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

Beat Foerster, Mohammad Abufaraj, Surena F. Matin, Mounsif Azizi, Mohit Gupta, Wei Ming Li, Thomas Seisen, Timothy Clinton, Evanguelos Xylinas, M. Carmen Mir, Donald Schweitzer, Andrea Mari, Shoji Kimura, Marco Bandini, Romain Mathieu, Ja H. Ku, Gautier Marcq, Georgi Guruli, Markus Grabbert, Anna K. CzechTim Muilwijk, Armin Pycha, David D'Andrea, Firas G. Petros, Philippe E. Spiess, Trinity Bivalacqua, Wen Jeng Wu, Morgan Rouprêt, Laura Maria Krabbe, Kees Hendricksen, Shin Egawa, Alberto Briganti, Marco Moschini, Vivien Graffeille, Wassim Kassouf, Riccardo Autorino, Axel Heidenreich, Piotr Chlosta, Steven Joniau, Francesco Soria, Phillip Martin Pierorazio, Shahrokh F. Shariat

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
JournalEuropean Urology
DOIs
StateAccepted/In press - 2021

Keywords

  • Kidney-sparing surgery
  • Radical nephroureterectomy
  • Risk stratification
  • Upper tract urothelial carcinoma

ASJC Scopus subject areas

  • Urology

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