@article{TAU11795,
author = {Zine-Eddine Khene and Romain Mathieu and Solène-Florence Kammerer-Jacquet and Thomas Seisen and Morgan Roupret and Shahrokh F. Shariat and Benoit Peyronnet and Karim Bensalah},
title = {Risk stratification for kidney sparing procedure in upper tract urothelial carcinoma},
journal = {Translational Andrology and Urology},
volume = {5},
number = {5},
year = {2016},
keywords = {},
abstract = {Risk stratification for kidney sparing procedures (KSP) to treat upper tract urothelial carcinoma (UTUC) is a major issue. A non-systematic Medline/PubMed literature search was performed using the terms “upper tract urothelial carcinoma” with different combinations of keywords to review the current knowledge on this topic. Original articles, reviews and editorials in English language were selected based on their clinical relevance. Available techniques for KSP include segmental ureterectomy and endoscopic resection through a percutaneous or flexible ureteroscopic access. These approaches were traditionally restricted to patients with imperative indications. Current recommendations suggest that selected patients with normal contralateral kidney should also be candidates for such treatments. Modern imaging and endoscopy have improved to accurately stage and grade the tumor while various prognostic clinical factors and biomarkers have been proposed to identify tumor with aggressive features and worse outcomes. Several predictive models using different combinations of such baseline characteristics may help clinicians in clinical decision making. However, risk-adapted based approach that has been proposed in recent guidelines to identify patients who are more likely to benefit from KSP only relies on few clinical and pathological factors. Despite growing understanding of the disease, treatment of UTUC remains challenging. Further efforts and collaborative multicenter studies are mandatory to improve risk stratification to decide and promote optimal KSP in UTUC. These efforts should focus on the integration of promising biomarkers and predictive tools in clinical decision making.},
issn = {2223-4691}, url = {https://tau.amegroups.org/article/view/11795}
}