Preoperative Prostate-specific Antigen Isoform p2PSA and Its Derivatives, %p2PSA and Prostate Health Index, Predict Pathologic Outcomes in Patients Undergoing Radical Prostatectomy for Prostate Cancer: Results from a Multicentric European Prospective Study

TY - JOUR

T1 - Preoperative Prostate-specific Antigen Isoform p2PSA and Its Derivatives, %p2PSA and Prostate Health Index, Predict Pathologic Outcomes in Patients Undergoing Radical Prostatectomy for Prostate Cancer: Results from a Multicentric European Prospective Study

AU - Fossati, Nicola

AU - Buffi, Nicolò Maria

AU - Haese, Alexander

AU - Stephan, Carsten

AU - Larcher, Alessandro

AU - McNicholas, Thomas

AU - de la Taille, Alexandre

AU - Freschi, Massimo

AU - Lughezzani, Giovanni

AU - Abrate, Alberto

AU - Bini, Vittorio

AU - Palou Redorta, Joan

AU - Graefen, Markus

AU - Guazzoni, Giorgio

AU - Lazzeri, Massimo

N1 - Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

PY - 2015/7

Y1 - 2015/7

N2 - BACKGROUND: Currently available predictive models fail to assist clinical decision making in prostate cancer (PCa) patients who are potential candidates for radical prostatectomy (RP). New biomarkers would be welcome.OBJECTIVE: To test the hypothesis that prostate-specific antigen (PSA) isoform p2PSA and its derivatives, percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI), predict PCa characteristics at final pathology.DESIGN, SETTING, AND PARTICIPANTS: An observational prospective multicentre European study was performed in 489 consecutive PCa patients treated with RP. Total PSA (tPSA), free PSA (fPSA), and p2PSA levels were determined. The %fPSA [(fPSA / tPSA) × 100], %p2PSA [(p2PSA pg/ml) / (fPSA ng/ml × 1000) × 100], and PHI [(p2PSA / fPSA) × √tPSA] were calculated.INTERVENTION: Open or robot-assisted RP.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression models were fitted to test the predictors of pT3 stage and/or pathologic Gleason score (GS) ≥7 and to determine their predictive accuracy. The base multivariable model included tPSA, digital rectal examination, biopsy GS, and percentage of positive biopsy cores. Decision curve analysis provided an estimate of the net benefit obtained using p2PSA, %p2PSA, or PHI.RESULTS AND LIMITATIONS: Overall, 344 patients (70%) were affected by pT3 disease or pathologic GS ≥7; pT3 disease and pathologic GS ≥7 were present in 126 patients (26%). At univariable analysis, p2PSA, %p2PSA, and PHI were significant predictors of pT3 disease and/or pathologic GS ≥7 (all p ≤ 0.001). The inclusion of PHI significantly increased the accuracy of the base multivariable model by 2.3% (p=0.003) and 2.4% (p=0.01) for the prediction of pT3 disease and/or pathologic GS ≥7, respectively. However, at decision curve analysis, models including PHI did not show evidence of a greater clinical net benefit.CONCLUSIONS: Both %p2PSA and PHI are significant predictors of unfavourable PCa characteristics at final pathology; however, %p2PSA and PHI did not provide a greater net benefit for clinical decision making.PATIENT SUMMARY: Prostate-specific antigen (PSA) isoform p2PSA and its derivatives, percentage of p2PSA to free PSA and the Prostate Health Index, are associated with adverse characteristics of prostate cancer; however, these biomarkers provided only a slight net benefit for clinical decision making.

AB - BACKGROUND: Currently available predictive models fail to assist clinical decision making in prostate cancer (PCa) patients who are potential candidates for radical prostatectomy (RP). New biomarkers would be welcome.OBJECTIVE: To test the hypothesis that prostate-specific antigen (PSA) isoform p2PSA and its derivatives, percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI), predict PCa characteristics at final pathology.DESIGN, SETTING, AND PARTICIPANTS: An observational prospective multicentre European study was performed in 489 consecutive PCa patients treated with RP. Total PSA (tPSA), free PSA (fPSA), and p2PSA levels were determined. The %fPSA [(fPSA / tPSA) × 100], %p2PSA [(p2PSA pg/ml) / (fPSA ng/ml × 1000) × 100], and PHI [(p2PSA / fPSA) × √tPSA] were calculated.INTERVENTION: Open or robot-assisted RP.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Logistic regression models were fitted to test the predictors of pT3 stage and/or pathologic Gleason score (GS) ≥7 and to determine their predictive accuracy. The base multivariable model included tPSA, digital rectal examination, biopsy GS, and percentage of positive biopsy cores. Decision curve analysis provided an estimate of the net benefit obtained using p2PSA, %p2PSA, or PHI.RESULTS AND LIMITATIONS: Overall, 344 patients (70%) were affected by pT3 disease or pathologic GS ≥7; pT3 disease and pathologic GS ≥7 were present in 126 patients (26%). At univariable analysis, p2PSA, %p2PSA, and PHI were significant predictors of pT3 disease and/or pathologic GS ≥7 (all p ≤ 0.001). The inclusion of PHI significantly increased the accuracy of the base multivariable model by 2.3% (p=0.003) and 2.4% (p=0.01) for the prediction of pT3 disease and/or pathologic GS ≥7, respectively. However, at decision curve analysis, models including PHI did not show evidence of a greater clinical net benefit.CONCLUSIONS: Both %p2PSA and PHI are significant predictors of unfavourable PCa characteristics at final pathology; however, %p2PSA and PHI did not provide a greater net benefit for clinical decision making.PATIENT SUMMARY: Prostate-specific antigen (PSA) isoform p2PSA and its derivatives, percentage of p2PSA to free PSA and the Prostate Health Index, are associated with adverse characteristics of prostate cancer; however, these biomarkers provided only a slight net benefit for clinical decision making.

U2 - 10.1016/j.eururo.2014.07.034

DO - 10.1016/j.eururo.2014.07.034

M3 - SCORING: Journal article

C2 - 25139197

VL - 68

SP - 132

EP - 138

JO - EUR UROL

JF - EUR UROL

SN - 0302-2838

IS - 1

ER -