Percentage of tumour-positive biopsy cores: an independent predictor of extraprostatic disease

Autor: Peter S. Mortensen, Michael Borre, Martin Mørck Mortensen
Rok vydání: 2009
Předmět:
Zdroj: Mortensen, M M, Mortensen, P S & Borre, M 2009, ' Percentage of tumour-positive biopsy cores: an independent predictor of extraprostatic disease ', Scandinavian Journal of Urology and Nephrology, vol. 43, no. 2, pp. 109-13 . https://doi.org/10.1080/00365590802670348
ISSN: 0036-5599
DOI: 10.1080/00365590802670348
Popis: Udgivelsesdato: 2009-null OBJECTIVE: Preoperative staging of patients diagnosed with prostate cancer is vital in determining the correct treatment including radical prostatectomy. Serum prostate-specific antigen (PSA), Gleason score in prostate biopsies and predicted clinical T-stage using digital rectal examination and transrectal ultrasound are known predictors of extraprostatic disease after surgery. This study analysed whether the percentage of positive biopsy cores was a significant preoperative predictor of extraprostatic disease in patients undergoing radical prostatectomy. MATERIAL AND METHODS: An analysis was conducted on 390 consecutive patients who underwent radical prostatectomy at Arhus University hospital from 2000 to 2006. Serum PSA, Gleason score, predicted clinical T-stage and percentage of positive biopsy cores were tested in a univariate analysis, and then a multivariate logistical regression model, to determine whether they were predictors of extraprostatic disease. RESULTS: The percentage of positive biopsy cores was, together with T-stage and Gleason score, shown to be a significant predictor of extraprostatic disease in both univariate and multivariate analysis with a p-value of 0.05. The calculation yields a model that can predict risk of non-organ-confined disease in a non-screened population. CONCLUSION: Being an independent predictor of extraprostatic disease, the percentage of positive biopsy cores can supplement existing preoperative staging variables as found in current staging nomograms.
Databáze: OpenAIRE
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