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PROSTATE CANCER STAGING TABLES - A PREDICTIVE NOMOGRAM FOR THE UK

Mr Simon R J Bott, Professor John R Masters

Prostate Cancer Research Centre, UCL Institute of Urology

  

INTRODUCTION
Accurate risk stratification is a pre-requisite to informed decision making when considering prostate cancer treatments. Most models are derived from cases managed in the USA. The validity of these methods maybe compromised when used in a healthcare system other than that used for generating the predicted outcomes. We present predictive nomograms derived from the observed outcomes of men treated by radical prostatectomy (RP) in the UK.

METHODS
Using logistic regression a pilot study identified the best predictors of pathological stage from eight preoperative variables. All full BAUS members were asked to submit their consecutive RP patients' age, biopsy Gleason score, pre operative PSA, number of biopsy cores, number of biopsy cores containing cancer (% positive cores) and pathological stage. Nomograms were constructed using this data to predict pT2, pT3a or pT3b/4/N1 disease after RP and were validated using bootstrapping techniques.

RESULTS
1913 patients undergoing RP by 39 Consultant Urologists were included. Using multivariate analysis significant predictors of pathological stage were preoperative PSA (p<0.0001), biopsy Gleason sum (p<0.0001), % positive cores (p<0.0001) and age (p<0.001). Nomograms were constructed based on these variables.

CONCLUSIONS
These nomograms are derived from a large essentially unscreened cohort from across the country and reflect UK RP patients.

Research summary dated 01 December 2004
Project 2004/04