Evidence map›Paper›PMID 29141027›Full record

SynthesisPloS one2017

The efficacy of chimeric antigen receptor (CAR) immunotherapy in animal models for solid tumors: A systematic review and meta-analysis.

Yingcheng Wu, Ran Xu, Keren Jia, Hui Shi

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2017. 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
0.2field-weighted citation impact, top 40% 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. 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

4 authors at 1 institution in 1 country.

Yingcheng WuMedical School of Nantong University, Jiangsu, China.ORCID http://orcid.org/0000-0001-9473-546X
Ran XuMedical School of Nantong University, Jiangsu, China.
Keren JiaMedical School of Nantong University, Jiangsu, China.
Hui ShiDepartment of Thoracic Surgery, Affiliated Hospital of Nantong University, Nantong, Jiangsu, China.ORCID http://orcid.org/0000-0001-6446-4160
Nantong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMost recently, an emerging theme in the field of tumor immunology predominates: chimeric antigen receptor (CAR) therapy in treating solid tumors. The number of related preclinical trials was surging. However, an evaluation of the effects of preclinical studies remained absent. Hence, a meta-analysis was conducted on the efficacy of CAR in animal models for solid tumors.

methodsThe authors searched PubMed/Medline, Embase, and Google scholar up to April 2017. HR for survival was extracted based on the survival curve. The authors used fixed effect models to combine the results of all the trials. Heterogeneity was assessed by I-square statistic. Quality assessment was conducted following the Stroke Therapy Academic Industry Roundtable standard. Publication bias was assessed using Egger's test.

resultsEleven trials were included, including 54 experiments with a total of 362 animals involved. CAR immunotherapy significantly improved the survival of animals (HR: 0.25, 95% CI: 0.13-0.37, P < 0.001). The quality assessment revealed that no study reported whether allocation concealment and blinded outcome assessment were conducted, and only five studies implemented randomization.

conclusionsThis meta-analysis indicated that CAR therapy may be a potential clinical strategy in treating solid tumors.

Indexed as

Disease Models, AnimalImmunotherapyAnimalsHumansNeoplasmsReceptors, AntigenRecombinant Fusion ProteinsReceptors, AntigenRecombinant Fusion Proteins

Identifiers

PMID29141027
PMCPMC5687736
OpenAlexW2769734729

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.