Original Paper
Urologia
Received: January 21, 2015 Accepted: February 5, 2015 Published online: March 17, 2015
Urol Int DOI: 10.1159/000379758
Internationalis
Use of the Prostate Health Index for the Detection of Aggressive Prostate Cancer at Radical Prostatectomy Luigi Mearini a Elisabetta Nunzi a Carla Ferri c Guido Bellezza b Carolina Lolli a Carlo Porrozzi a Massimo Porena a
c
Department of Urology and b Institute of Pathologic Anatomy and Histology, University of Perugia, and Clinical Pathology and Haematology Laboratory, Azienda Ospedaliera di Perugia, Perugia, Italy
Key Words Pathologic examination · Prostate cancer · Prostate health index · Prostate-specific antigen · Radical prostatectomy
Abstract Introduction: In current study, we compared the accuracy of the PSA isoform p2PSA and its derivatives, the percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI) in the detection of prostate cancer (PC) characteristics at the final pathology with respect to reference standards. Materials and Methods: This was an observational prospective study evaluating 43 consecutive PC patients treated with laparoscopic/robotic radical prostatectomy (RP). Logistic regression models were fitted to test the predictors of pT3 stage, pathologic Gleason score ≥8 or Gleason score upgrading, margin status, lymph node invasion, and the presence of high-risk disease (pT3 disease and/or Gleason score ≥8 and/or positive lymph node). The comparative base model included tPSA, clinical stage, biopsy Gleason score, and percentage of positive core. Results: Seventeen patients (39.5%) were affected by pT3 disease or had a pathologic Gleason score ≥8; positive margins were detected in 12 patients (27.9%), lymph node invasion was found in 2 patients (4.7%), and 15 patients (34.8%) harbored high-risk disease. In the univariate analysis, p2PSA, %p2PSA, and PHI were significant predictors of pT3 disease, pathologic Gleason score, and the
© 2015 S. Karger AG, Basel 0042–1138/15/0000–0000$39.50/0 E-Mail [email protected] www.karger.com/uin
presence of high-risk disease (all p < 0.05), whereas only PHI was an independent predictor of pT3 disease, margin status, and presence of high-risk disease, increasing the accuracy of a base multivariable model by 6.3% (p < 0.05) and 4.2% (p < 0.05) for the prediction of pT3 and high-risk disease, respectively. Conclusions: p2PSA and its derivatives, primarily PHI, were significant predictors of unfavorable PC characteristics as detected at the final pathology, thus improving the clinical performance of standard prognostic factors for aggressive disease. © 2015 S. Karger AG, Basel
Introduction
During the process of diagnosing prostate cancer (PC), active or opportunistic screening based on the prostatespecific antigen (PSA) leads to a significant number of patients demonstrating organ-confined or low-risk disease [1]. In this context, overdiagnosis leading to overtreatment is an important adverse effect of such diagnostic intervention. The promise of a screening, i.e. that cancers should be detected as early as possible to maximize the chance of cure and reduce mortality, in PC frequently translates to overdiagnosis and harm [2]. There is a wide range of standard treatments for men with localized PC, ranging from active surveillance (AS) Luigi Mearini, MD Department of Urology, Azienda Ospedaliera di Perugia University of Perugia, Perugia Sant’Andrea delle Fratte, IT–06100 Perugia (Italy) E-Mail luigi.mearini @ tin.it
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a
or focal therapy to radical prostatectomy (RP) or radiation therapy. According to life expectancy and the characteristics of the disease, the best treatment should provide the patient with an appropriate, well-balanced harm/ benefit ratio, i.e. optimal oncologic and functional outcomes. Currently, the available clinical parameters used in the evaluation of PC, such as PSA, digital rectal examination (DRE), and Gleason score, fail to accurately predict under- or overtreatment of PC. Therefore, many predictive and prognostic tools have been developed to assist patients and physicians in their difficult clinical decisionmaking process before [3, 4] and after biopsy [5–7]. All of the prognostic tools aim to reduce errors in the clinical evaluation of PC aggressiveness. In this context, multiparametric MRI, a new imaging tool, should help determine the best treatment option for a patient with a new diagnosis of PC [8], and new biomarkers are welcome to reduce error margins in discriminating between clinically significant and insignificant PC. Recent studies have shown that the PSA isoformproPSA (p2PSA) and its derivatives, percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI) (Beckman Coulter, Brea, Calif., USA), improve the accuracy of total PSA (tPSA) and the percentage of free PSA (%fPSA) in predicting the presence of PC at prostate biopsy [9–12] and are predictors of PC aggressiveness at biopsy. More recently, five studies [13–17] have investigated the role of p2PSA and its derivatives in the prediction of PC aggressiveness confirmed at final pathology after RP. The aim of the current prospective study was to compare these biomarkers with the established prognostic characteristics in the prediction of pathologic PC within a contemporary cohort of patients who underwent laparoscopic RP for clinically localized PC at a single highvolume institution.
