VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC)
Background/Aim: The European Association of Urology (EAU) Guidelines recently renewed the criteria for pretreatment risk stratification as exclusion criteria for kidney-sparing surgery (KSS). The aim of the present study was to evaluate the additive value of each factor including the whole model for...
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| Veröffentlicht in: | Anticancer research 2018-04, Vol.38 (4), p.2574 |
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| creator | Soria, Francesco Foerster, Beat Matin, Surena F Seisen, Thomas Xylinas, Evanguelos Kimura, Shoji Monteiro, Leonardo L Azizi, Mounsif Bandini, Marco Clinton, Timothy Hendricksen, Kees Ku, Ja H Grabbert, Markus Czech, Anna K Mathieu, Romain Muilwijk, Tim Anele, Uzoma Petros, Firas Krabbe, Laura-Maria Rouprêt, Morgan Briganti, Alberto Heidenreich, Axel Pycha, Armin Autorino, Riccardo Egawa, Shin Spiess, Philippe E Joniau, Steven Kassouf, Wassim Shariat, Shahrokh F |
| description | Background/Aim: The European Association of Urology (EAU) Guidelines recently renewed the criteria for pretreatment risk stratification as exclusion criteria for kidney-sparing surgery (KSS). The aim of the present study was to evaluate the additive value of each factor including the whole model for identifying advanced pathologic stage after RNU. Materials and Methods: We conducted a multi-institutional retrospective study that included 406 patients who underwent ureterorenoscopy with biopsy followed by radical nephroureterectomy (RNU) for non-metastatic UTUC between 2000 and 2017. Patients who received preoperative chemotherapy were excluded. We performed logistic regression analyses with area under the curve receiver operating characteristics (AUC-ROC) to compare the different factors in predicting ≥pT2 pathologic stage. Furthermore, we conducted decision curve analysis to assess the clinical net benefit and net reduction. Results: Overall, 146 (35.6%) patients had a high-grade biopsy, 94 (23.2%) high-grade cytology, 39 (9.6%) invasive disease in computed tomography urography (CTU), 201 (49.5%) tumor size >2 cm, 112 (27.6%) preoperative hydronephrosis, 18 (4.4%) previous cystectomy and 80 (19.7%) multifocal disease. The final RNU pathology revealed 173 (42.6%) patients with ≥pT2 disease. In a preoperative multivariable model, biopsy high-grade [odds ratio (OR)=4.44, p2 cm. Preoperative hydronephrosis, previous cystectomy and multifocality did not convey any clinical net benefit nor net reduction to this model. Conclusion: High-grade ureteroscopic biopsy and cytology, CTU invasion and tumor size >2cm seem to be the best factors to identify patients who harbor muscle-invasive disease within a box model. The additive value of preoperative hydronephrosis, previous cystectomy and tumor multifocality could be limited. Further biomarkers are needed to best identify the |
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| fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2138071272</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2138071272</sourcerecordid><originalsourceid>FETCH-proquest_journals_21380712723</originalsourceid><addsrcrecordid>eNqNy0FOwzAQhWELgdTQcoeR2MAikpModbscOZPWamJHkzHbikW7qBCFhh6Am2MJDsDqLb7_3aisMOsiN3Wlb1Wmy1rnRut6pu6n6aT1crleVZn6fsHONSgueAgtDEy5MKH05AXYjTsYhRO3zv5GAzL2JMQjoLWBG-c3IAEII2yia6hznkZIZRwGYkhvKxA5yDYRdmCRrfOhR3iKEu3zQt0dX9-mw8PfztVjS2K3-cfl_Hk9TF_70_l6eU-0L4tqpU1RmrL6X_UDF6xFtQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2138071272</pqid></control><display><type>article</type><title>VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC)</title><source>EZB-FREE-00999 