期刊
WORLD JOURNAL OF UROLOGY
卷 35, 期 3, 页码 337-353出版社
SPRINGER
DOI: 10.1007/s00345-016-1826-2
关键词
Upper tract urothelial carcinoma; Prognosis; Prognostic factors; Predictive tools; Nomograms; Risk stratification; Biomarkers; Survival; Disease recurrence
资金
- Association des Amis de la Faculte de medecine de Nice
Upper tract urothelial carcinoma (UTUC) is a rare and heterogeneous disease. Several clinical and biological prognostic factors have been identified in multi-institutional collaborative works with the aim of helping decision-making in pursuit of tailored individual patient care. This review provides an overview of these existing prognostic factors and predictive tools for the management of patients with UTUC. A systematic literature search was performed using PubMed/MEDLINE, Web of Science and Scopus databases regarding articles published in English between January 2000 and November 2015 according to PRISMA guidelines. Thresholds of 100 and 300 patients were applied for studies on biomarkers and clinical studies, respectively. All the studies on predictive tools were included for analysis. Outcomes of interest were features associated with advanced-stage UTUC, disease recurrence and survival. A total of 116 studies were included in this review. These large and/or multi-institutional studies have confirmed the prognostic value of standard pathological factors (i.e., tumor stage, grade and lymph node metastasis) and identified novel features such as lymphovascular invasion, tumor architecture, multifocality, concomitant CIS, variant histology and biomarker status among others. Based on these variables, several predictive tools have been developed; however, they often lack of validation. The value of these features and tools needs prospective testing. Efforts provided by international collaboration groups have permitted to validate established features and identify new features of biologically and clinically aggressive UTUC. Further investigation on prognostic factors and biomarkers is still needed to assess the benefit of these features and tools on clinical decision-making.
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