Evidence map›Paper›PMID 30213399›Full record

ReviewBest practice & research. Clinical haematology2018

The promise of CAR T-cell therapy in aggressive B-cell lymphoma.

Ranjit Nair, Sattva S Neelapu

Abstract readReview
In one paragraph

Review in Best practice & research. Clinical haematology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.5field-weighted citation impact, top 8% 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

21 citing papers in PubMed, 41 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Ranjit NairDepartment of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA. Electronic address: RNair@mdanderson.org.
Sattva S NeelapuDepartment of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA. Electronic address: SNeelapu@mdanderson.org.
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

Relapsed or refractory aggressive B-cell lymphoma has an extremely poor prognosis and efforts to develop novel therapies for these patients have failed for almost four decades until the advent of chimeric antigen receptor (CAR) T-cell therapy. Within the last one year, two anti-CD19 CAR T-cell therapy products, axicabtagene ciloleucel and tisagenlecleucel, were approved by the United States Food and Drug Administration for the treatment of relapsed or refractory large B-cell lymphoma after at least two lines of systemic therapy based on multicenter single-arm phase two clinical trials. Here, we will discuss the different components of the CAR construct and their mechanisms of action, the role of conditioning chemotherapy, the efficacy and toxicity observed with anti-CD19 CAR T-cell therapies in aggressive B-cell lymphomas, and emerging strategies to further improve the safety and efficacy of these highly promising approaches.

Indexed as

Antigens, CD19Biological ProductsClinical Trials, Phase II as TopicHumansImmunotherapy, AdoptiveLymphoma, B-CellMulticenter Studies as TopicReceptors, Antigen, T-CellReceptors, Chimeric AntigenAntigens, CD19axicabtagene ciloleucelBiological ProductsReceptors, Antigen, T-CellReceptors, Chimeric AntigentisagenlecleucelAxicabtagene ciloleucelCAR T-cellDiffuse large B-cell lymphomaTisagenlecleucel

Identifiers

PMID30213399
PMCPMC6594830
OpenAlexW2885185414

What OpenQuestion holds

Textmetadata
LicenceTDM
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.