ArticleSurgical innovation2018
Pilot Study: Detection of Gastric Cancer From Exhaled Air Analyzed With an Electronic Nose in Chinese Patients.
Article in Surgical innovation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 21 papers, 6 of them syntheses that pooled it.
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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.
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Who cites it
21 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Exploring Components, Sensors, and Techniques for Cancer Detection via eNose Technology: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis.JAMA network open · 2022Pooled it
- Volatile organic compounds as a potential screening tool for neoplasm of the digestive system: a meta-analysis.Scientific reports · 2021Pooled it
- Breath analysis for the detection of digestive tract malignancies: systematic review.BJS open · 2021Pooled it
- Volatile Organic Compounds in Human Exhaled Breath to Diagnose Gastrointestinal Cancer: A Meta-Analysis.Frontiers in oncology · 2021Pooled it
- Pooled it
- Advanced breath analysis through hierarchical deep convolutional neural network for multi-cancer screening.NPJ digital medicine · 2026Article
- A Review of Exhaled Volatile Organic Compounds as Emerging Diagnostic Tools for Gastrointestinal Malignancies.Archives of Iranian medicine · 2026Review
- Application of electronic nose technology in the diagnosis of gastrointestinal diseases: a review.Journal of cancer research and clinical oncology · 2024Review
- Sample Collection and Processing in Volatile Organic Compound Analysis for Gastrointestinal Cancers.Diagnostics (Basel, Switzerland) · 2024Review
- Diagnosis of chondrosarcoma in a noninvasive way using volatile organic compounds in exhaled breath: a pilot study.Future oncology (London, England) · 2024Article
- Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends.Biomedicines · 2023Review
- Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection.Diagnostics (Basel, Switzerland) · 2022Article
- Diagnostic Ability of Volatile Organic Compounds in Digestive Cancer: A Systematic Review With Meta-Analysis.Clinical Medicine Insights. Oncology · 2022Article
- Volatolomics in healthcare and its advanced detection technology.Nano research · 2022Review
- Diagnostic Application of Volatile Organic Compounds as Potential Biomarkers for Detecting Digestive Neoplasia: A Systematic Review.Diagnostics (Basel, Switzerland) · 2021Review
- Applying the electronic nose for pre-operative SARS-CoV-2 screening.Surgical endoscopy · 2021Article
- Review
- Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors.Diagnostics (Basel, Switzerland) · 2020Article
- Can Electric Nose Breath Analysis Identify Abdominal Wall Hernia Recurrence and Aortic Aneurysms? A Proof-of-Concept Study.Surgical innovation · 2020Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this pilot study is to investigate the ability of an electronic nose (e-nose) to distinguish malignant gastric histology from healthy controls in exhaled breath. In a period of 3 weeks, all preoperative gastric carcinoma (GC) patients (n = 16) in the Beijing Oncology Hospital were asked to participate in the study. The control group (n = 28) consisted of family members screened by endoscopy and healthy volunteers. The e-nose consists of 3 sensors with which volatile organic compounds in the exhaled air react. Real-time analysis takes place within the e-nose, and binary data are exported and interpreted by an artificial neuronal network. This is a self-learning computational system. The inclusion rate of the study was 100%. Baseline characteristics differed significantly only for age: the average age of the patient group was 57 years and that of the healthy control group 37 years ( P value = .000). Weight loss was the only significant different symptom ( P value = .040). A total of 16 patients and 28 controls were included; 13 proved to be true positive and 20 proved to be true negative. The receiver operating characteristic curve showed a sensitivity of 81% and a specificity of 71%, with an accuracy of 75%. These results give a positive predictive value of 62% and a negative predictive value of 87%. This pilot study shows that the e-nose has the capability of diagnosing GC based on exhaled air, with promising predictive values for a screening purpose.
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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.