Background: Several groups have proposed features to identify low-risk patients who may benefit from endoscopic kidney-sparing surgery in upper tract urothelial carcinoma (UTUC).Objective: To evaluate standard risk stratification features, develop an optimal model to identify >= pT2/N+ stage at radical nephroureterectomy (RNU), and compare it with the existing unvalidated models.Design, setting, and participants: This was a collaborative retrospective study that included 1214 patients who underwent ureterorenoscopy with biopsy followed by RNU for nonmetastatic UTUC between 2000 and 2017.Outcome measurements and statistical analysis: We performed multiple imputation of chained equations for missing data and multivariable logistic regression analysis with a stepwise selection algorithm to create the optimal predictive model. The area under the curve and a decision curve analysis were used to compare the models.Results and limitations: Overall, 659 (54.3%) and 555 (45.7%) patients had <= pT1N0/Nx and >= pT2/N+ disease, respectively. In the multivariable logistic regression analysis of our model, age (odds ratio [OR] 1.02, 95% confidence interval [CI] 1.0-1.03, p = 0.013), high-grade biopsy (OR 1.81, 95% CI 1.37-2.40, p < 0.001), biopsy cT1+ staging (OR 3.23, 95% CI 1.93-5.41, p < 0.001), preoperative hydronephrosis (OR 1.37 95% CI 1.04-1.80, p = 0.024), tumor size (OR 1.09, 95% CI 1.01-1.17, p = 0.029), invasion on imaging (OR 5.10, 95% CI 3.32-7.81, p < 0.001), and sessile architecture (OR 2.31, 95% CI 1.58-3.36, p < 0.001) were significantly associated with >= pT2/pN+ disease. Compared with the existing models, our model had the highest performance accuracy (75% vs 66-71%) and an additional clinical net reduction (four per 100 patients).Conclusions: Our proposed risk-stratification model predicts the risk of harboring >= pT2/N+ UTUC with reliable accuracy and a clinical net benefit outperforming the current risk-stratification models.Patient summary: We developed a risk stratification model to better identify patients for endoscopic kidney-sparing surgery in upper tract urothelial carcinoma. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology.

Pretreatment Risk Stratification for Endoscopic Kidney-sparing Surgery in Upper Tract Urothelial Carcinoma: An International Collaborative Study / Foerster, Beat; Abufaraj, Mohammad; Matin, Surena F; Azizi, Mounsif; Gupta, Mohit; Li, Wei-Ming; Seisen, Thomas; Clinton, Timothy; Xylinas, Evanguelos; Mir, M Carmen; Schweitzer, Donald; Mari, Andrea; Kimura, Shoji; Bandini, Marco; Mathieu, Romain; Ku, Ja H; Marcq, Gautier; Guruli, Georgi; Grabbert, Markus; Czech, Anna K; Muilwijk, Tim; Pycha, Armin; D'Andrea, David; Petros, Firas G; Spiess, Philippe E; Bivalacqua, Trinity; Wu, Wen-Jeng; Rouprêt, Morgan; Krabbe, Laura-Maria; Hendricksen, Kees; Egawa, Shin; Briganti, Alberto; Moschini, Marco; Graffeille, Vivien; Kassouf, Wassim; Autorino, Riccardo; Heidenreich, Axel; Chlosta, Piotr; Joniau, Steven; Soria, Francesco; Pierorazio, Phillip M; Shariat, Shahrokh F. - In: EUROPEAN UROLOGY. - ISSN 0302-2838. - ELETTRONICO. - 80:(2021), pp. 507-515. [10.1016/j.eururo.2021.05.004]

Pretreatment Risk Stratification for Endoscopic Kidney-sparing Surgery in Upper Tract Urothelial Carcinoma: An International Collaborative Study

Mari, Andrea;
2021

Abstract

Background: Several groups have proposed features to identify low-risk patients who may benefit from endoscopic kidney-sparing surgery in upper tract urothelial carcinoma (UTUC).Objective: To evaluate standard risk stratification features, develop an optimal model to identify >= pT2/N+ stage at radical nephroureterectomy (RNU), and compare it with the existing unvalidated models.Design, setting, and participants: This was a collaborative retrospective study that included 1214 patients who underwent ureterorenoscopy with biopsy followed by RNU for nonmetastatic UTUC between 2000 and 2017.Outcome measurements and statistical analysis: We performed multiple imputation of chained equations for missing data and multivariable logistic regression analysis with a stepwise selection algorithm to create the optimal predictive model. The area under the curve and a decision curve analysis were used to compare the models.Results and limitations: Overall, 659 (54.3%) and 555 (45.7%) patients had <= pT1N0/Nx and >= pT2/N+ disease, respectively. In the multivariable logistic regression analysis of our model, age (odds ratio [OR] 1.02, 95% confidence interval [CI] 1.0-1.03, p = 0.013), high-grade biopsy (OR 1.81, 95% CI 1.37-2.40, p < 0.001), biopsy cT1+ staging (OR 3.23, 95% CI 1.93-5.41, p < 0.001), preoperative hydronephrosis (OR 1.37 95% CI 1.04-1.80, p = 0.024), tumor size (OR 1.09, 95% CI 1.01-1.17, p = 0.029), invasion on imaging (OR 5.10, 95% CI 3.32-7.81, p < 0.001), and sessile architecture (OR 2.31, 95% CI 1.58-3.36, p < 0.001) were significantly associated with >= pT2/pN+ disease. Compared with the existing models, our model had the highest performance accuracy (75% vs 66-71%) and an additional clinical net reduction (four per 100 patients).Conclusions: Our proposed risk-stratification model predicts the risk of harboring >= pT2/N+ UTUC with reliable accuracy and a clinical net benefit outperforming the current risk-stratification models.Patient summary: We developed a risk stratification model to better identify patients for endoscopic kidney-sparing surgery in upper tract urothelial carcinoma. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology.
2021
80
507
515
Foerster, Beat; Abufaraj, Mohammad; Matin, Surena F; Azizi, Mounsif; Gupta, Mohit; Li, Wei-Ming; Seisen, Thomas; Clinton, Timothy; Xylinas, Evanguelos; Mir, M Carmen; Schweitzer, Donald; Mari, Andrea; Kimura, Shoji; Bandini, Marco; Mathieu, Romain; Ku, Ja H; Marcq, Gautier; Guruli, Georgi; Grabbert, Markus; Czech, Anna K; Muilwijk, Tim; Pycha, Armin; D'Andrea, David; Petros, Firas G; Spiess, Philippe E; Bivalacqua, Trinity; Wu, Wen-Jeng; Rouprêt, Morgan; Krabbe, Laura-Maria; Hendricksen, Kees; Egawa, Shin; Briganti, Alberto; Moschini, Marco; Graffeille, Vivien; Kassouf, Wassim; Autorino, Riccardo; Heidenreich, Axel; Chlosta, Piotr; Joniau, Steven; Soria, Francesco; Pierorazio, Phillip M; Shariat, Shahrokh F
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1287832
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