freely available EZB journals</source><creator>Soria, Francesco ; Foerster, Beat ; Matin, Surena F ; Seisen, Thomas ; Xylinas, Evanguelos ; Kimura, Shoji ; Monteiro, Leonardo L ; Azizi, Mounsif ; Bandini, Marco ; Clinton, Timothy ; Hendricksen, Kees ; Ku, Ja H ; Grabbert, Markus ; Czech, Anna K ; Mathieu, Romain ; Muilwijk, Tim ; Anele, Uzoma ; Petros, Firas ; Krabbe, Laura-Maria ; Rouprêt, Morgan ; Briganti, Alberto ; Heidenreich, Axel ; Pycha, Armin ; Autorino, Riccardo ; Egawa, Shin ; Spiess, Philippe E ; Joniau, Steven ; Kassouf, Wassim ; Shariat, Shahrokh F</creator><creatorcontrib>Soria, Francesco ; Foerster, Beat ; Matin, Surena F ; Seisen, Thomas ; Xylinas, Evanguelos ; Kimura, Shoji ; Monteiro, Leonardo L ; Azizi, Mounsif ; Bandini, Marco ; Clinton, Timothy ; Hendricksen, Kees ; Ku, Ja H ; Grabbert, Markus ; Czech, Anna K ; Mathieu, Romain ; Muilwijk, Tim ; Anele, Uzoma ; Petros, Firas ; Krabbe, Laura-Maria ; Rouprêt, Morgan ; Briganti, Alberto ; Heidenreich, Axel ; Pycha, Armin ; Autorino, Riccardo ; Egawa, Shin ; Spiess, Philippe E ; Joniau, Steven ; Kassouf, Wassim ; Shariat, Shahrokh F</creatorcontrib><description>Background/Aim: The European Association of Urology (EAU) Guidelines recently renewed the criteria for pretreatment risk stratification as exclusion criteria for kidney-sparing surgery (KSS). The aim of the present study was to evaluate the additive value of each factor including the whole model for identifying advanced pathologic stage after RNU. Materials and Methods: We conducted a multi-institutional retrospective study that included 406 patients who underwent ureterorenoscopy with biopsy followed by radical nephroureterectomy (RNU) for non-metastatic UTUC between 2000 and 2017. Patients who received preoperative chemotherapy were excluded. We performed logistic regression analyses with area under the curve receiver operating characteristics (AUC-ROC) to compare the different factors in predicting ≥pT2 pathologic stage. Furthermore, we conducted decision curve analysis to assess the clinical net benefit and net reduction. Results: Overall, 146 (35.6%) patients had a high-grade biopsy, 94 (23.2%) high-grade cytology, 39 (9.6%) invasive disease in computed tomography urography (CTU), 201 (49.5%) tumor size >2 cm, 112 (27.6%) preoperative hydronephrosis, 18 (4.4%) previous cystectomy and 80 (19.7%) multifocal disease. The final RNU pathology revealed 173 (42.6%) patients with ≥pT2 disease. In a preoperative multivariable model, biopsy high-grade [odds ratio (OR)=4.44, p<0.001], CTU invasion (OR=4.19, p<0.001), tumor size >2 cm (OR=1.75, p=0.013) and high-grade cytology (OR=1.72, p=0.039) were independently associated with muscle-invasive pathologic stage. On the other hand, preoperative hydronephrosis, previous cystectomy and multifocality were not. The addition of these three factors improved the model’s accuracy from 74 to 75% and the negative predictive value (NPV) from 89 to 90%. Decision curve analyses showed a maximum clinical net benefit of 0.19 at the threshold probability of 0.25 for the model with biopsy grade, cytology, CTU invasion and tumor size >2 cm. Preoperative hydronephrosis, previous cystectomy and multifocality did not convey any clinical net benefit nor net reduction to this model. Conclusion: High-grade ureteroscopic biopsy and cytology, CTU invasion and tumor size >2cm seem to be the best factors to identify patients who harbor muscle-invasive disease within a box model. The additive value of preoperative hydronephrosis, previous cystectomy and tumor multifocality could be limited. Further biomarkers are needed to best identify the patients who could most likely benefit from endoscopic KSS.