In:
The Prostate, Wiley, Vol. 70, No. 12 ( 2010-09), p. 1371-1378
Abstract:
In the last 10 years, several user‐friendly predictive tools have been developed to help clinicians in decision‐making process before and after radical prostatectomy. OBJECTIVE To review the most known and used predictive models in pre‐operative and post‐operative setting. EVIDENCE ACQUISITION A structured, comprehensive literature review was performed using data retrieved from recent review articles, original articles, and abstracts. Used keywords were predictive models, nomograms, look‐up tables, classification and regression‐tree analysis, artificial neural networks, and radical prostatectomy. EVIDENCE SYNTHESIS A great amount of predictive models has been provided in oncology setting: nomograms, look‐up tables, classification and regression‐tree analysis, propensity scores, risk‐group stratification models, and artificial neural networks. Pre‐surgery predictive tools offer the opportunity of getting the most evidence‐based and individualized selection of available treatment alternatives. Post‐operative predictive models usually provide higher accuracy relative to the pre‐surgery models. CONCLUSIONS Decisions and treatment should be tailored to each individual patient and to the specific characteristics of patients. A number of available predictive models represent a tool to provide accurate prediction of cancer natural history and to improve patients' care. Prostate 70:1371–1378, 2010. © 2010 Wiley‐Liss, Inc.
Type of Medium:
Online Resource
ISSN:
0270-4137
,
1097-0045
Language:
English
Publisher:
Wiley
Publication Date:
2010
detail.hit.zdb_id:
1494709-2
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