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This study evaluates whether urinary volatile organic compounds (VOCs) can serve as an emerging diagnostic biomarker for PCa. Gas chromatography-ion mobility spectrometry (GC-IMS) quantified VOCs in 66 PCa patients and 87 non-cancer controls. Machine learning based on four selected VOCs enabled diagnostic models, with RF and SVM achieving AUCs of 0.955 and 0.981, respectively.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/volatile-organic-compounds-for-early-detection-of-prostate-cancer-from-urine/376884/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/volatile-organic-compounds-for-early-detection-of-prostate-cancer-from-urine/376884.png","ImageObject",300,407,{"name":92,"@type":93},"Margaret","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-24",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why is early detection of prostate cancer challenging?","Question",{"text":113,"@type":114},"Early diagnosis is extremely challenging due to the lack of effective diagnostic methods. PSA-based screening has limited specificity, leading to many false positives and unnecessary biopsy procedures.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were volatile organic compounds (VOCs) detected in the study?",{"text":118,"@type":114},"The study used gas chromatography-ion mobility spectrometry (GC-IMS) to detect VOCs in urine samples, then compared PCa samples with non-cancer controls.",{"name":120,"@type":111,"acceptedAnswer":121},"Which diagnostic models performed best, and what were the AUC values?",{"text":122,"@type":114},"Models built from four selected VOCs were tested using four machine learning algorithms. The RF and SVM models showed AUCs of 0.955 and 0.981, respectively, outperforming NN and DT, which had AUCs around 0.8 but weaker sensitivity or specificity.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},376884,1790637042,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":34,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},137451207643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Heliyon 9 (2023) e16686  \nContents lists available at ScienceDirect  \nHeliyon  \njournal [homepage:](homepage: www.cell.com/heliyon)[ www.cell.com/heliyon](homepage: www.cell.com/heliyon)  \n| Volatile organic compounds for early detection of prostate cancer from urine\u003Cbr>Qi Liu a, b, Yingjing Fan a, b, Shunjie Zenga, b, Yuxiao Zhao a, b, Longchen Yu a, b, Liqiang Zhao c, Jingxian Gaoc, Xin Zhang a, b, **, Yi Zhang a, b, *\u003Cbr>a Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China b Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China\u003Cbr>c Department of Research and Development, Hanon Advanced Technology Group Co., Ltd, Jinan, China |  |  |\n| --- | --- | --- |\n| A R T I C L E I N F O |  | A B S T R A C T |\n| Keywords:\u003Cbr>Prostate cancer\u003Cbr>Volatile organic compounds Diagnosis\u003Cbr>Urine |  | 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. |\n\n1. Introduction  \nProstate cancer (PCa) is the second most common cancer and fifth leading cause of cancer death among men worldwide [1]. In 2020, PCa is estimated to be responsible for 1,400,000 new cases and 375,000 deaths worldwide. Current PCa diagnosis and monitoring consists of PSA testing, abnormal digital rectal examination, and histopathological evaluation of prostate biopsy samples. Nevertheless, a high number of false positive results are associated with PSA screening in the diagnosis of PCa due to its lack of specificity. Furthermore, most abnormal PSA results are false positive results caused by benign prostatic hyperplasia (BPH), prostatitis, or cystitis, and the normal PSA can’t exclude PCa either [2,3]. The resulting unnecessary prostate biopsy often leads to fever, infection and pain in patients [4]. The survival time of PCa patients is closely related to the malignant tumor stage at clinical diagnosis. Although the progression of PCa is slow, most newly diagnosed cases of PCa are in advanced stage due to insidious onset, resulting in poor overall prognosis of PCa patients. Therefore, screening for PCa in high-risk groups, diagnosis of early PCa, and standardized treatment are  \n* Corresponding author. Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China.  \n** Corresponding author. Department of Clinical Laboratory, Qilu Hospital of Shandong University, 107 Wenhua Xi Road, Jinan, Shandong, 250012, China.  \nE-mail addresses: [xinzhang@sdu.edu.cn](xinzhang@sdu.edu.cn) (X. Zhang), [yizhang@sdu.edu.cn](yizhang@sdu.edu.cn) (Y. Zhang).  \n[https://doi.org/10.1016/j.heliyon.2023.e16686](https://doi.org/10.1016/j.heliyon.2023.e16686)  \nReceived 21 February 2023; Received in revised form 22 May 2023; Accepted 24 May 2023 Available online 25 May 2023  \n2405-8440/© 2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license  \n([http://creativecommons.org/licens","cbCaioEKvTGzyWa1","https://ap.wps.com/l/cbCaioEKvTGzyWa1","pdf",1924531,"English","# Introduction\n## Prostate cancer burden and current diagnostic limits\n## Need for early diagnosis and biomarkers\n## Urine metabolomics and VOC rationale","[{\"question\":\"Why is early detection of prostate cancer challenging?\",\"answer\":\"Early diagnosis is extremely challenging due to the lack of effective diagnostic methods. PSA-based screening has limited specificity, leading to many false positives and unnecessary biopsy procedures.\"},{\"question\":\"How were volatile organic compounds (VOCs) detected in the study?\",\"answer\":\"The study used gas chromatography-ion mobility spectrometry (GC-IMS) to detect VOCs in urine samples, then compared PCa samples with non-cancer controls.\"},{\"question\":\"Which diagnostic models performed best, and what were the AUC values?\",\"answer\":\"Models built from four selected VOCs were tested using four machine learning algorithms. The RF and SVM models showed AUCs of 0.955 and 0.981, respectively, outperforming NN and DT, which had AUCs around 0.8 but weaker sensitivity or specificity.\"}]","Volatile organic compounds for early detection of prostate cancer from urine | PDF",1790221972,18]