</description><identifier>ISSN: 0250-7005</identifier><identifier>EISSN: 1791-7530</identifier><language>eng</language><publisher>Athens: International Institute of Anticancer Research</publisher><subject>Biomarkers ; Biopsy ; Bladder cancer ; Cellular biology ; Chemotherapy ; Computed tomography ; Cytology ; Decision analysis ; Guidelines ; Identification methods ; Invasiveness ; Mathematical models ; Metastases ; Model accuracy ; Muscles ; Patients ; Reduction ; Regression analysis ; Statistical analysis ; Surgery ; Tumors ; Urography ; Urology ; Urothelial carcinoma</subject><ispartof>Anticancer research, 2018-04, Vol.38 (4), p.2574</ispartof><rights>Copyright International Institute of Anticancer Research Apr 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Soria, Francesco</creatorcontrib><creatorcontrib>Foerster, Beat</creatorcontrib><creatorcontrib>Matin, Surena F</creatorcontrib><creatorcontrib>Seisen, Thomas</creatorcontrib><creatorcontrib>Xylinas, Evanguelos</creatorcontrib><creatorcontrib>Kimura, Shoji</creatorcontrib><creatorcontrib>Monteiro, Leonardo L</creatorcontrib><creatorcontrib>Azizi, Mounsif</creatorcontrib><creatorcontrib>Bandini, Marco</creatorcontrib><creatorcontrib>Clinton, Timothy</creatorcontrib><creatorcontrib>Hendricksen, Kees</creatorcontrib><creatorcontrib>Ku, Ja H</creatorcontrib><creatorcontrib>Grabbert, Markus</creatorcontrib><creatorcontrib>Czech, Anna K</creatorcontrib><creatorcontrib>Mathieu, Romain</creatorcontrib><creatorcontrib>Muilwijk, Tim</creatorcontrib><creatorcontrib>Anele, Uzoma</creatorcontrib><creatorcontrib>Petros, Firas</creatorcontrib><creatorcontrib>Krabbe, Laura-Maria</creatorcontrib><creatorcontrib>Rouprêt, Morgan</creatorcontrib><creatorcontrib>Briganti, Alberto</creatorcontrib><creatorcontrib>Heidenreich, Axel</creatorcontrib><creatorcontrib>Pycha, Armin</creatorcontrib><creatorcontrib>Autorino, Riccardo</creatorcontrib><creatorcontrib>Egawa, Shin</creatorcontrib><creatorcontrib>Spiess, Philippe E</creatorcontrib><creatorcontrib>Joniau, Steven</creatorcontrib><creatorcontrib>Kassouf, Wassim</creatorcontrib><creatorcontrib>Shariat, Shahrokh F</creatorcontrib><title>VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC)</title><title>Anticancer research</title><description>Background/Aim: The European Association of Urology (EAU) Guidelines recently renewed the criteria for pretreatment risk stratification as exclusion criteria for kidney-sparing surgery (KSS). The aim of the present study was to evaluate the additive value of each factor including the whole model for identifying advanced pathologic stage after RNU. Materials and Methods: We conducted a multi-institutional retrospective study that included 406 patients who underwent ureterorenoscopy with biopsy followed by radical nephroureterectomy (RNU) for non-metastatic UTUC between 2000 and 2017. Patients who received preoperative chemotherapy were excluded. We performed logistic regression analyses with area under the curve receiver operating characteristics (AUC-ROC) to compare the different factors in predicting ≥pT2 pathologic stage. Furthermore, we conducted decision curve analysis to assess the clinical net benefit and net reduction. Results: Overall, 146 (35.6%) patients had a high-grade biopsy, 94 (23.2%) high-grade cytology, 39 (9.6%) invasive disease in computed tomography urography (CTU), 201 (49.5%) tumor size >2 cm, 112 (27.6%) preoperative hydronephrosis, 18 (4.4%) previous cystectomy and 80 (19.7%) multifocal disease. The final RNU pathology revealed 