title: A systematic review of the tools available for predicting survival and managing patients with urothelial carcinomas of the bladder and of the upper tract in a curative setting.
abstract: OBJECTIVE
  To identify the predictive tools which have emerged recently in the field of urothelial carcinomas.
  
  
  METHODS
  We performed a thorough MEDLINE literature review using a combination of the following keywords: urothelial carcinoma, transitional cell carcinoma, bladder, renal pelvis, ureter, predictive tools, predictive models and nomograms. We found 117 articles, but only the relevant reports were selected.
  
  
  RESULTS
  The majority of available tools are prediction models, particularly nomograms. These models combine good performance accuracy with ease of use. They appear to be more accurate than risk grouping or tree modeling and are more suitable for clinicians than artificial intelligence. The most recent nomograms have been designed to be used in daily clinical practice and are even available as computer or smartphone applications. They focus on pathological outcomes or more frequently on survival statistics or recurrence risk after surgery. They provide an accurate prediction of disease evolution and may help clinicians to choose the most appropriate treatment option. However, these prediction tools still need to be validated and regularly utilized.
  
  
  CONCLUSIONS
  Predictive tools represent very helpful clinical decision-making aids but need to be validated in larger populations.
authors.affiliation: Academic Department of Urology of la Pitié-Salpêtrière Hospital, 1 Assistance Publique-Hôpitaux de Paris, Faculté de Médecine Pierre et Marie Curie, University Paris VI, Hôpital Pitié, 47-83 bvd de l'Hôpital, 75013, Paris, France.
authors.forename: Sarah J
authors.initials: SJ
authors.lastname: Drouin
authors.forename: David R
authors.initials: DR
authors.lastname: Yates
authors.forename: Vincent
authors.initials: V
authors.lastname: Hupertan
authors.forename: Olivier
authors.initials: O
authors.lastname: Cussenot
authors.forename: Morgan
authors.initials: M
authors.lastname: Rouprêt
mesh_terms: D002295:Carcinoma, Transitional Cell / Q000175:diagnosis* / Q000401:mortality / Q000628:therapy; D003661:Decision Support Techniques; D006801:Humans; D049451:Nomograms; D011379:Prognosis; D014571:Urologic Neoplasms / Q000175:diagnosis* / Q000401:mortality / Q000628:therapy