title: Prognostic and Prediction Tools in Bladder Cancer: A Comprehensive Review of the Literature.
abstract: BACKGROUND
  This review focuses on risk assessment and prediction tools for bladder cancer (BCa).
  
  
  OBJECTIVE
  To review the current knowledge on risk assessment and prediction tools to enhance clinical decision making and counseling of patients with BCa.
  
  
  METHODS
  A literature search in English was performed using PubMed in July 2013. Relevant risk assessment and prediction tools for BCa were selected. More than 1600 publications were retrieved. Special attention was given to studies that investigated the clinical benefit of a prediction tool.
  
  
  RESULTS
  Most prediction tools for BCa focus on the prediction of disease recurrence and progression in non-muscle-invasive bladder cancer or disease recurrence and survival after radical cystectomy. Although these tools are helpful, recent prediction tools aim to address a specific clinical problem, such as the prediction of organ-confined disease and lymph node metastasis to help identify patients who might benefit from neoadjuvant chemotherapy. Although a large number of prediction tools have been reported in recent years, many of them lack external validation. Few studies have investigated the clinical utility of any given model as measured by its ability to improve clinical decision making. There is a need for novel biomarkers to improve the accuracy and utility of prediction tools for BCa.
  
  
  CONCLUSIONS
  Decision tools hold the promise of facilitating the shared decision process, potentially improving clinical outcomes for BCa patients. Prediction models need external validation and assessment of clinical utility before they can be incorporated into routine clinical care.
  
  
  RESULTS
  We looked at models that aim to predict outcomes for patients with bladder cancer (BCa). We found a large number of prediction models that hold the promise of facilitating treatment decisions for patients with BCa. However, many models are missing confirmation in a different patient cohort, and only a few studies have tested the clinical utility of any given model as measured by its ability to improve clinical decision making.
authors.affiliation: Department of Urology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, USA; Department of Urology, University Medical-Center Hamburg-Eppendorf, Hamburg, Germany.
authors.forename: Luis A
authors.initials: LA
authors.lastname: Kluth
authors.affiliation: Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.
authors.forename: Peter C
authors.initials: PC
authors.lastname: Black
authors.affiliation: Department of Urology, Memorial Sloan-Kettering Cancer Center, Kimmel Center for Prostate and Urologic Tumors, New York, NY, USA.
authors.forename: Bernard H
authors.initials: BH
authors.lastname: Bochner
authors.affiliation: Academic Urology Unit, University of Sheffield, Sheffield, UK.
authors.forename: James
authors.initials: J
authors.lastname: Catto
authors.affiliation: Scott Department of Urology, Baylor College of Medicine, Houston, TX, USA.
authors.forename: Seth P
authors.initials: SP
authors.lastname: Lerner
authors.affiliation: Department of Urology, Eberhard-Karls University, Tuebingen, Germany.
authors.forename: Arnulf
authors.initials: A
authors.lastname: Stenzl
authors.affiliation: EORTC Headquarters, Brussels, Belgium.
authors.forename: Richard
authors.initials: R
authors.lastname: Sylvester
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Vickers
authors.affiliation: Department of Urology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, USA; Department of Urology, Cochin Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University, Paris, France.
authors.forename: Evanguelos
authors.initials: E
authors.lastname: Xylinas
authors.affiliation: Department of Urology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, USA; Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Urology, UT Southwestern, Dallas, TX, USA; Division of Medical Oncology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY, USA. Electronic address: sfshariat@gmail.com.
authors.forename: Shahrokh F
authors.initials: SF
authors.lastname: Shariat
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism; D017024:Chemotherapy, Adjuvant; D015653:Cystectomy; D003661:Decision Support Techniques; D018450:Disease Progression; D018572:Disease-Free Survival; D006801:Humans; D008207:Lymphatic Metastasis; D020360:Neoadjuvant Therapy; D060787:Neoplasm Grading; D009364:Neoplasm Recurrence, Local; D009367:Neoplasm Staging; D049451:Nomograms; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome; D001749:Urinary Bladder Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000401:mortality / Q000473:pathology / Q000628:therapy
chemical_list: D014408:Biomarkers, Tumor
keywords: Bladder cancer; Disease recurrence; Nomogram; Outcome; Prediction; Prediction tool; Prognosis; Prognostic tool; Radical cystectomy; Survival