SynthesisMedical science monitor : international medical journal of experimental and clinical research2015
A Positive Role of Cytokine-Induced Killer Cell Therapy on Gastric Cancer Therapy in a Chinese Population: A Systematic Meta-Analysis.
Synthesis in Medical science monitor : international medical journal of experimental and clinical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 12 citations in OpenAlex.
- Efficacy of DC-CIK Immunotherapy Combined with Chemotherapy on Locally Advanced Gastric Cancer.Journal of oncology · 2022Article
- Clinical Trials with Combination of Cytokine-Induced Killer Cells and Dendritic Cells for Cancer Therapy.International journal of molecular sciences · 2019Review
- Immunotherapy for Gastric Cancer: Time for a Personalized Approach?International journal of molecular sciences · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChemotherapy and radiation therapy provide limited improvement in survival of gastric cancer patients after tumor resection. It is essential to develop a novel therapeutics for gastric cancer. In the recent years, cytokine-induced killer cells (CIKs)-based adoptive immune therapy has been explored in gastric cancer patients. Due to the small number of patients included in each clinical trial and low-power statistical analysis, the effectiveness of this approach is still unclear. To address this issue, we systemically analyzed the relevant clinical trial data published in recent years by powerful statistical meta-analysis. MATERIAL AND
methodsClinical data was searched by multiple electronic databases with a term "gastric cancer" and "cytokine-induced killer cells". Six relevant clinical trials with case-control studies were extracted for our meta-analysis, including 318 patients receiving CIK cell therapy and 369 patients receiving conventional therapy.
resultsOverall survival (OS) and odds ratio (OR) were analyzed for patients at 1, 2, 3, and 5 years post-CIK cell therapy and post-conventional therapy. Heterogeneity and publication bias were analyzed for included data quality and publication bias. Our meta-analysis from 6 clinical trials suggests that CIK cell therapy significantly increased 5-year OS from 27±2.44% to 49±7.62% (p<0.05) and 5-year OR up to 1.77 (p<0.05). The increased 5-year survival rate was also highly correlated with the increased CD3+ T cell number and ratio of CD4+/CD8+ in the CIK treated patients.
conclusionsCIK cell therapy significantly increased 5-year survival rate compared to conventional chemotherapy among gastric cancer patients. The study provides powerful statistical evidence for large-scale clinical trials with CIK cell therapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.