ArticleHeliyon2023
Volatile organic compounds for early detection of prostate cancer from urine.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Urinary and cellular volatile organic compounds as biomarkers for urological cancers: a systematic review of GC-MS-based volatolomics.Metabolomics : Official journal of the Metabolomic Society · 2026Pooled it
- Machine Learning-Based Profiling of Urinary Volatile Organic Compounds Reveals Distinct Diagnostic Signatures for Gastric Cancer.Cancer medicine · 2026Article
- Olfactory Science and Technology in Prostate Cancer Diagnosis: From Invertebrate Models to Artificial Intelligence.Life (Basel, Switzerland) · 2026Review
- Urine volatile organic compounds (VOCs) combined with machine learning algorithm in the diagnosis of gallstones with cholecystitis.Scientific reports · 2026Article
- Multidimensional liquid biopsy in bladder cancer: advances in circulating tumor cells, circulating tumor DNA, exosomes, and metabolomics.The oncologist · 2026Review
- Article
- Single-layer biosensor for urinary prostate-cancer biomarkers through transition-metal-doped graphene: a DFT study.RSC advances · 2025Article
- Urinary Metabolome Study for Monitoring Prostate Cancer Recurrence Following Radical Prostatectomy.Cancers · 2025Article
- Identification of a panel of volatile organic compounds in urine for early detection of for bladder cancer.Scientific reports · 2025Article
- Non-Invasive Detection of Tumors by Volatile Organic Compounds in Urine.Biomedicines · 2025Review
- Article
- 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
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Early diagnosis of PCa is extremely challenging due to the lack of effective diagnostic methods. The study presented here aims to evaluate whether urine volatile organic compounds (VOCs) can be used as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) was used to detect VOCs in urine samples from 66 patients with PCa and to comparatively analyze samples from 87 patients with non-cancerous controls (NCs). A total of 86 substance peak heights were detected in urine samples from all patients. Analysis using four machine learning algorithms suggested that the diagnosis of PCa could be effectively facilitated. Ultimately, diagnostic models were constructed based on the four VOCs selected. The AUC for the RF and SVM model were 0.955 and 0.981, respectively. Both the NN and DT diagnostic models also achieved an AUC of 0.8 or more, but their sensitivity or specificity was poor compared to the RF and SVM models.
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Registered trials
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