tients gave their written informed consent. The principles and policies of the Declaration of Helsinki were followed. The primary endpoint of the study was to determine the accuracy of p2PSA, %p2PSA, and PHI in predicting (1) the presence of extracapsular disease (pT3), (2) the presence of a pathologic Gleason score ≥8 or pathological upgrading, (3) the presence of a positive margin, (4) the presence of positive lymph nodes, and (5) the presence of pathological high-risk disease (defined as pT3 and/or Gleason score ≥8 and/or positive lymph nodes). The biomarkers p2PSA, %p2PSA, and PHI were used as the index tests and were compared with the accepted reference standard tests: tPSA, free PSA (fPSA), fPSA-to-tPSA ratio (%fPSA), Gleason score at biopsy, percentage of positive core at biopsy, and clinical stage. A blood sample was drawn the day before surgery and prior to any manipulations (e.g. DRE, enema) that might cause an increase in biomarkers. Blood samples were processed using the UniCel DxI800 Immunoassay System analyzer (Beckman Coulter) and were managed according to the criteria described by Semjonow et al. [18]. Blood sample analysis was performed using the Hybritechcalibrated Access tPSA (Beckman Coulter) and fPSA assay. Biopsy cores and RP specimens were processed and evaluated by a single experienced genitourinary pathologist (G.B.). PC was graded according to the definitions of the 2005 consensus conference of the International Society of Urological Pathology. Statistical Analysis The Kolmogorov-Smirnov test was used to assess the normal distribution of variables. The Mann-Whitney U test was used for comparisons of ordinal and nonnormally distributed continuous variables. Spearman’s rho coefficient was used to test correlations between continuous and ordinal variables. Bivariate and multivariate logistic regression models were fitted for the prediction of the presence of pT3, the presence of a pathologic Gleason score >8 or pathological upgrading, margin status, lymph node invasion, and finally the presence of high-risk PC. The logistic regression model goodness-of-fit was checked using the Hosmer-Lemeshow test. Odds ratios (ORs) with 95% CI were also calculated. Predictive accuracy was quantified as the area under the receiver operating characteristics curve (AUC). All calculations were carried out using SPSS 13. p < 0.05 was considered significant.
Materials and Methods Our observational prospective study cohort consisted of 43 consecutive patients with biopsy-proven, clinically localized PC, who were consecutively recruited between October 2013 and April 2014 and who underwent either laparoscopic or robot-assisted RP at our institution. Local staging processes included DRE and transrectal ultrasound scan; bone scintigraphy and CT scan were scheduled according to risk classification. None of the patients received drugs that could have altered the PSA values, such as dutasteride and finasteride, or neoadjuvant androgen-deprivation therapy. The hospital ethics committee approved the study, representing the expansion of clinical trial NCT01672411, and all of the pa-
2
Urol Int DOI: 10.1159/000379758
The descriptive characteristics of the overall study population are shown in table 1. At clinical evaluation, 29 patients (67.4%) were diagnosed with a Gleason score ≤6, and 16 (37.2%) and 27 (67.8%) patients were diagnosed with cT1c and cT2 disease, respectively. Forty patients (93%) were diagnosed with a pathologic Gleason score ≤7 PC, and 14 (32.6%) and 2 (4.7%) patients were diagnosed with pT3 and pN1 disease, respectively. The negative margin rate was 72.1%. Overall, 14 patients (32.5%) were classified as harboring high-risk disease. As shown in figures 1–3, p2PSA, %p2PSA, and PHI levels were significantly higher in patients with pT3 disMearini/Nunzi/Ferri/Bellezza/Lolli/ Porrozzi/Porena
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Results
n (%) Age, years Prostate volume, ml tPSA, ng/ml PSA density, ng/ml2 fPSA, ng/ml %fPSA p2PSA, pg/ml %p2PSA PHI DRE Negative Positive Transrectal ultrasound Negative Positive Biopsy Gleason score 6 7 >8 Number of biopsy cores % positive cores Clinical stage cT1c cT2 Pathological Gleason score 6 7 >8 Pathological stage pT2 pT3 Margin status Positive Negative Lymph node status Negative Positive High-risk disease
