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Preoperative prostate health index predicts adverse pathology and Gleason score upgrading after radical prostatectomy for prostate cancer

V. Novak, S. Vesely, H. Luksanová, R. Prusa, O. Capoun, V. Fiala, O. Dolejsová, H. Sedlacková, R. Kucera, J. Stejskal, M. Zalesky, M. Babjuk

. 2020 ; 20 (1) : 144. [pub] 20200907

Jazyk angličtina Země Velká Británie

Typ dokumentu časopisecké články, multicentrická studie

Perzistentní odkaz   https://www.medvik.cz/link/bmc21020145

BACKGROUND: We aimed to explore the utility of prostate specific antigen (PSA) isoform [- 2] proPSA and its derivatives for prediction of pathological outcome after radical prostatectomy (RP). METHODS: Preoperative blood samples were prospectively and consecutivelyanalyzed from 472 patients treated with RP for clinically localized prostate cancerat four medical centers. Measured parameters were PSA, free PSA (fPSA), fPSA/PSA ratio, [- 2] proPSA (p2PSA), p2PSA/fPSA ratio and Prostate Health Index (PHI)(p2PSA/fPSA)*√PSA]. Logistic regression models were fitted to determine the accuracy of markers for prediction of pathological Gleason score (GS) ≥7, Gleason score upgrading, extracapsular extension of the tumor (pT3) and the presence of positive surgical margin (PSM). The accuracy of predictive models was compared using area under the receiver operating curve (AUC). RESULTS: Of 472 patients undergoing RP, 339 (72%) were found to have pathologic GS ≥ 7, out of them 178 (53%) experienced an upgrade from their preoperative GS = 6. The findings of pT3 and PSM were present in 132 (28%) and 133 (28%) cases, respectively. At univariable analysis of all the preoperative parameters, PHI was the most accurate predictor of pathological GS ≥7 (OR 1.02, 95% CI 1.01-1.03, p<0.001), GS upgrading (OR 1.02, 95% CI 1.01-1.03, p<0.003), pT3 disease (OR 1.01, 95% CI 1.00-1.02, p<0.007) and the presence of PSM (OR 1.01, 95% CI 1.00-1.02, p<0.002). Adding of PHI into the base multivariable model increased significantly the accuracy for prediction of pathological GS by 4.4% to AUC = 66.6 (p = 0.015) and GS upgrading by 5.0% to AUC = 65.9 (p = 0.025), respectively. CONCLUSIONS: Preoperative PHI levels may contribute significantly to prediction of prostate cancer aggressiveness and expansion of the tumor detected at final pathology.

Citace poskytuje Crossref.org

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$a Novak, Vojtech $u Department of Urology, Charles University 2nd Faculty of Medicine University Hospital Motol, Prague, Czech Republic. vojtech.novak.lf2@gmail.com
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$a Preoperative prostate health index predicts adverse pathology and Gleason score upgrading after radical prostatectomy for prostate cancer / $c V. Novak, S. Vesely, H. Luksanová, R. Prusa, O. Capoun, V. Fiala, O. Dolejsová, H. Sedlacková, R. Kucera, J. Stejskal, M. Zalesky, M. Babjuk
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$a BACKGROUND: We aimed to explore the utility of prostate specific antigen (PSA) isoform [- 2] proPSA and its derivatives for prediction of pathological outcome after radical prostatectomy (RP). METHODS: Preoperative blood samples were prospectively and consecutivelyanalyzed from 472 patients treated with RP for clinically localized prostate cancerat four medical centers. Measured parameters were PSA, free PSA (fPSA), fPSA/PSA ratio, [- 2] proPSA (p2PSA), p2PSA/fPSA ratio and Prostate Health Index (PHI)(p2PSA/fPSA)*√PSA]. Logistic regression models were fitted to determine the accuracy of markers for prediction of pathological Gleason score (GS) ≥7, Gleason score upgrading, extracapsular extension of the tumor (pT3) and the presence of positive surgical margin (PSM). The accuracy of predictive models was compared using area under the receiver operating curve (AUC). RESULTS: Of 472 patients undergoing RP, 339 (72%) were found to have pathologic GS ≥ 7, out of them 178 (53%) experienced an upgrade from their preoperative GS = 6. The findings of pT3 and PSM were present in 132 (28%) and 133 (28%) cases, respectively. At univariable analysis of all the preoperative parameters, PHI was the most accurate predictor of pathological GS ≥7 (OR 1.02, 95% CI 1.01-1.03, p<0.001), GS upgrading (OR 1.02, 95% CI 1.01-1.03, p<0.003), pT3 disease (OR 1.01, 95% CI 1.00-1.02, p<0.007) and the presence of PSM (OR 1.01, 95% CI 1.00-1.02, p<0.002). Adding of PHI into the base multivariable model increased significantly the accuracy for prediction of pathological GS by 4.4% to AUC = 66.6 (p = 0.015) and GS upgrading by 5.0% to AUC = 65.9 (p = 0.025), respectively. CONCLUSIONS: Preoperative PHI levels may contribute significantly to prediction of prostate cancer aggressiveness and expansion of the tumor detected at final pathology.
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$a Vesely, Stepan $u Department of Urology, Charles University 2nd Faculty of Medicine University Hospital Motol, Prague, Czech Republic
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$a Luksanová, Hana $u Department of Medical Chemistry and Clinical Biochemistry, Charles University 2nd Faculty of Medicine University Hospital Motol, Prague, Czech Republic
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$a Prusa, Richard $u Department of Medical Chemistry and Clinical Biochemistry, Charles University 2nd Faculty of Medicine University Hospital Motol, Prague, Czech Republic
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$a Capoun, Otakar $u Department of Urology, General University Hospital and 1st Faculty of Medicine, Charles University, Prague, Czech Republic
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$a Fiala, Vojtech $u Department of Urology, General University Hospital and 1st Faculty of Medicine, Charles University, Prague, Czech Republic
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$a Dolejsová, Olga $u Department of Urology, University Hospital and Faculty of Medicine in Pilsen, Pilsen, Czech Republic
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$a Sedlacková, Hana $u Department of Urology, University Hospital and Faculty of Medicine in Pilsen, Pilsen, Czech Republic
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$a Kucera, Radek $u Department of Immunochemistry, University Hospital and Faculty of Medicine in Pilsen, Pilsen, Czech Republic
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$a Stejskal, Jiri $u Department of Urology and 1st and 3rd Medical Faculty, Thomayer Hospital, Charles University, Prague, Czech Republic
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$a Zalesky, Miroslav $u Department of Urology and 1st and 3rd Medical Faculty, Thomayer Hospital, Charles University, Prague, Czech Republic
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$a Babjuk, Marko $u Department of Urology, Charles University 2nd Faculty of Medicine University Hospital Motol, Prague, Czech Republic $u Medical University of Vienna, Vienna, Austria
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