Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis
ObjectiveThis study investigates the risk factors associated with rectal positive surgical margins (RPSM) following radical prostatectomy and aims to develop a predictive model.MethodsClinical data from 198 patients undergoing radical prostatectomy at the Department of Urology, Kunshan Hospital of T...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Surgery |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fsurg.2025.1563344/full |
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| author | Yufan Wu Yufan Wu Fei Liu Shiyu Ma Guodong Jing Qiwei Yu Linya Yao Chengwei Shao Weiguo Chen Xingbo Wang |
| author_facet | Yufan Wu Yufan Wu Fei Liu Shiyu Ma Guodong Jing Qiwei Yu Linya Yao Chengwei Shao Weiguo Chen Xingbo Wang |
| author_sort | Yufan Wu |
| collection | DOAJ |
| description | ObjectiveThis study investigates the risk factors associated with rectal positive surgical margins (RPSM) following radical prostatectomy and aims to develop a predictive model.MethodsClinical data from 198 patients undergoing radical prostatectomy at the 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.ResultsMultivariate logistic regression identified clinical stage, PSA level, Gleason score, bilateral prostate infiltration, and PI-RADS as significant predictors of RPSM (all P < 0.05). Using these predictors, we developed a nomogram 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).ConclusionThe predictive model effectively forecasts the likelihood of RPSM following radical prostatectomy, offering valuable insights for personalized patient management. |
| format | Article |
| id | doaj-art-bc04fb8d8ea542d99d212442354b013b |
| institution | DOAJ |
| issn | 2296-875X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Surgery |
| spelling | doaj-art-bc04fb8d8ea542d99d212442354b013b2025-08-20T03:05:21ZengFrontiers Media S.A.Frontiers in Surgery2296-875X2025-04-011210.3389/fsurg.2025.15633441563344Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysisYufan Wu0Yufan Wu1Fei Liu2Shiyu Ma3Guodong Jing4Qiwei Yu5Linya Yao6Chengwei Shao7Weiguo Chen8Xingbo Wang9Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Urology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, JiangSu, ChinaDepartment of Urology, Kunshan Sixth People’s Hospital, Kunshan, JiangSu, ChinaDepartment of Radiology, Changhai Hospital, Shanghai, ChinaDepartment of Radiology, Changhai Hospital, Shanghai, ChinaDepartment of Urology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, JiangSu, ChinaDepartment of Urology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, JiangSu, ChinaDepartment of Radiology, Changhai Hospital, Shanghai, ChinaDepartment of Urology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Urology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, JiangSu, ChinaObjectiveThis study investigates the risk factors associated with rectal positive surgical margins (RPSM) following radical prostatectomy and aims to develop a predictive model.MethodsClinical data from 198 patients undergoing radical prostatectomy at the 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.ResultsMultivariate logistic regression identified clinical stage, PSA level, Gleason score, bilateral prostate infiltration, and PI-RADS as significant predictors of RPSM (all P < 0.05). Using these predictors, we developed a nomogram 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).ConclusionThe predictive model effectively forecasts the likelihood of RPSM following radical prostatectomy, offering valuable insights for personalized patient management.https://www.frontiersin.org/articles/10.3389/fsurg.2025.1563344/fullprostate cancerradical prostatectomyrectal positive surgical marginspredictive modelPI-RADS |
| spellingShingle | Yufan Wu Yufan Wu Fei Liu Shiyu Ma Guodong Jing Qiwei Yu Linya Yao Chengwei Shao Weiguo Chen Xingbo Wang Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis Frontiers in Surgery prostate cancer radical prostatectomy rectal positive surgical margins predictive model PI-RADS |
| title | Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| title_full | Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| title_fullStr | Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| title_full_unstemmed | Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| title_short | Enhanced precision in prostate surgery: determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| title_sort | enhanced precision in prostate surgery determining key factors for rectal positive surgical margins through integrated imaging and clinical data analysis |
| topic | prostate cancer radical prostatectomy rectal positive surgical margins predictive model PI-RADS |
| url | https://www.frontiersin.org/articles/10.3389/fsurg.2025.1563344/full |
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