Median
IQR
64.9 49.3 6.75 0.14 0.7 10.3 18.7 2.5 63.7
61.5–67.7 37.7–67.0 5.32–8.34 0.09–0.18 0.5–1.0 7.7–15.0 13.0–22.8 1.9–3.1 48.9–79.6
22.0 33.3
22.0–25.0 13.6–50.0
18 (41.9) 25 (58.1) 21 (48.8) 22 (51.2) 29 (67.4) 9 (20.9) 5 (11.7)
16 (37.2) 27 (62.8) 25 (58.1) 15 (34.9) 3 (7) 29 (67.4) 14 (32.6) 12 (27.9) 31 (72.1) 41 (95.2) 2 (4.7) 15 (34.8)
ease; %p2PSA and PHI were significantly higher in those with a pathologic Gleason score ≥8, positive margins, and high-risk disease, and p2PSA and PHI were significantly higher in patients with N1 disease (all p values < 0.01). The Spearman’s rho (r) analysis demonstrated that the pathological stage positively correlates with p2PSA, %p2PSA, PHI, pathologic Gleason score, margin status, and lymph node status (rho = 0.428, p < 0.001; rho = 0.500, p < 0.001; rho = 0.684, p < 0.0001; rho = 0.394, p < 0.01; rho = 0.432, p < 0.01, and rho = 0.318, p < 0.05, respectively). A pathological Gleason score positively correlates with the biopsy Gleason score, PHI, and N status PHI and PC Aggressiveness
(rho = 0.458, p < 0.001; rho = 0.383, p < 0.050, and rho = 0.373, p < 0.05, respectively). Margin status positively correlates with %p2PSA and PHI (rho = 0.351, p < 0.05 and rho = 0.514, p < 0.001, respectively). N status positively correlates with p2PSA and PHI (rho = 0.329, p < 0.05 and rho = 0.320, p < 0.05, respectively). Finally, highrisk disease positively correlates with %p2PSA, PHI, pathological stage, and margin status (rho = 0.351, p < 0.05; rho = 0.514, p < 0.001; rho = 0.432, p < 0.001, and rho = 1.000, p < 0.0001, respectively). According to the bivariate analyses, p2PSA, %p2PSA, and PHI were accurate predictors of the presence of pT3 disease and high-risk disease and, together with the biopsy Gleason score, of a pathologic Gleason score ≥8. p2PSA was a predictor of pathological upgrading, whereas %p2PSA and PHI were accurate predictors of margin status. Finally, PHI and % positive core were accurate predictors of N status. At multivariate analysis, PHI was an independent predictor of the presence of pT3 disease, margin status, and high-risk disease (table 2). Predictive accuracy was quantified as the AUC for each outcome of interest according to a single predictor (table 3). The inclusion of p2PSA, %p2PSA, and PHI significantly increased the AUC of a basal multivariate model that included tPSA, fPSA, f/tPSA, clinical stage, biopsy Gleason score, and % of positive cores in the detection of pathological stage, margin status, and high-risk disease. However, there was a significant gain in predictive accuracy only for the detection of pT3 disease and high-risk disease. Table 4 describes the sensitivity and specificity at different PHI cutoff points in the prediction of pathological stage, margin status, and the presence of high-risk PC.
Discussion
In the current study, we prospectively tested the relationship between p2PSA and its derivatives, %p2PSA and PHI, and PC aggressiveness according to final pathology in a population of patients treated with mini-invasive RP for clinically organ-confined PC. Our assumptions supported the hypothesis that p2PSA and its derivatives, %p2PSA and PHI, may predict some paramount pathologic outcomes. In the univariate analyses, PHI emerged as the most accurate predictor of pathologic disease characteristics, i.e. the presence of pT3 disease, pathologic Gleason score ≥8, the presence of positive margins or lymph node invasion, and the presence of high-risk disease. Moreover, PHI reached independent predictor staUrol Int DOI: 10.1159/000379758
3
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Table 1. Patient characteristics and descriptive statistics
p2PSA
75.00 50.00
125.00
100.00
100.00
75.00 50.00
25.00
25.00
0
0 2
3
17 *35 25
*
75.00
6
17 25
50.00
*
125.00
25.00
0
39
17
25.00
*
75.00
6
17 35
50.00 25.00
0 0
39
125.00
*35
50.00
1
Gleason upgrading
100.00
75.00
0
35 25
50.00
8
100.00 p2PSA
p2PSA
100.00
6
75.00
Gleason score
39
39
0 7
Stage
125.00
*
25.00
p2PSA
p2PSA
100.00
125.00 p2PSA
39
125.00
0
1
0
1
Margin status
0
N status
1
High-risk disease
Fig. 1. p2PSA relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and presence of high-risk disease. * = Extreme outliers; ° = mild outliers.
