Detection of Prostate Cancer by Ultrasonographically-guided Transrectal Prostate Biopsies at the Department of Urology of the First Faculty of Medicine, Charles University and General Teaching Hospital in Prague, Analysis of 1464 Cases


Authors: L. Šafařík 1;  K. Novák 1;  J. Stolz 1;  M.;  J. Zlatohlávek 2;  M. Pešl 1;  M. Babjuk 1;  I. Pavlík 1;  T. Hanuš 1;  J. Dvořáček 1
Authors‘ workplace: Urologická klinika 1. LF UK a VFN, Praha 1;  Matematicko-fyzikální fakulta UK, Praha 2
Published in: Čas. Lék. čes. 2007; 146: 788-792
Category: Original Article

Overview

Background.
Early diagnostics of prostate cancer is still the most important factor in tumor-specific survival of patients harbouring this malignant disease. Without better understanding of the etiology and without relevant markers of the disease progression, only the early diagnostics of organ-confined disease can save the patient’s life. 

Methods and Results.
Throughout 7 consecutive years, 1464 transrectal prostate biopsies in 1302 patients were performed. In all cases, the age, DRE (positive or negative), prostatic volume (ccm), total PSA in peripheral blood (ng/ml) were assigned, as well as free/total PSA ratio (%) in most of them. Apart from previously used linear regression, we applied logistic regression, since only age grows linear and DRE is determined only as positive or negative. The surrogate endpoint was ROC, which determines the area applying to the relations of sensitivity and specificity of any marker. Multifactorial logistic regression then reached best results at values over 0.8 in all tested age categories with maximal deviation of 8%, which had not been achieved before. 

Conclusions.
Despite hundreds of papers published on this topic, the question of when and how the patient is indicated to the biopsy of the prostate has not been solved. A computer driven model based on 1464 documented examinations on the relatively homogeneous population is presented. On the basis of the combination of biological and statistical methods, the model can give correct predictions in 9 out of 10 cases. 

Key words:
prostate cancer, early diagnostics, computer model.


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Journal of Czech Physicians

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2007 Issue 10

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