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  • 1
    Online Resource
    Online Resource
    Walter de Gruyter GmbH ; 2020
    In:  Serbian Journal of Experimental and Clinical Research Vol. 21, No. 4 ( 2020-12-01), p. 299-305
    In: Serbian Journal of Experimental and Clinical Research, Walter de Gruyter GmbH, Vol. 21, No. 4 ( 2020-12-01), p. 299-305
    Abstract: Screening has dramatically changed the distribution of the mean age, stage and grade of prostate cancer (PCa) at diagnosis. However, regional-level data that characterize contemporary PCa patients are limited. The aim of the study was to ascertain main clinical and pathological characteristics of PCa at the present time in the circumstances of opportunistic testing. High-grade PCa according to age, serum prostate specific antigen (PSA), volume prostate, PSA density (PSAD), digital rectal examination (DRE) number of positive cores biopsies and the average percentage of cancer in biopsy at diagnosis has been retrospectively evaluated in 100 men with biopsyproven PCa, at Clinical Centre Kragujevac, from September 2016 until September 2017. PCa were stratified according to Gleason score (GS) into low/intermediate-grade (GS ≤ 7) and high-grade (GS ≥ 8). To identify the determinants associated with high-grade PCa, we performed univariate and multivariate logistic regression. The most prevalent PCa were the low/intermediate-grade (65%), followed by high-grade (35%). The mean age of the patients was 71.5 (range: 56–88) years and median PSA was 14.6 (range: 1.4–935) ng/ml. There were significant differences in age, PSA, PSAD, DRE, number of positive biopsy and average percentage of cancer in biopsy between patients with or without high-grade GS. Logistic analysis demonstrated the PSAD and age have strong prognostic value of high-grade PCa. In conclusion, our study has shown the worrying frequency of high-grade PCa in the circumstances of opportunistic testing. Older men and higher level of PSAD had a much higher probability of high-grade PCa.
    Type of Medium: Online Resource
    ISSN: 2335-075X , 1820-8665
    Language: English
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2710266-X
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Walter de Gruyter GmbH ; 2020
    In:  Serbian Journal of Experimental and Clinical Research Vol. 21, No. 1 ( 2020-03-01), p. 43-50
    In: Serbian Journal of Experimental and Clinical Research, Walter de Gruyter GmbH, Vol. 21, No. 1 ( 2020-03-01), p. 43-50
    Abstract: Serum prostate-specific antigen (PSA) testing increases the number of persons who undergo prostate biopsy. However, the best possible strategy for selecting patients for prostate biopsy has not yet been defined. The aim of this study was to develop a classification and regression tree (CART) decision model that can be used to predict significant prostate cancer (PCa) in the course of prostate biopsy for patients with serum PSA levels of 10 ng/ml or less. The following clinicopathological characteristics of patients who had undergone ultrasound-guided transrectal prostate biopsy were collected: age, PSA, digital rectal examination, volume of the prostate, and PSA density (PSAD). CART analysis was carried out by using all predictors. Different aspects of the predictive performances of the prediction model were assessed. In this retrospective study, significant PCa values were detected in 26 (26.8%) of a total of 97 patients. The CART model had three branching levels based on PSAD as the most decisive variable and age. The model sensitivity was 73.1%, the specificity was 80.3% and the accuracy was 78.3%. Our model showed an area under the receiver operating characteristic curve of 82.6%. The model was well calibrated. In conclusion, CART analysis determined that PSAD was the key parameter for the identification of patients with a minimal risk for positive biopsies. The model showed a good discrimination capacity that surpassed individual predictors. However, before recommending its use in clinical practice, an evaluation of a larger and more complete database is necessary for the prediction of significant PCa.
    Type of Medium: Online Resource
    ISSN: 2335-075X , 1820-8665
    Language: English
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2710266-X
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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