4.00
37
%p2PSA
%p2PSA
6.00
2.00
4
0 2
8.00
8.00
6.00
6.00 %p2PSA
39
8.00
4.00
2.00
0
0
3
7
8.00
8.00
39
8.00
39
4.00
4.00
2.00
2.00
2.00
0
0
0
0
1 Margin status
39
6.00 %p2PSA
4.00
1
Gleason upgrading
6.00 %p2PSA
%p2PSA
6.00
*
43 0
8
Gleason score
*
39
4.00
2.00
Stage
*
0
1 N status
37
4 0
1
High-risk disease
presence of high-risk disease. * = Extreme outliers; ° = mild outliers.
4
Urol Int DOI: 10.1159/000379758
Mearini/Nunzi/Ferri/Bellezza/Lolli/ Porrozzi/Porena
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Fig. 2. Percentage of p2PSA to fPSA (%p2PSA) relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and
* *
6
37
9
100.00 50.00
250.00
250.00
200.00
200.00 37
150.00 100.00
0
5
0
2
3
*
200.00
6
150.00
PHI
PHI
250.00
39
100.00 50.00
*
0 0
250.00
39
*
200.00
100.00
39
6
150.00 100.00 50.00
5
0 1
1
Gleason upgrading
37
150.00
5 0
8
50.00 5
6
100.00
Gleason score
250.00
39
37
0
7
Stage
200.00
150.00
*
50.00
50.00 5
PHI
150.00
PHI
PHI
200.00
39
PHI
250.00
0
Margin status
5
0 1 N status
0
1
High-risk disease
Fig. 3. PHI relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and presence of high-risk disease. * = Ex-
tus when considering the presence of pT3 disease (p < 0.05), margin status, and the presence of high-risk disease. In a preoperative evaluation, adding p2PSA, %p2PSA, and PHI determination increased the accuracy of tPSA, fPSA, %fPSA, clinical stage, biopsy Gleason score, and % of positive cores in predicting the pathologic stage. In the current era of PSA-based PC active or opportunistic screening, increasing numbers of patients are diagnosed with early, localized PC, either indolent or aggressive. These men will consider numerous options, ranging from AS or focal therapy to RP or radiotherapy. The use of a more accurate marker (either biomarker or imaging-based ‘marker’), alone or in combination with other established variables that enable prediction of a clinically significant PC, could be extremely useful in the complex patient/physician decision-making process because PSA and %fPSA lack clear thresholds in balancing specificity and sensitivity for the prediction of aggressive or nonorgan-confined PC. To date, the indication for a policy of AS included a low biopsy Gleason score (≤6), PSA 66.1 92.8 >90.8 50.0 PHI and margin status >40.5 93.5 >59.6 74.1 >74.3 45.1 PHI and high-risk disease >40.5 100.00 >67.6 86.67 >90.8 46.67
Specificity
95% CI
76.8–100 66.1–99.8 23.0–77.0
13.7 82.7 96.5
3.9–31.7 64.2–94.2 82.2–99.9
78.6–99.2 55.4–88.1 27.3–64.0
16.6 75.0 100
2.1–48.4 42.8–94.5 73.5–100
78.2–100.0 59.5–98.3 21.3–73.4
14.2 85.7 96.4
4.0–32.7 67.3–96.0 81.7–99.9
considered the best standard, ‘with the most relevant information provided by the number and sites of positive prostate biopsies, the tumor grade, and the level of serum PSA, while multiparametric MRI should be used only if its results change patient management, and finally, MRI is not recommended for staging purposes in patients with low-risk PC’ [28]. In 2012, Guazzoni et al. [13] demonstrated that some PSA derivatives, such as p2PSA, %p2PSA, and PHI, may help in the prediction of the final pathologic outcomes. In particular, %p2PSA and PHI emerged as the most accurate predictors of locally advanced disease (pT3 disease), 8
Urol Int DOI: 10.1159/000379758
intermediate risk pathologic Gleason score ≥7 or Gleason score upgrading, and significant tumor volume (
Urologia
Received: January 21, 2015 Accepted: February 5, 2015 Published online: March 17, 2015
Urol Int DOI: 10.1159/000379758
Internationalis
Use of the Prostate Health Index for the Detection of Aggressive Prostate Cancer at Radical Prostatectomy Luigi Mearini a Elisabetta Nunzi a Carla Ferri c Guido Bellezza b Carolina Lolli a Carlo Porrozzi a Massimo Porena a
c
Department of Urology and b Institute of Pathologic Anatomy and Histology, University of Perugia, and Clinical Pathology and Haematology Laboratory, Azienda Ospedaliera di Perugia, Perugia, Italy
Key Words Pathologic examination · Prostate cancer · Prostate health index · Prostate-specific antigen · Radical prostatectomy
