ArticleMedicine2020
Protocol for a systematic review and meta-analysis of Kang-ai injection for patients with oesophageal cancer.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Efficacy and safety of Chinese patent medicine (Kang-ai injection) as an adjuvant in the treatment of patients with hepatocellular carcinoma: a meta-analysis.Pharmaceutical biology · 2021Pooled it
- Article
- Association between preoperative neutrophil-to-lymphocyte ratio and the survival outcomes of esophageal cancer patients underwent esophagectomy: a systematic review and meta-analysis.Frontiers in oncology · 2024Review
- Overcoming Basal Autophagy, Kangai Injection Enhances Cisplatin Cytotoxicity by Regulating FOXO3a-Dependent Autophagic Cell Death and Apoptosis in Human Lung Adenocarcinoma A549/DDP Cells.BioMed research international · 2022Article
- The value of microRNA-203 as a biomarker for the prognosis of esophageal cancer: A protocol for systematic review and meta-analysis.Medicine · 2020Article
- Traditional Chinese Medicine Therapy for Esophageal Cancer: A Literature Review.Integrative cancer therapiesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOesophageal cancer (OC) is the sixth leading cause of cancer death worldwide. Despite the improvement of therapeutic methods in recent years, the prognosis of OC remains unsatisfactory. Kang-ai injection, a kind of traditional Chinese herbal medicine, has been widely applied as a promising adjunctive drug for OC. In this study, we aimed to summarize the efficacy and safety of Kang-ai injection for patients with advanced OC through the meta-analysis, in order to provide scientific reference for the design of future clinical trials.
methodsRelevant randomized controlled trials and high-quality prospective cohort studies were searched from PubMed, Web of Science, Medline, Cochrane Library, Google Scholar, Excerpt Medica Database, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, China Scientific Journal Database and Wanfang Database. Papers in English or Chinese published from their inception to August 2020 will be included without any restrictions.Study selection and data extraction will be performed independently by 2 investigators. The clinical outcomes including overall response rate, disease control rate, overall survival, disease-free survival, quality of life, immune function and adverse events, were systematically evaluated. Stata 14.0 and Review Manager 5.3 were used for data synthesis, subgroup analysis, sensitivity analysis, meta regression, and risk of bias assessment.
resultsThe results of this study will be published in a peer-reviewed journal, or presented the findings at a relevant conference.
conclusionOur study will draw an objective conclusion of the effects of Kang-ai injection combined with conventional treatment for advanced OC and provide a helpful evidence for clinicians to formulate the best postoperative adjuvant treatment strategy for OC patients. INPLASY REGISTRATION NUMBER: INPLASY202080019.
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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.