173 (42.6%) patients with ≥pT2 disease. In a preoperative multivariable model, biopsy high-grade [odds ratio (OR)=4.44, p<0.001], CTU invasion (OR=4.19, p<0.001), tumor size >2 cm (OR=1.75, p=0.013) and high-grade cytology (OR=1.72, p=0.039) were independently associated with muscle-invasive pathologic stage. On the other hand, preoperative hydronephrosis, previous cystectomy and multifocality were not. The addition of these three factors improved the model’s accuracy from 74 to 75% and the negative predictive value (NPV) from 89 to 90%. Decision curve analyses showed a maximum clinical net benefit of 0.19 at the threshold probability of 0.25 for the model with biopsy grade, cytology, CTU invasion and tumor size >2 cm. Preoperative hydronephrosis, previous cystectomy and multifocality did not convey any clinical net benefit nor net reduction to this model. Conclusion: High-grade ureteroscopic biopsy and cytology, CTU invasion and tumor size >2cm seem to be the best factors to identify patients who harbor muscle-invasive disease within a box model. The additive value of preoperative hydronephrosis, previous cystectomy and tumor multifocality could be limited. Further biomarkers are needed to best identify the patients who could most likely benefit from endoscopic KSS.</description><subject>Biomarkers</subject><subject>Biopsy</subject><subject>Bladder cancer</subject><subject>Cellular biology</subject><subject>Chemotherapy</subject><subject>Computed tomography</subject><subject>Cytology</subject><subject>Decision analysis</subject><subject>Guidelines</subject><subject>Identification methods</subject><subject>Invasiveness</subject><subject>Mathematical models</subject><subject>Metastases</subject><subject>Model accuracy</subject><subject>Muscles</subject><subject>Patients</subject><subject>Reduction</subject><subject>Regression analysis</subject><subject>Statistical analysis</subject><subject>Surgery</subject><subject>Tumors</subject><subject>Urography</subject><subject>Urology</subject><subject>Urothelial carcinoma</subject><issn>0250-7005</issn><issn>1791-7530</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqNy0FOwzAQhWELgdTQcoeR2MAikpModbscOZPWamJHkzHbikW7qBCFhh6Am2MJDsDqLb7_3aisMOsiN3Wlb1Wmy1rnRut6pu6n6aT1crleVZn6fsHONSgueAgtDEy5MKH05AXYjTsYhRO3zv5GAzL2JMQjoLWBG-c3IAEII2yia6hznkZIZRwGYkhvKxA5yDYRdmCRrfOhR3iKEu3zQt0dX9-mw8PfztVjS2K3-cfl_Hk9TF_70_l6eU-0L4tqpU1RmrL6X_UDF6xFtQ</recordid><startdate>20180401</startdate><enddate>20180401</enddate><creator>Soria, Francesco</creator><creator>Foerster, Beat</creator><creator>Matin, Surena F</creator><creator>Seisen, Thomas</creator><creator>Xylinas, Evanguelos</creator><creator>Kimura, Shoji</creator><creator>Monteiro, Leonardo L</creator><creator>Azizi, Mounsif</creator><creator>Bandini, Marco</creator><creator>Clinton, Timothy</creator><creator>Hendricksen, Kees</creator><creator>Ku, Ja H</creator><creator>Grabbert, Markus</creator><creator>Czech, Anna K</creator><creator>Mathieu, Romain</creator><creator>Muilwijk, Tim</creator><creator>Anele, Uzoma</creator><creator>Petros, Firas</creator><creator>Krabbe, Laura-Maria</creator><creator>Rouprêt, Morgan</creator><creator>Briganti, Alberto</creator><creator>Heidenreich, Axel</creator><creator>Pycha, Armin</creator><creator>Autorino, Riccardo</creator><creator>Egawa, Shin</creator><creator>Spiess, Philippe E</creator><creator>Joniau, Steven</creator><creator>Kassouf, Wassim</creator><creator>Shariat, Shahrokh F</creator><general>International Institute of Anticancer