Abstract Introduction: In current study, we compared the accuracy of the PSA isoform p2PSA and its derivatives, the percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI) in the detection of prostate cancer (PC) characteristics at the final pathology with respect to reference standards. Materials and Methods: This was an observational prospective study evaluating 43 consecutive PC patients treated with laparoscopic/robotic radical prostatectomy (RP). Logistic regression models were fitted to test the predictors of pT3 stage, pathologic Gleason score ≥8 or Gleason score upgrading, margin status, lymph node invasion, and the presence of high-risk disease (pT3 disease and/or Gleason score ≥8 and/or positive lymph node). The comparative base model included tPSA, clinical stage, biopsy Gleason score, and percentage of positive core. Results: Seventeen patients (39.5%) were affected by pT3 disease or had a pathologic Gleason score ≥8; positive margins were detected in 12 patients (27.9%), lymph node invasion was found in 2 patients (4.7%), and 15 patients (34.8%) harbored high-risk disease. In the univariate analysis, p2PSA, %p2PSA, and PHI were significant predictors of pT3 disease, pathologic Gleason score, and the
© 2015 S. Karger AG, Basel 0042–1138/15/0000–0000$39.50/0 E-Mail [email protected] www.karger.com/uin
presence of high-risk disease (all p < 0.05), whereas only PHI was an independent predictor of pT3 disease, margin status, and presence of high-risk disease, increasing the accuracy of a base multivariable model by 6.3% (p < 0.05) and 4.2% (p < 0.05) for the prediction of pT3 and high-risk disease, respectively. Conclusions: p2PSA and its derivatives, primarily PHI, were significant predictors of unfavorable PC characteristics as detected at the final pathology, thus improving the clinical performance of standard prognostic factors for aggressive disease. © 2015 S. Karger AG, Basel
Introduction
During the process of diagnosing prostate cancer (PC), active or opportunistic screening based on the prostatespecific antigen (PSA) leads to a significant number of patients demonstrating organ-confined or low-risk disease [1]. In this context, overdiagnosis leading to overtreatment is an important adverse effect of such diagnostic intervention. The promise of a screening, i.e. that cancers should be detected as early as possible to maximize the chance of cure and reduce mortality, in PC frequently translates to overdiagnosis and harm [2]. There is a wide range of standard treatments for men with localized PC, ranging from active surveillance (AS) Luigi Mearini, MD Department of Urology, Azienda Ospedaliera di Perugia University of Perugia, Perugia Sant’Andrea delle Fratte, IT–06100 Perugia (Italy) E-Mail luigi.mearini @ tin.it
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a
or focal therapy to radical prostatectomy (RP) or radiation therapy. According to life expectancy and the characteristics of the disease, the best treatment should provide the patient with an appropriate, well-balanced harm/ benefit ratio, i.e. optimal oncologic and functional outcomes. Currently, the available clinical parameters used in the evaluation of PC, such as PSA, digital rectal examination (DRE), and Gleason score, fail to accurately predict under- or overtreatment of PC. Therefore, many predictive and prognostic tools have been developed to assist patients and physicians in their difficult clinical decisionmaking process before [3, 4] and after biopsy [5–7]. All of the prognostic tools aim to reduce errors in the clinical evaluation of PC aggressiveness. In this context, multiparametric MRI, a new imaging tool, should help determine the best treatment option for a patient with a new diagnosis of PC [8], and new biomarkers are welcome to reduce error margins in discriminating between clinically significant and insignificant PC. Recent studies have shown that the PSA isoformproPSA (p2PSA) and its derivatives, percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI) (Beckman Coulter, Brea, Calif., USA), improve the accuracy of total PSA (tPSA) and the percentage of free PSA (%fPSA) in predicting the presence of PC at prostate biopsy [9–12] and are predictors of PC aggressiveness at biopsy. More recently, five studies [13–17] have investigated the role of p2PSA and its derivatives in the prediction of PC aggressiveness confirmed at final pathology after RP. The aim of the current prospective study was to compare these biomarkers with the established prognostic characteristics in the prediction of pathologic PC within a contemporary cohort of patients who underwent laparoscopic RP for clinically localized PC at a single highvolume institution.
