title: Predictive and prognostic models in radical prostatectomy candidates: a critical analysis of the literature.
abstract: BACKGROUND
  Numerous predictive and prognostic tools have recently been developed for risk stratification of prostate cancer (PCa) patients who are candidates for or have been treated with radical prostatectomy (RP).
  
  
  OBJECTIVE
  To critically review the currently available predictive and prognostic tools for RP patients and to describe the criteria that should be applied in selecting the most accurate and appropriate tool for a given clinical scenario.
  
  
  METHODS
  A review of the literature was performed using the Medline, Scopus, and Web of Science databases. Relevant reports published between 1996 and January 2010 identified using the keywords prostate cancer, radical prostatectomy, predictive tools, predictive models, and nomograms were critically reviewed and summarised.
  
  
  RESULTS
  We identified 16 predictive and 22 prognostic validated tools that address a variety of end points related to RP. The majority of tools are prediction models, while a few consist of risk-stratification schemes. Regardless of their format, the tools can be distinguished as preoperative or postoperative. Preoperative tools focus on either predicting pathologic tumour characteristics or assessing the probability of biochemical recurrence (BCR) after RP. Postoperative tools focus on cancer control outcomes (BCR, metastatic progression, PCa-specific mortality [PCSM], overall mortality). Finally, a novel category of tools focuses on functional outcomes. Prediction tools have shown better performance in outcome prediction than the opinions of expert clinicians. The use of these tools in clinical decision-making provides more accurate and highly reproducible estimates of the outcome of interest. Efforts are still needed to improve the available tools' accuracy and to provide more evidence to further justify their routine use in clinical practice. In addition, prediction tools should be externally validated in independent cohorts before they are applied to different patient populations.
  
  
  CONCLUSIONS
  Predictive and prognostic tools represent valuable aids that are meant to consistently and accurately provide most evidence-based estimates of the end points of interest. More accurate, flexible, and easily accessible tools are needed to simplify the practical task of prediction.
authors: Department of Urology, Vita-Salute San Raffaele University, Milano, Italy. lughezzani.giovanni@hsr.it
authors: Giovanni
authors: G
authors: Lughezzani
authors: Alberto
authors: A
authors: Briganti
authors: Pierre I
authors: PI
authors: Karakiewicz
authors: Michael W
authors: MW
authors: Kattan
authors: Francesco
authors: F
authors: Montorsi
authors: Shahrokh F
authors: SF
authors: Shariat
authors: Andrew J
authors: AJ
authors: Vickers
mesh_terms: D019317:Evidence-Based Medicine; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011468:Prostatectomy / Q000401:mortality*; D011471:Prostatic Neoplasms / Q000401:mortality / Q000473:pathology / Q000601:surgery