Research</general><scope>7QO</scope><scope>7T5</scope><scope>7TM</scope><scope>7TO</scope><scope>7U7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope></search><sort><creationdate>20180401</creationdate><title>VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC)</title><author>Soria, Francesco ; Foerster, Beat ; Matin, Surena F ; Seisen, Thomas ; Xylinas, Evanguelos ; Kimura, Shoji ; Monteiro, Leonardo L ; Azizi, Mounsif ; Bandini, Marco ; Clinton, Timothy ; Hendricksen, Kees ; Ku, Ja H ; Grabbert, Markus ; Czech, Anna K ; Mathieu, Romain ; Muilwijk, Tim ; Anele, Uzoma ; Petros, Firas ; Krabbe, Laura-Maria ; Rouprêt, Morgan ; Briganti, Alberto ; Heidenreich, Axel ; Pycha, Armin ; Autorino, Riccardo ; Egawa, Shin ; Spiess, Philippe E ; Joniau, Steven ; Kassouf, Wassim ; Shariat, Shahrokh F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_21380712723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Biomarkers</topic><topic>Biopsy</topic><topic>Bladder cancer</topic><topic>Cellular biology</topic><topic>Chemotherapy</topic><topic>Computed tomography</topic><topic>Cytology</topic><topic>Decision analysis</topic><topic>Guidelines</topic><topic>Identification methods</topic><topic>Invasiveness</topic><topic>Mathematical models</topic><topic>Metastases</topic><topic>Model accuracy</topic><topic>Muscles</topic><topic>Patients</topic><topic>Reduction</topic><topic>Regression analysis</topic><topic>Statistical analysis</topic><topic>Surgery</topic><topic>Tumors</topic><topic>Urography</topic><topic>Urology</topic><topic>Urothelial carcinoma</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Soria, Francesco</creatorcontrib><creatorcontrib>Foerster, Beat</creatorcontrib><creatorcontrib>Matin, Surena F</creatorcontrib><creatorcontrib>Seisen, Thomas</creatorcontrib><creatorcontrib>Xylinas, Evanguelos</creatorcontrib><creatorcontrib>Kimura, Shoji</creatorcontrib><creatorcontrib>Monteiro, Leonardo L</creatorcontrib><creatorcontrib>Azizi, Mounsif</creatorcontrib><creatorcontrib>Bandini, Marco</creatorcontrib><creatorcontrib>Clinton, Timothy</creatorcontrib><creatorcontrib>Hendricksen, Kees</creatorcontrib><creatorcontrib>Ku, Ja H</creatorcontrib><creatorcontrib>Grabbert, Markus</creatorcontrib><creatorcontrib>Czech, Anna K</creatorcontrib><creatorcontrib>Mathieu, Romain</creatorcontrib><creatorcontrib>Muilwijk, Tim</creatorcontrib><creatorcontrib>Anele, Uzoma</creatorcontrib><creatorcontrib>Petros, Firas</creatorcontrib><creatorcontrib>Krabbe, Laura-Maria</creatorcontrib><creatorcontrib>Rouprêt, Morgan</creatorcontrib><creatorcontrib>Briganti, Alberto</creatorcontrib><creatorcontrib>Heidenreich, Axel</creatorcontrib><creatorcontrib>Pycha, Armin</creatorcontrib><creatorcontrib>Autorino, Riccardo</creatorcontrib><creatorcontrib>Egawa, Shin</creatorcontrib><creatorcontrib>Spiess, Philippe E</creatorcontrib><creatorcontrib>Joniau, Steven</creatorcontrib><creatorcontrib>Kassouf, Wassim</creatorcontrib><creatorcontrib>Shariat, Shahrokh F</creatorcontrib><collection>Biotechnology Research Abstracts</collection><collection>Immunology Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Anticancer research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Soria, Francesco</au><au>Foerster, Beat</au><au>Matin, Surena F</au><au>Seisen, Thomas</au><au>Xylinas, Evanguelos</au><au>Kimura, Shoji</au><au>Monteiro, Leonardo L</au><au>Azizi, Mounsif</au><au>Bandini, Marco</au><au>Clinton, Timothy</au><au>Hendricksen, Kees</au><au>Ku, Ja H</au><au>Grabbert, Markus</au><au>Czech, Anna K</au><au>Mathieu, Romain</au><au>Muilwijk, Tim</au><au>Anele, Uzoma</au><au>Petros, Firas</au><au>Krabbe, Laura-Maria</au><au>Rouprêt, Morgan</au><au>Briganti, Alberto</au><au>Heidenreich, Axel</au><au>Pycha, Armin</au><au>Autorino, Riccardo</au><au>Egawa, Shin</au><au>Spiess, Philippe