tients gave their written informed consent. The principles and policies of the Declaration of Helsinki were followed. The primary endpoint of the study was to determine the accuracy of p2PSA, %p2PSA, and PHI in predicting (1) the presence of extracapsular disease (pT3), (2) the presence of a pathologic Gleason score ≥8 or pathological upgrading, (3) the presence of a positive margin, (4) the presence of positive lymph nodes, and (5) the presence of pathological high-risk disease (defined as pT3 and/or Gleason score ≥8 and/or positive lymph nodes). The biomarkers p2PSA, %p2PSA, and PHI were used as the index tests and were compared with the accepted reference standard tests: tPSA, free PSA (fPSA), fPSA-to-tPSA ratio (%fPSA), Gleason score at biopsy, percentage of positive core at biopsy, and clinical stage. A blood sample was drawn the day before surgery and prior to any manipulations (e.g. DRE, enema) that might cause an increase in biomarkers. Blood samples were processed using the UniCel DxI800 Immunoassay System analyzer (Beckman Coulter) and were managed according to the criteria described by Semjonow et al. [18]. Blood sample analysis was performed using the Hybritechcalibrated Access tPSA (Beckman Coulter) and fPSA assay. Biopsy cores and RP specimens were processed and evaluated by a single experienced genitourinary pathologist (G.B.). PC was graded according to the definitions of the 2005 consensus conference of the International Society of Urological Pathology. Statistical Analysis The Kolmogorov-Smirnov test was used to assess the normal distribution of variables. The Mann-Whitney U test was used for comparisons of ordinal and nonnormally distributed continuous variables. Spearman’s rho coefficient was used to test correlations between continuous and ordinal variables. Bivariate and multivariate logistic regression models were fitted for the prediction of the presence of pT3, the presence of a pathologic Gleason score >8 or pathological upgrading, margin status, lymph node invasion, and finally the presence of high-risk PC. The logistic regression model goodness-of-fit was checked using the Hosmer-Lemeshow test. Odds ratios (ORs) with 95% CI were also calculated. Predictive accuracy was quantified as the area under the receiver operating characteristics curve (AUC). All calculations were carried out using SPSS 13. p < 0.05 was considered significant.
Materials and Methods Our observational prospective study cohort consisted of 43 consecutive patients with biopsy-proven, clinically localized PC, who were consecutively recruited between October 2013 and April 2014 and who underwent either laparoscopic or robot-assisted RP at our institution. Local staging processes included DRE and transrectal ultrasound scan; bone scintigraphy and CT scan were scheduled according to risk classification. None of the patients received drugs that could have altered the PSA values, such as dutasteride and finasteride, or neoadjuvant androgen-deprivation therapy. The hospital ethics committee approved the study, representing the expansion of clinical trial NCT01672411, and all of the pa-
2
Urol Int DOI: 10.1159/000379758
The descriptive characteristics of the overall study population are shown in table 1. At clinical evaluation, 29 patients (67.4%) were diagnosed with a Gleason score ≤6, and 16 (37.2%) and 27 (67.8%) patients were diagnosed with cT1c and cT2 disease, respectively. Forty patients (93%) were diagnosed with a pathologic Gleason score ≤7 PC, and 14 (32.6%) and 2 (4.7%) patients were diagnosed with pT3 and pN1 disease, respectively. The negative margin rate was 72.1%. Overall, 14 patients (32.5%) were classified as harboring high-risk disease. As shown in figures 1–3, p2PSA, %p2PSA, and PHI levels were significantly higher in patients with pT3 disMearini/Nunzi/Ferri/Bellezza/Lolli/ Porrozzi/Porena
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Results
n (%) Age, years Prostate volume, ml tPSA, ng/ml PSA density, ng/ml2 fPSA, ng/ml %fPSA p2PSA, pg/ml %p2PSA PHI DRE Negative Positive Transrectal ultrasound Negative Positive Biopsy Gleason score 6 7 >8 Number of biopsy cores % positive cores Clinical stage cT1c cT2 Pathological Gleason score 6 7 >8 Pathological stage pT2 pT3 Margin status Positive Negative Lymph node status Negative Positive High-risk disease
