Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions
Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (Th...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Can Hu [verfasserIn] Jiale Sun [verfasserIn] Zhenyu Xu [verfasserIn] Zhiyu Zhang [verfasserIn] Qi Zhou [verfasserIn] Jiangnan Xu [verfasserIn] Hao Chen [verfasserIn] Chao Wang [verfasserIn] Jun Ouyang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Cancer Medicine - Wiley, 2012, 12(2023), 3, Seite 2560-2571 |
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| Übergeordnetes Werk: |
volume:12 ; year:2023 ; number:3 ; pages:2560-2571 |
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| DOI / URN: |
10.1002/cam4.5100 |
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| Katalog-ID: |
DOAJ079893961 |
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| 245 | 1 | 0 | |a Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
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| 520 | |a Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. | ||
| 650 | 4 | |a csPCa | |
| 650 | 4 | |a equivocal lesions | |
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| 653 | 0 | |a Neoplasms. Tumors. Oncology. Including cancer and carcinogens | |
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| 700 | 0 | |a Jiangnan Xu |e verfasserin |4 aut | |
| 700 | 0 | |a Hao Chen |e verfasserin |4 aut | |
| 700 | 0 | |a Chao Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Jun Ouyang |e verfasserin |4 aut | |
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10.1002/cam4.5100 doi (DE-627)DOAJ079893961 (DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7 DE-627 ger DE-627 rakwb eng RC254-282 Can Hu verfasserin aut Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. csPCa equivocal lesions nomogram PI‐RADS v2.1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jiale Sun verfasserin aut Zhenyu Xu verfasserin aut Zhiyu Zhang verfasserin aut Qi Zhou verfasserin aut Jiangnan Xu verfasserin aut Hao Chen verfasserin aut Chao Wang verfasserin aut Jun Ouyang verfasserin aut In Cancer Medicine Wiley, 2012 12(2023), 3, Seite 2560-2571 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:12 year:2023 number:3 pages:2560-2571 https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 kostenfrei https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 3 2560-2571 |
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10.1002/cam4.5100 doi (DE-627)DOAJ079893961 (DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7 DE-627 ger DE-627 rakwb eng RC254-282 Can Hu verfasserin aut Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. csPCa equivocal lesions nomogram PI‐RADS v2.1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jiale Sun verfasserin aut Zhenyu Xu verfasserin aut Zhiyu Zhang verfasserin aut Qi Zhou verfasserin aut Jiangnan Xu verfasserin aut Hao Chen verfasserin aut Chao Wang verfasserin aut Jun Ouyang verfasserin aut In Cancer Medicine Wiley, 2012 12(2023), 3, Seite 2560-2571 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:12 year:2023 number:3 pages:2560-2571 https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 kostenfrei https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 3 2560-2571 |
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10.1002/cam4.5100 doi (DE-627)DOAJ079893961 (DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7 DE-627 ger DE-627 rakwb eng RC254-282 Can Hu verfasserin aut Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. csPCa equivocal lesions nomogram PI‐RADS v2.1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jiale Sun verfasserin aut Zhenyu Xu verfasserin aut Zhiyu Zhang verfasserin aut Qi Zhou verfasserin aut Jiangnan Xu verfasserin aut Hao Chen verfasserin aut Chao Wang verfasserin aut Jun Ouyang verfasserin aut In Cancer Medicine Wiley, 2012 12(2023), 3, Seite 2560-2571 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:12 year:2023 number:3 pages:2560-2571 https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 kostenfrei https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 3 2560-2571 |
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10.1002/cam4.5100 doi (DE-627)DOAJ079893961 (DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7 DE-627 ger DE-627 rakwb eng RC254-282 Can Hu verfasserin aut Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. csPCa equivocal lesions nomogram PI‐RADS v2.1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jiale Sun verfasserin aut Zhenyu Xu verfasserin aut Zhiyu Zhang verfasserin aut Qi Zhou verfasserin aut Jiangnan Xu verfasserin aut Hao Chen verfasserin aut Chao Wang verfasserin aut Jun Ouyang verfasserin aut In Cancer Medicine Wiley, 2012 12(2023), 3, Seite 2560-2571 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:12 year:2023 number:3 pages:2560-2571 https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 kostenfrei https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 3 2560-2571 |
