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Clinical data from 198 patients (June 2022 to June 2024) are analyzed by univariate and multivariate logistic regression, then modeled using integrated imaging and clinical variables. The resulting nomogram evaluates discrimination and calibration through ROC analysis with reported AUC and C-index performance.",{"@graph":69,"@context":122},[70,84,105],{"@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/enhanced-precision-in-prostate-surgery-determining-key-factors-for-rectal-positive-surgical-margins-through-integrated-imaging-and-clinical-data-analysis/365269/",{"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/enhanced-precision-in-prostate-surgery-determining-key-factors-for-rectal-positive-surgical-margins-through-integrated-imaging-and-clinical-data-analysis/365269.png","ImageObject",300,407,{"name":92,"@type":93},"Rhys","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What clinical problem does the study focus on?","Question",{"text":112,"@type":113},"The study focuses on risk factors for rectal positive surgical margins (RPSM) after radical prostatectomy and the development of a predictive model.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were potential predictors of RPSM identified?",{"text":117,"@type":113},"The study used univariate and multivariate logistic regression on clinical data from 198 patients to identify independent predictors of RPSM.",{"name":119,"@type":110,"acceptedAnswer":120},"Which factors were found to significantly predict RPSM?",{"text":121,"@type":113},"Multivariate logistic regression identified clinical stage, PSA level, Gleason score, bilateral prostate infiltration, and PI-RADS as significant predictors of RPSM.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},365269,1790341918,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":34,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},687207024643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","TYPE Original Research PUBLISHED 10 April 2025  \nDOI 10.3389/fsurg.2025.1563344  \nEDITED BY  \nYichen Ding,  \nThe University of Texas at Dallas, United States  \nREVIEWED BY  \nAnfu Pan,  \nAffiliated to Zhejiang Chinese Medical University, China  \nJiawei Wu,  \nJiangsu University, China  \n*CORRESPONDENCE  \nChengwei Shao  \n [cwshao@sina.com](cwshao@sina.com)[ ](cwshao@sina.com)Weiguo Chen  \n [chenweiguo1971@suda.edu.cn](chenweiguo1971@suda.edu.cn)[ ](chenweiguo1971@suda.edu.cn)Xingbo Wang  \n [dr.wxb@163.com](dr.wxb@163.com)  \n†These authors have contributed equally to this work  \nRECEIVED 08 February 2025  \nACCEPTED 24 March 2025  \nPUBLISHED 10 April 2025  \nCITATION  \nWu Y, Liu F, Ma S, Jing G, Yu Q, Yao L, Shao C, Chen W and Wang X (2025) Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis.  \nFront. Surg. 12:1563344 .  \ndoi: 10.3389/fsurg.2025.1563344  \nCOPYRIGHT  \n© 2025 Wu, Liu, Ma, Jing, Yu, Yao, Shao, Chen and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nEnhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis  \nYufan Wu1,2†, Fei Liu3†, Shiyu Ma4†, Guodong Jing4, Qiwei Yu2, Linya Yao2, Chengwei Shao4*, Weiguo Chen1* and Xingbo Wang5*  \n1Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China, 2Department of Urology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, JiangSu, China, 3Department of Urology, Kunshan Sixth People’s Hospital, Kunshan, JiangSu, China, 4Department of Radiology, Changhai Hospital, Shanghai, China, 5Department of Urology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, JiangSu, China  \nObjective: This study investigates the risk factors associated with rectal positive surgical margins (RPSM) following radical prostatectomy and aims to develop a predictive model.  \nMethods: Clinical data from 198 patients undergoing radical prostatectomy atthe Department of Urology, Kunshan Hospital of Traditional Chinese Medicine from June 2022 to June 2024 were analyzed. Patients were categorized into groups with and without RPSM. Univariate and multivariate logistic regression analyses identified independent predictors of RPSM. Utilizing R software, we generated a column chart illustrating prostate cancer’s RPSM incidence and constructed ROC curves with the area under the curve (AUC) to assess the discriminative performance and calibration of our model.  \nResults: Multivariate logistic regression identified clinical stage, PSA level, Gleason score, bilateral prostate infiltration, and PI-RADS as significant predictors of RPSM (all P \u003C 0 . 05) . Using these predictors, we developed anomogram that achieved a C-index of 0.833(95% CI: 0.785–0.887) and an AUC of 0 .755 (95% CI: 0 .645–0. 866) .  \nConclusion: The predictive model effectively forecasts the likelihood of RPSM following radical prostatectomy, offering valuable insights for personalized patient management.  \nKEYWORDS  \nprostate cancer, radical prostatectomy, rectal positive surgical margins, predictive model, PI-RADS  \n1 Introduction  \nProstate cancer (PCa) is a prevalent malignancy among men, ranking second in mortality largely due to its high propensity (65%–75%) for bone metastasis (1) . Studies highlight that Positive Surgical Margin (PSM) represents a significant challenge in radical prostatectomy for PCa (2), serving as a crucial indicator ","cbCaiqof1Y3v5gJM","https://ap.wps.com/l/cbCaiqof1Y3v5gJM","pdf",527282,"English","# Objective\n# Methods\n# Results\n# Conclusion\n# Introduction","[{\"question\":\"What clinical problem does the study focus on?\",\"answer\":\"The study focuses on risk factors for rectal positive surgical margins (RPSM) after radical prostatectomy and the development of a predictive model.\"},{\"question\":\"How were potential predictors of RPSM identified?\",\"answer\":\"The study used univariate and multivariate logistic regression on clinical data from 198 patients to identify independent predictors of RPSM.\"},{\"question\":\"Which factors were found to significantly predict RPSM?\",\"answer\":\"Multivariate logistic regression identified clinical stage, PSA level, Gleason score, bilateral prostate infiltration, and PI-RADS as significant predictors of RPSM.\"}]","Enhanced precision in prostate surgery - determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis | PDF",1790160514,18]