Median
IQR
64.9 49.3 6.75 0.14 0.7 10.3 18.7 2.5 63.7
61.5–67.7 37.7–67.0 5.32–8.34 0.09–0.18 0.5–1.0 7.7–15.0 13.0–22.8 1.9–3.1 48.9–79.6
22.0 33.3
22.0–25.0 13.6–50.0
18 (41.9) 25 (58.1) 21 (48.8) 22 (51.2) 29 (67.4) 9 (20.9) 5 (11.7)
16 (37.2) 27 (62.8) 25 (58.1) 15 (34.9) 3 (7) 29 (67.4) 14 (32.6) 12 (27.9) 31 (72.1) 41 (95.2) 2 (4.7) 15 (34.8)
ease; %p2PSA and PHI were significantly higher in those with a pathologic Gleason score ≥8, positive margins, and high-risk disease, and p2PSA and PHI were significantly higher in patients with N1 disease (all p values < 0.01). The Spearman’s rho (r) analysis demonstrated that the pathological stage positively correlates with p2PSA, %p2PSA, PHI, pathologic Gleason score, margin status, and lymph node status (rho = 0.428, p < 0.001; rho = 0.500, p < 0.001; rho = 0.684, p < 0.0001; rho = 0.394, p < 0.01; rho = 0.432, p < 0.01, and rho = 0.318, p < 0.05, respectively). A pathological Gleason score positively correlates with the biopsy Gleason score, PHI, and N status PHI and PC Aggressiveness
(rho = 0.458, p < 0.001; rho = 0.383, p < 0.050, and rho = 0.373, p < 0.05, respectively). Margin status positively correlates with %p2PSA and PHI (rho = 0.351, p < 0.05 and rho = 0.514, p < 0.001, respectively). N status positively correlates with p2PSA and PHI (rho = 0.329, p < 0.05 and rho = 0.320, p < 0.05, respectively). Finally, highrisk disease positively correlates with %p2PSA, PHI, pathological stage, and margin status (rho = 0.351, p < 0.05; rho = 0.514, p < 0.001; rho = 0.432, p < 0.001, and rho = 1.000, p < 0.0001, respectively). According to the bivariate analyses, p2PSA, %p2PSA, and PHI were accurate predictors of the presence of pT3 disease and high-risk disease and, together with the biopsy Gleason score, of a pathologic Gleason score ≥8. p2PSA was a predictor of pathological upgrading, whereas %p2PSA and PHI were accurate predictors of margin status. Finally, PHI and % positive core were accurate predictors of N status. At multivariate analysis, PHI was an independent predictor of the presence of pT3 disease, margin status, and high-risk disease (table 2). Predictive accuracy was quantified as the AUC for each outcome of interest according to a single predictor (table 3). The inclusion of p2PSA, %p2PSA, and PHI significantly increased the AUC of a basal multivariate model that included tPSA, fPSA, f/tPSA, clinical stage, biopsy Gleason score, and % of positive cores in the detection of pathological stage, margin status, and high-risk disease. However, there was a significant gain in predictive accuracy only for the detection of pT3 disease and high-risk disease. Table 4 describes the sensitivity and specificity at different PHI cutoff points in the prediction of pathological stage, margin status, and the presence of high-risk PC.
Discussion
In the current study, we prospectively tested the relationship between p2PSA and its derivatives, %p2PSA and PHI, and PC aggressiveness according to final pathology in a population of patients treated with mini-invasive RP for clinically organ-confined PC. Our assumptions supported the hypothesis that p2PSA and its derivatives, %p2PSA and PHI, may predict some paramount pathologic outcomes. In the univariate analyses, PHI emerged as the most accurate predictor of pathologic disease characteristics, i.e. the presence of pT3 disease, pathologic Gleason score ≥8, the presence of positive margins or lymph node invasion, and the presence of high-risk disease. Moreover, PHI reached independent predictor staUrol Int DOI: 10.1159/000379758
3
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Table 1. Patient characteristics and descriptive statistics
p2PSA
75.00 50.00
125.00
100.00
100.00
75.00 50.00
25.00
25.00
0
0 2
3
17 *35 25
*
75.00
6
17 25
50.00
*
125.00
25.00
0
39
17
25.00
*
75.00
6
17 35
50.00 25.00
0 0
39
125.00
*35
50.00
1
Gleason upgrading
100.00
75.00
0
35 25
50.00
8
100.00 p2PSA
p2PSA
100.00
6
75.00
Gleason score
39
39
0 7
Stage
125.00
*
25.00
p2PSA
p2PSA
100.00
125.00 p2PSA
39
125.00
0
1
0
1
Margin status
0
N status
1
High-risk disease
Fig. 1. p2PSA relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and presence of high-risk disease. * = Extreme outliers; ° = mild outliers.
