ArticleScientific reports2024
Urinary cancer detection by the target urine volatile organic compounds biosensor platform.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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
10 citing papers in PubMed, 10 citations in OpenAlex.
- Pulmonary hypertension in dialysis patients: clinical insights from tricuspid regurgitation velocity (TRV)-based echocardiographic criteria.Renal failure · 2026Article
- Advances and Challenges in Wearable Sensors for Health Monitoring.ACS applied materials & interfaces · 2026Review
- Prevalence and risk factors of atrial fibrillation in type 2 diabetes mellitus: a hospital-based cross-sectional study.BMC cardiovascular disorders · 2026Article
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.BMC nephrology · 2025Article
- Colorectal Cancer Detection Through Sweat Volatilome Using an Electronic Nose System and GC-MS Analysis.Cancers · 2025Article
- Volatile Organic Compounds in Biological Matrices as a Sensitive Weapon in Cancer Diagnosis.Pharmaceuticals (Basel, Switzerland) · 2025Review
- The biosensor using the target urine volatile organic compounds for detecting diabetic kidney disease.Scientific reports · 2025Article
- Non-Invasive Detection of Tumors by Volatile Organic Compounds in Urine.Biomedicines · 2025Review
- Evaluation of urinary volatile organic compounds as a novel metabolomic biomarker to assess chronic kidney disease progression.BMC nephrology · 2024Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Volatile organic compounds (VOCs) have grown due to their crucial role in transitioning from invasive to noninvasive cancer diagnostic methods. This study aimed to assess the feasibility of the metal oxide biosensor platform using urine VOCs for detecting genitourinary cancers. Five different commercially available semiconductor sensors were chosen to detect specific VOCs (methane, iso-butane, hydrogen, ethanol, hydrogen sulfide, ammonia, toluene, butane, propane, trimethylamine, and methyl-mercaptan). Changes in electrical resistance due to temperature variations from the voltage heater were examined to characterize VOC metabolism. Logistic regression and ROC analysis were employed to evaluate potential urine VOCs for genitourinary cancer determination. This study involved 64 participants which were categorized into a cancer and a non-cancer group. The genitourinary cancer (confirmed by tissue pathology) comprised 32 patients, including renal cell carcinoma (3.1%), transitional cell carcinoma (46.9%), and prostate cancer (50%). The non-cancer comprised 32 patients, with 9 healthy subjects and 23 individuals with other genitourinary diseases. Results indicated that VOC sensors for methane, iso-butane, hydrogen, and ethanol, at a voltage heater of 2000 mV, demonstrated a significant predictive capability for genitourinary cancer with P = 0.013. The ROC of these biomarkers also indicated statistical significance in predicting the occurrence of the disease (P < 0.05). This report suggested that methane, iso-butane, hydrogen, and ethanol VOCs exhibited potential for diagnosing genitourinary cancer. Developing gas metal oxide sensors tailored to these compounds, and monitoring changes in electrical resistance, could serve as an innovative tool for identifying this specific type of cancer.
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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.