu Daopei Hospital, Langfang, Hebei 065201, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CD19-targeted chimeric antigen receptor T-cell (CAR-T) therapy is effective in refractory/relapsed (R/R) B-cell acute lymphoblastic leukemia (B-ALL). This review focuses on achievements, current obstacles, and future directions in CAR-T research. A high complete remission rate of 68% to 93% could be achieved after anti-CD19 CAR-T treatment for B-ALL. Cytokine release syndrome and CAR-T-related neurotoxicity could be managed. In view of difficulties collecting autologous lymphocytes, universal CAR-T is a direction to explore. Regarding the high relapse rate after anti-CD19 CAR-T therapy, the main solutions have been developing new targets including CD22 CAR-T, or CD19/CD22 dual CAR-T. Additionally, some studies showed that bridging into transplant post-CAR-T could improve leukemia-free survival. Some patients who did not respond to CAR-T therapy were found to have an abnormal conformation of the CD19 exon or trogocytosis. Anti-CD19 CAR-T therapy for R/R B-ALL is effective. From individual to universal CAR-T, from one target to multi-targets, CAR-T-cell has a chance to be off the shelf in the future.

Indexed as

Antigens, CD19Hematopoietic Stem Cell TransplantationHumansImmunotherapy, AdoptivePrecursor B-Cell Lymphoblastic Leukemia-LymphomaReceptors, Chimeric AntigenRecurrenceAntigens, CD19Receptors, Chimeric Antigen

Identifiers

PMID31977556
PMCPMC7046249
OpenAlexW3001747163

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.