4.00
37
%p2PSA
%p2PSA
6.00
2.00
4
0 2
8.00
8.00
6.00
6.00 %p2PSA
39
8.00
4.00
2.00
0
0
3
7
8.00
8.00
39
8.00
39
4.00
4.00
2.00
2.00
2.00
0
0
0
0
1 Margin status
39
6.00 %p2PSA
4.00
1
Gleason upgrading
6.00 %p2PSA
%p2PSA
6.00
*
43 0
8
Gleason score
*
39
4.00
2.00
Stage
*
0
1 N status
37
4 0
1
High-risk disease
presence of high-risk disease. * = Extreme outliers; ° = mild outliers.
4
Urol Int DOI: 10.1159/000379758
Mearini/Nunzi/Ferri/Bellezza/Lolli/ Porrozzi/Porena
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Fig. 2. Percentage of p2PSA to fPSA (%p2PSA) relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and
* *
6
37
9
100.00 50.00
250.00
250.00
200.00
200.00 37
150.00 100.00
0
5
0
2
3
*
200.00
6
150.00
PHI
PHI
250.00
39
100.00 50.00
*
0 0
250.00
39
*
200.00
100.00
39
6
150.00 100.00 50.00
5
0 1
1
Gleason upgrading
37
150.00
5 0
8
50.00 5
6
100.00
Gleason score
250.00
39
37
0
7
Stage
200.00
150.00
*
50.00
50.00 5
PHI
150.00
PHI
PHI
200.00
39
PHI
250.00
0
Margin status
5
0 1 N status
0
1
High-risk disease
Fig. 3. PHI relative to tumor stage, Gleason score, Gleason upgrading, margin status, N status, and presence of high-risk disease. * = Ex-
tus when considering the presence of pT3 disease (p < 0.05), margin status, and the presence of high-risk disease. In a preoperative evaluation, adding p2PSA, %p2PSA, and PHI determination increased the accuracy of tPSA, fPSA, %fPSA, clinical stage, biopsy Gleason score, and % of positive cores in predicting the pathologic stage. In the current era of PSA-based PC active or opportunistic screening, increasing numbers of patients are diagnosed with early, localized PC, either indolent or aggressive. These men will consider numerous options, ranging from AS or focal therapy to RP or radiotherapy. The use of a more accurate marker (either biomarker or imaging-based ‘marker’), alone or in combination with other established variables that enable prediction of a clinically significant PC, could be extremely useful in the complex patient/physician decision-making process because PSA and %fPSA lack clear thresholds in balancing specificity and sensitivity for the prediction of aggressive or nonorgan-confined PC. To date, the indication for a policy of AS included a low biopsy Gleason score (≤6), PSA 66.1 92.8 >90.8 50.0 PHI and margin status >40.5 93.5 >59.6 74.1 >74.3 45.1 PHI and high-risk disease >40.5 100.00 >67.6 86.67 >90.8 46.67
Specificity
95% CI
76.8–100 66.1–99.8 23.0–77.0
13.7 82.7 96.5
3.9–31.7 64.2–94.2 82.2–99.9
78.6–99.2 55.4–88.1 27.3–64.0
16.6 75.0 100
2.1–48.4 42.8–94.5 73.5–100
78.2–100.0 59.5–98.3 21.3–73.4
14.2 85.7 96.4
4.0–32.7 67.3–96.0 81.7–99.9
considered the best standard, ‘with the most relevant information provided by the number and sites of positive prostate biopsies, the tumor grade, and the level of serum PSA, while multiparametric MRI should be used only if its results change patient management, and finally, MRI is not recommended for staging purposes in patients with low-risk PC’ [28]. In 2012, Guazzoni et al. [13] demonstrated that some PSA derivatives, such as p2PSA, %p2PSA, and PHI, may help in the prediction of the final pathologic outcomes. In particular, %p2PSA and PHI emerged as the most accurate predictors of locally advanced disease (pT3 disease), 8
Urol Int DOI: 10.1159/000379758
intermediate risk pathologic Gleason score ≥7 or Gleason score upgrading, and significant tumor volume (
