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Arch Ital Urol Androl ; 76(1): 19-24, 2004 Mar.
Article in English | MEDLINE | ID: mdl-15185817

ABSTRACT

OBJECTIVES: Uro-gramma is a probabilistic predictive model of pathological staging of prostate cancer (Pca) from preoperative parameters (PSA, clinical Gs, clinical stage) published in 2000. Aim of this study is to improve Uro-gramma, updating it, to take into account the continuous evolution of the population. MATERIALS AND METHODS: From 1998 to 2000, 991 Pca patients have undergone radical prostatectomy in several Italian urological centers. Inclusion criteria were: preoperative PSA < 50 ng/ml, clinical stage < or = T3c, availability of a bioptic Gs and pathological staging. A predictive model has been estimated for each year and its behaviour on the following years tested, using Hosmer and Lemeshow tests, which compare the expected rate with the observed one. RESULTS: The mean age was 66.3 years. Pca familiarity was present in 3.2% of the patients in 1998, 2.6% in 1999 and 7.4% in 2000. PSA values < 10 have increased (from 41% to 47%) and those > 10 decreased (from 59% to 53%). The mean number of bioptic samples per patient has increased from 4.9 to 6, while clinical and pathologic Gs have remained stable. An increase in the rate of organ confined Pca has been noticed, either clinically (87.4% in 1998, 92% in 2000) or pathologically (55.2% in '98, 57% in 2000). Staging lymphadenectomy has been performed in 88% of the pts in 1998, 94.2% in 1999 and 94.5% in 2000, whereas the % of N+ patients has moved from 11.3% in 1998 to 9.8% in 2000. CONCLUSIONS: Uro-gramma update results show that the mean estimate error has fallen from 6.4% to 1.2%. The new model strengthens the previous one and confirms its validity, but it also underlines the need of a constant update to take into account the continuous evolution of the population and of the methods of diagnosis and staging.


Subject(s)
Models, Statistical , Prostatic Neoplasms/pathology , Aged , Aged, 80 and over , Humans , Male , Middle Aged , Neoplasm Staging , Prognosis
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