ArticleHeliyon2024
Quantification of cancer biomarkers in urine using volatilomic approach.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Collision-Induced Gas-Phase Reactions of PFB-TMS Derivatives of FMolecules (Basel, Switzerland) · 2025Pooled it
- Advances in biomarkers of benzene exposure and toxicity: From mechanistic insights to occupational health applications (Review).Molecular medicine reports · 2026Review
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Non-Invasive Detection of Tumors by Volatile Organic Compounds in Urine.Biomedicines · 2025Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urine analysis is an attractive approach for non-invasive cancer diagnostics. In this study, a procedure for the determination of volatile organic compounds (VOCs) in human urine (acetone, acetonitrile, dimethylsulfide, dimethyl disulfide, dimethyl trisulfide, hexane, benzene, toluene, 2-butanone, 2-pentanone, pentanal) has been described including sample preparation using preconcentration of analytes in sorbent tubes followed by gas chromatography with mass spectrometry (GC-MS). Fractional factorial design and constrained surfaces design were used to optimize preconcentration of VOCs in sorbent tubes. The procedure was validated by analysis of synthetic urine containing VOC standards in the concentration range of 1-5000 ng/mL. Optimized procedure was applied to analyze urine samples of 89 healthy volunteers and 85 patients with cancer of various localizations: 42 patients with lung cancer, 25 - colon, 3 - stomach, 2 - prostate, 2 - esophageal, 2 - pancreas, 2 - kidney, 1 - ovarian, 1 - cervical, 1 - skin, 1 - liver. Concentrations of 2-butanone, 2-pentanone, acetonitrile, and benzene were found different in urine of patients with cancer and healthy individuals. Influence of cancer localization and tumor, nodule, metastasis stage on urine VOC profile was considered. The approach of using ratios of VOCs to the main ones instead of concentrations was considered. A diagnostic model based on significantly different VOC ratios was created to classify healthy individuals and patients with cancer using artificial neural network (ANN). The model was validated during construction by means of 3-fold cross-validation. Average area under receiver operating characteristic (ROC) curve on test dataset was 0.886. Average sensitivity and specificity of the created model were 91 % and 82 %.
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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.