Evidence map›Paper›PMID 30648123›Full record

SynthesisJournal of immunology research2018

The Antitumor Immunity and Tumor Responses of Chemotherapy with or without DC-CIK for Non-Small-Cell Lung Cancer in China: A Meta-Analysis of 28 Randomized Controlled Trials.

Zheng Xiao, Cheng-Qiong Wang, Ming-Hua Zhou, Na-Na Li, Yong-Ping Sun, Yu-Zhi Wang, Shi-Yu Liu, Hong-Song Yu, Cheng-Wen Li, Xian-Tao Zeng and 3 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in Journal of immunology research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. 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

13 authors.

Zheng XiaoEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.ORCID 0000-0002-3678-8923
Cheng-Qiong WangEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.
Ming-Hua ZhouEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.
Na-Na LiEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.
Yong-Ping SunTeaching and Research Group of Evidence-based Medicine, Zhuhai Campus of Zunyi Medical College, Zhuhai, 519000 Guangdong, China.
Yu-Zhi WangDepartment of immunology, Southwest Medical University, Luzhou, 646000 Sichuan, China.
Shi-Yu LiuEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.
Hong-Song YuDepartment of Immunology, Special Key Laboratory of Gene Detection & Therapy of Guizhou Province, Zunyi Medical College, Zunyi, 563000 Guizhou, China.ORCID 0000-0002-1209-2104
Cheng-Wen LiDepartment of immunology, Southwest Medical University, Luzhou, 646000 Sichuan, China.
Xian-Tao ZengCenter for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071 Hubei, China.ORCID 0000-0003-1262-725X
Ling ChenEvidence-Based Medicine Center, MOE Virtual Research Center of Evidence-Based Medicine at Zunyi Medical College, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.
Xin-Sheng YaoDepartment of Immunology, Special Key Laboratory of Gene Detection & Therapy of Guizhou Province, Zunyi Medical College, Zunyi, 563000 Guizhou, China.ORCID 0000-0001-6960-4003
Ji-Hong FengDepartment of Oncology, Affiliated Hospital of Zunyi Medical College, Zunyi, 563000 Guizhou, China.ORCID 0000-0002-9095-9367

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDC-CIK therapy included DC-CIK cells and Ag-DC-CIK cells. To further confirm whether DC-CIK reconstructs the antitumor immunity and improves the tumor responses and reveals its optimal usage and combination with chemotherapy, we systematically reevaluated all the related studies. MATERIALS AND

methodsAll studies about DC-CIK plus chemotherapy for NSCLC were collected from the published and ongoing database as CBM, CNKI, VIP, Wanfang, ISI, Embase, MEDLINE, CENTRAL, WHO-ICTRP, Chi-CTR, and US clinical trials (established on June 2017). We evaluated their methodological bias risk according to the Cochrane evaluation handbook of RCTs (5.1.0), extracted data following the predesigned data extraction form, and synthesized the data using meta-analysis.

resultsWe included 28 RCTs (phase IV) with 2242 patients, but most trials had unclear bias risk. The SMD and 95% CI of meta-analysis for CD3

conclusionsDC-CIK therapy can simultaneously improve the antitumor immunity and tumor responses. DC-CIK therapy, especially DC-CIK cells, can improve antitumor immunity through increasing the T lymphocyte subsets, CIK cell, and NK cells in peripheral blood. The one cycle to two cycles may be optimal cycle, and the NP or GP may be optimal combination.

Indexed as

Antigens, NeoplasmCarcinoma, Non-Small-Cell LungChinaCombined Modality TherapyCytokine-Induced Killer CellsDendritic CellsHumansImmunityLung NeoplasmsLymphocyte ActivationRandomized Controlled Trials as TopicT-LymphocytesAntigens, Neoplasm

Identifiers

PMID30648123
PMCPMC6311820

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.