E</au><au>Joniau, Steven</au><au>Kassouf, Wassim</au><au>Shariat, Shahrokh F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC)</atitle><jtitle>Anticancer research</jtitle><date>2018-04-01</date><risdate>2018</risdate><volume>38</volume><issue>4</issue><spage>2574</spage><pages>2574-</pages><issn>0250-7005</issn><eissn>1791-7530</eissn><abstract>Background/Aim: The European Association of Urology (EAU) Guidelines recently renewed the criteria for pretreatment risk stratification as exclusion criteria for kidney-sparing surgery (KSS). The aim of the present study was to evaluate the additive value of each factor including the whole model for identifying advanced pathologic stage after RNU. Materials and Methods: We conducted a multi-institutional retrospective study that included 406 patients who underwent ureterorenoscopy with biopsy followed by radical nephroureterectomy (RNU) for non-metastatic UTUC between 2000 and 2017. Patients who received preoperative chemotherapy were excluded. We performed logistic regression analyses with area under the curve receiver operating characteristics (AUC-ROC) to compare the different factors in predicting ≥pT2 pathologic stage. Furthermore, we conducted decision curve analysis to assess the clinical net benefit and net reduction. Results: Overall, 146 (35.6%) patients had a high-grade biopsy, 94 (23.2%) high-grade cytology, 39 (9.6%) invasive disease in computed tomography urography (CTU), 201 (49.5%) tumor size >2 cm, 112 (27.6%) preoperative hydronephrosis, 18 (4.4%) previous cystectomy and 80 (19.7%) multifocal disease. The final RNU pathology revealed 173 (42.6%) patients with ≥pT2 disease. In a preoperative multivariable model, biopsy high-grade [odds ratio (OR)=4.44, p<0.001], CTU invasion (OR=4.19, p<0.001), tumor size >2 cm (OR=1.75, p=0.013) and high-grade cytology (OR=1.72, p=0.039) were independently associated with muscle-invasive pathologic stage. On the other hand, preoperative hydronephrosis, previous cystectomy and multifocality were not. The addition of these three factors improved the model’s accuracy from 74 to 75% and the negative predictive value (NPV) from 89 to 90%. Decision curve analyses showed a maximum clinical net benefit of 0.19 at the threshold probability of 0.25 for the model with biopsy grade, cytology, CTU invasion and tumor size >2 cm. Preoperative hydronephrosis, previous cystectomy and multifocality did not convey any clinical net benefit nor net reduction to this model. Conclusion: High-grade ureteroscopic biopsy and cytology, CTU invasion and tumor size >2cm seem to be the best factors to identify patients who harbor muscle-invasive disease within a box model. The additive value of preoperative hydronephrosis, previous cystectomy and tumor multifocality could be limited. Further biomarkers are needed to best identify the patients who could most likely benefit from endoscopic KSS.</abstract><cop>Athens</cop><pub>International Institute of Anticancer Research</pub></addata></record> |
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| subjects | Biomarkers Biopsy Bladder cancer Cellular biology Chemotherapy Computed tomography Cytology Decision analysis Guidelines Identification methods Invasiveness Mathematical models Metastases Model accuracy Muscles Patients Reduction Regression analysis Statistical analysis Surgery Tumors Urography Urology Urothelial carcinoma |
| title | VALIDATION OF PRE-TREATMENT RISK STRATIFICATION PARAMETERS ACCORDING TO EAU GUIDELINES ON UPPER TRACT UROTHELIAL CARCINOMA (UTUC) |
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