Full Text Journal Articles from
Abstract 34023164


Find full text journal articles

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

PMID: 34023164 (view PubMed database entry)
DOI: 10.1016/j.eururo.2021.05.004 (read at publisher's website )

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 Czech, Tim 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 M Pierorazio, Shahrokh F Shariat,

<h4>Background</h4>Several groups have proposed features to identify low-risk patients who may benefit from endoscopic kidney-sparing surgery in upper tract urothelial carcinoma (UTUC).<h4>Objective</h4>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.<h4>Design, setting, and participants</h4>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.<h4>Outcome measurements and statistical analysis</h4>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.<h4>Results and limitations</h4>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).<h4>Conclusions</h4>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.<h4>Patient summary</h4>We developed a risk stratification model to better identify patients for endoscopic kidney-sparing surgery in upper tract urothelial carcinoma.

Eur Urol (European urology)
[2021, 80(4):507-515]

Cited: 0 times

AltMetric Statistics



0.6648 s