ArticleTechniques in coloproctology2019
Colorectal cancer and adenoma screening using urinary volatile organic compound (VOC) detection: early results from a single-centre bowel screening population (UK BCSP).
Article in Techniques in coloproctology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 5 of them syntheses that pooled 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.
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
38 citing papers in PubMed, 5 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Pooled it
- Diagnostic performance of volatile organic compounds analysis and electronic noses for detecting colorectal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Volatile organic compounds as a potential screening tool for neoplasm of the digestive system: a meta-analysis.Scientific reports · 2021Pooled it
- Medical diagnosis at the point-of-care by portable high-field asymmetric waveform ion mobility spectrometry: a systematic review and meta-analysis.Journal of breath research · 2021Pooled it
- Volatile organic compounds analysis as a potential novel screening tool for colorectal cancer: A systematic review and meta-analysis.Medicine · 2020Pooled it
- Urine volatile organic compounds (VOCs) combined with machine learning algorithm in the diagnosis of gallstones with cholecystitis.Scientific reports · 2026Article
- The diagnostic potential of urinary volatile organic compounds for colorectal neoplasia in Lynch syndrome-A prospective longitudinal study.International journal of cancer · 2026Article
- Colorectal Cancer Detection Through Sweat Volatilome Using an Electronic Nose System and GC-MS Analysis.Cancers · 2025Article
- Harnessing serum VOCs and machine learning for the early detection of MAFLD.Frontiers in endocrinology · 2025Article
- Article
- The human volatilome meets cancer diagnostics: past, present, and future of noninvasive applications.Metabolomics : Official journal of the Metabolomic Society · 2024Review
- Sample Collection and Processing in Volatile Organic Compound Analysis for Gastrointestinal Cancers.Diagnostics (Basel, Switzerland) · 2024Review
- Unraveling the microbiome-metabolome nexus: a comprehensive study protocol for personalized management of Behçet's disease using explainable artificial intelligence.Frontiers in microbiology · 2024Article
- Potential urinary volatile organic compounds as screening markers in cancer - a review.Frontiers in oncology · 2024Review
- Identification of urinary volatile organic compounds as a potential non-invasive biomarker for esophageal cancer.Scientific reports · 2023Article
- Gut bacteria promote proliferation in benign S/RG/C2 colorectal tumour cells, and promote proliferation, migration and invasion in malignant HCT116 cells.Scientific reports · 2023Article
- Identification of Volatile Markers of Colorectal Cancer from Tumor Tissues Using Volatilomic Approach.Molecules (Basel, Switzerland) · 2023Article
- Volatile Organic Compound Assessment as a Screening Tool for Early Detection of Gastrointestinal Diseases.Microorganisms · 2023Review
- The Versatility and Diagnostic Potential of VOC Profiling for Noninfectious Diseases.BME frontiers · 2023Article
- Microbiome and Colorectal Cancer Management.Cureus · 2022Review
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 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe United Kingdom (UK) bowel cancer screening programme has reduced mortality from colorectal cancer (CRC), but poor uptake with stool-based tests and lack of specificity of faecal occult blood testing (FOBT), has prompted investigation for a more suitable screening test. The aim of this study was to investigate the feasibility of a urinary volatile organic compounds (VOC)-based screening tool for CRC.
methodsThe urine from FOBT-positive patients was analysed using field asymmetric ion mobility spectrometry (FAIMS) and gas chromatography coupled with ion mobility spectrometry (GC-IMS). Data were analysed using a machine learning algorithm to calculate the test accuracy for correct classification of CRC against adenomas and other gastrointestinal pathology.
resultsOne hundred and sixty-three patients were enrolled in the study. Test accuracy was high for differentiating CRC from control: area under the curve (AUC) 0.98 (95% CI 0.93-1) and 0.82 (95% CI 0.67-0.97) using FAIMS and GC-IMS respectively. Correct classification of CRC from adenoma was high with AUC range 0.83-0.92 (95% CI 0.43-1.0). Classification of adenoma from control was poor with AUC range 0.54-0.61 (95% CI 0.47-0.75) using both analytical modalities.
conclusionsCRC was correctly distinguished from adenomas or no bowel pathology using urinary VOC markers, within the bowel screening population. This pilot study demonstrates the potential of this method for CRC detection, with higher test uptake and superior sensitivity than FOBT. In addition, this is the first application of GC-IMS in CRC detection which has shown high test accuracy and usability.
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.