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10.1002/cam4.5100 doi (DE-627)DOAJ079893961 (DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7 DE-627 ger DE-627 rakwb eng RC254-282 Can Hu verfasserin aut Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. csPCa equivocal lesions nomogram PI‐RADS v2.1 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jiale Sun verfasserin aut Zhenyu Xu verfasserin aut Zhiyu Zhang verfasserin aut Qi Zhou verfasserin aut Jiangnan Xu verfasserin aut Hao Chen verfasserin aut Chao Wang verfasserin aut Jun Ouyang verfasserin aut In Cancer Medicine Wiley, 2012 12(2023), 3, Seite 2560-2571 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:12 year:2023 number:3 pages:2560-2571 https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 kostenfrei https://doi.org/10.1002/cam4.5100 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 12 2023 3 2560-2571 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ079893961</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230310173718.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230310s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/cam4.5100</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ079893961</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJe2fd87cd6fcd4333816ae7a2a85f5ea7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC254-282</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Can Hu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. 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Can Hu |
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Can Hu misc RC254-282 misc csPCa misc equivocal lesions misc nomogram misc PI‐RADS v2.1 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
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RC254-282 Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions csPCa equivocal lesions nomogram PI‐RADS v2.1 |
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misc RC254-282 misc csPCa misc equivocal lesions misc nomogram misc PI‐RADS v2.1 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
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Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
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Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
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Can Hu Jiale Sun Zhenyu Xu Zhiyu Zhang Qi Zhou Jiangnan Xu Hao Chen Chao Wang Jun Ouyang |
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development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with psa <10 ng/ml and pi‐rads v2.1 = 3 lesions |
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RC254-282 |
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Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
| abstract |
Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. |
| abstractGer |
Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. |
| abstract_unstemmed |
Abstract Objective To develop and externally validate a novel nomogram in biopsy‐naïve patients with prostate‐specific antigen (PSA) <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Methods We retrospectively collected 307 men that underwent initial biopsy from October 2015 to January 2022 in Cohort 1 (The First Affiliated Hospital of Soochow University). External cohort (Cohort 2, Kunshan Hospital) included 109 men that met our criteria from July 2016 to June 2021. By Slicer‐3D Software, the volume of all lesions was divided into two subgroups (PI‐RADS v2.1 = 3a and 3b). Logistic regression analysis was performed to screen for variables and construct nomogram by analyzing clinical data from Cohort 1. Receiver operating characteristics curve analysis, calibration plot and decision curve analysis (DCA) were plotted to validate the nomogram in external cohort. Results A total of 70 (22.8%) patients was diagnosed with prostate cancer in Institution 1. Among them, 34 (11.1%) had clinically significant prostate cancer (csPCa). Age, prostate‐specific antigen density, digital rectal examination, PI‐RADS v2.1 = 3 subgroups (3a and 3b) and apparent diffusion coefficient (ADC, <750 mm2/s) were predictive factors for prostate cancer (PCa) and csPCa. High area under the curve of the nomogram was found in Cohort 1 and Cohort 2 for PCa (0.857 vs. 0.850) and for csPCa (0.896 vs. 0.893). Calibration curves showed excellent agreement between the predicted probability and actual risk for the models in internal and external validation. The DCA demonstrated net benefit of our nomogram. Conclusion Until now, this is the first nomogram that predicts PCa and csPCa in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions. Furthermore, PI‐RADS v2.1 = 3 subgroups were considered to be an independent risk factor in our model. Our nomogram may assist urologists in biopsy decision making for these so‐called “double gray zone” patients. |
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Development and external validation of a novel nomogram to predict prostate cancer in biopsy‐naïve patients with PSA <10 ng/ml and PI‐RADS v2.1 = 3 lesions |
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https://doi.org/10.1002/cam4.5100 https://doaj.org/article/e2fd87cd6fcd4333816ae7a2a85f5ea7 https://doaj.org/toc/2045-7634 |
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Jiale Sun Zhenyu Xu Zhiyu Zhang Qi Zhou Jiangnan Xu Hao Chen Chao Wang Jun Ouyang |
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Jiale Sun Zhenyu Xu Zhiyu Zhang Qi Zhou Jiangnan Xu Hao Chen Chao Wang Jun Ouyang |
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2024-07-04T01:14:11.692Z |
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