Evidence map›Paper›PMID 30026742›Full record

ArticleFrontiers in immunology2018

Combination of Cytokine-Induced Killer Cells and Programmed Cell Death-1 Blockade Works Synergistically to Enhance Therapeutic Efficacy in Metastatic Renal Cell Carcinoma and Non-Small Cell Lung Cancer.

Zibing Wang, Xiaoli Liu, Brian Till, Miaomiao Sun, Xiang Li, Quanli Gao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
0.8field-weighted citation impact, top 23% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Trial
  2. Cytokine-Induced Killer Cells: A Unique Platform for Adoptive Cell Immunotherapy after Allogeneic Hematopoietic Stem Cell Transplantation.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2025
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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

6 authors at 3 institutions in 2 countries.

Zibing WangAffiliated Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Xiaoli LiuAffiliated Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Brian TillFred Hutchinson Cancer Research Center, Seattle, WA, United States.
Miaomiao SunAffiliated Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Xiang LiAffiliated Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Quanli GaoAffiliated Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou, China.
Henan Cancer Hospital · CNZhengzhou University · CNFred Hutch Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionProgrammed cell death-1 (PD-1) inhibition therapy has changed the treatment paradigm of metastatic renal cell carcinoma (MRCC) and non-small cell lung cancer (NSCLC). However, attempts to use the drug as a single agent have achieved only limited clinical success. To further enhance the clinical benefits of monotherapy, combination therapies will likely be necessary. Cytokine-induced killer (CIK) cells are a heterogeneous subset of CASE PRESENTATION: The results of two patients treated in an ongoing clinical trial for MRCC and NSCLC are described here. The tumor biopsy from Patient 1 exhibited moderate CD3

conclusionA PD-1 inhibitor in combination with CIK cells led to potent antitumor activity in MRCC and NSCLC; CD3

Indexed as

cytokine-induced killer cellsimmunotherapylung cancerprogrammed cell death-1renal cell carcinoma

Identifiers

PMID30026742
PMCPMC6041387
OpenAlexW2809064179

What OpenQuestion holds

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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.