Alessandro Larcher

Updated Nomogram Predicting Lymph Node Invasion in Patients with Prostate Cancer Undergoing Extended Pelvic Lymph Node Dissection: The Essential Importance of Percentage of Positive Cores

BACKGROUND Few predictive models aimed at predicting the presence of lymph node invasion (LNI) in patients with prostate cancer (PCa) treated with extended pelvic lymph node dissection (ePLND) are available to date. OBJECTIVE Update a nomogram predicting the presence of LNI in patients treated with ePLND at the time of radical prostatectomy (RP). DESIGN, SETTING, AND PARTICIPANTS The study included 588 patients with clinically localised PCa treated between September 2006 and October 2010 at a single tertiary referral centre. INTERVENTION All patients underwent RP and ePLND invariably including removal of obturator, external iliac, and hypogastric nodes. MEASUREMENTS Prostate-specific antigen, clinical stage, and primary and secondary biopsy Gleason grade as well as percentage of positive cores were included in univariable (UVA) and multivariable (MVA) logistic regression models predicting LNI and formed the basis for the regression coefficient-based nomogram. The area under the curve (AUC) method was used to quantify the predictive accuracy (PA) of the model. RESULTS AND LIMITATIONS The mean number of lymph nodes removed and examined was 20.8 (median: 19; range: 10-52). LNI was found in 49 of 588 patients (8.3%). All preoperative PCa characteristics differed significantly between LNI-positive and LNI-negative patients (all p<0.001). In UVA predictive accuracy analyses, percentage of positive cores was the most accurate predictor of LNI (AUC: 79.5%). At MVA, clinical stage, primary biopsy Gleason grade, and percentage of positive cores were independent predictors of LNI (all p≤0.006). The updated nomogram demonstrated a bootstrap-corrected PA of 87.6%. Using a 5% nomogram cut-off, 385 of 588 patients (65.5%) would be spared ePLND. and LNI would be missed in only 6 patients (1.5%). The sensitivity, specificity, and negative predictive value associated with the 5% cut-off were 87.8%, 70.3%, and 98.4%, respectively. The relatively low number of patients included as well as the lack of an external validation represent the main limitations of our study. CONCLUSIONS We report the first update of a nomogram predicting the presence of LNI in patients treated with ePLND. The nomogram maintained high accuracy, even in more contemporary patients (87.6%). Because percentage of positive cores represents the foremost predictor of LNI, its inclusion should be mandatory in any LNI prediction model. Based on our model, those patients with a LNI risk<5% might be safely spared ePLND.

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

BACKGROUND Currently available predictive models fail to assist clinical decision making in prostate cancer (PCa) patients who are possible candidates for radical prostatectomy (RP). New biomarkers would be welcome. OBJECTIVE Test the hypothesis that prostate-specific antigen (PSA) isoform p2PSA and its derivates, percentage of p2PSA to free PSA (%p2PSA) and the Prostate Health Index (PHI), predict PCa characteristics at final pathology after RP. DESIGN, SETTING, AND PARTICIPANTS An observational prospective study was performed in 350 consecutive men diagnosed with clinically localised PCa who underwent RP. MEASUREMENTS We determined the predictive accuracy of serum total PSA (tPSA), free PSA (fPSA), fPSA-to-tPSA ratio (%fPSA), p2PSA, %p2PSA, and PHI. The primary end point was to determine the accuracy of these biomarkers in predicting the presence of pT3 disease, pathologic Gleason sum≥7, Gleason sum upgrading, and tumour volume<0.5 ml. INTERVENTION Open retropubic and robot-assisted laparoscopic RP was performed. Pelvic lymphadenectomy was performed according to baseline oncologic parameters and the surgeons judgement. RESULTS AND LIMITATIONS The %p2PSA and PHI levels were significantly higher in patients with pT3 disease, pathologic Gleason sum≥7, and Gleason sum upgrading (all p values<0.001). Conversely, %p2PSA and PHI levels were significantly lower in patients with tumour volume<0.5 ml (p<0.001). By univariate analysis, both %p2PSA and PHI were accurate predictors of pT3 disease, pathologic Gleason sum≥7, Gleason sum upgrading, and tumour volume<0.5 ml. By multivariate analyses, the inclusion of both %p2PSA and PHI significantly increased the predictive accuracy of a base multivariate model (excluding the tumour volume prediction for both variables, and Gleason sum upgrading for the model including %p2PSA) that included patient age, tPSA, fPSA, f/tPSA, clinical stage, and biopsy Gleason sum. CONCLUSIONS We found that p2PSA and its derivatives are predictors of PCa characteristics at final pathology after RP and are more accurate than currently available markers.

Identifying optimal candidates for local treatment of the primary tumor among patients diagnosed with metastatic prostate cancer: a SEER-based study.

UNLABELLED A recent study observed a survival benefit in men diagnosed with metastatic prostate cancer (mPCa) and managed with local treatment of the primary tumor (LT; either radical prostatectomy plus pelvic lymph node dissection or radiation therapy). We tested the hypothesis that only specific mPCa patients would benefit from LT and that the potential benefit would vary based on primary tumor characteristics. A total of 8197 mPCa patients at diagnosis (M1a, M1b, and M1c) were identified using the Surveillance Epidemiology and End Results database (2004-2011) and were divided according to treatment type: LT versus nonlocal treatment of the primary tumor (NLT; either androgen deprivation therapy or observation). Multivariable Cox regression analysis was used to predict cancer-specific mortality (CSM) in patients that received NLT. To assess whether the benefit of LT was different by baseline risk, we tested an interaction with CSM risk and LT. At multivariable analysis, all predictors were significantly associated with CSM, and the interaction test was statistically significant (p<0.0001). Local treatment of the primary tumor, compared with NLT, conferred a higher CSM-free survival rate in patients with a predicted CSM risk <40%. The number needed to treat according to the predicted CSM risk at 3 yr after diagnosis remained substantially constant from 10% to 30%, whereas it exponentially increased for predicted CSM risk >40%. These results should serve as a foundation for future prospective trials. PATIENT SUMMARY Among metastatic prostate cancer patients, the potential benefit of local treatment to the primary tumor depends greatly on tumor characteristics, and patient selection is essential to avoid either over- or undertreatment.

Head-to-Head Comparison of Prostate Health Index and Urinary PCA3 for Predicting Cancer at Initial or Repeat Biopsy

PURPOSE We performed a head-to-head comparison of the PHI (Prostate Health Index) and PCA3. MATERIALS AND METHODS We evaluated PHI and PCA3 performance in 211 patients undergoing initial (116) or repeat (95) prostate biopsy. Multivariable logistic regression analysis was done using the AUC to test the accuracy of PHI and PCA3 for predicting prostate cancer in the overall population and in each setting. Decision curve analysis was used to compare the clinical benefit of different models. RESULTS Overall, the AUC of the PHI (0.70) was significantly higher than the AUC of PCA3 (0.59), total prostate specific antigen (0.56) and free-to-total prostate specific antigen (0.60) (p = 0.043, 0.002 and 0.037, respectively). PHI was more accurate than PCA3 for predicting prostate cancer in the initial setting (AUC 0.69 vs 0.57) and in the repeat setting (AUC 0.72 vs 0.63), although no statistically significant difference was observed. Including PCA3 in the base multivariable model (prostate specific antigen plus free-to-total prostate specific antigen plus prostate volume) did not increase predictive accuracy in either setting (AUC 0.79 vs 0.80 and 0.75 vs 0.76, respectively). Conversely, including PHI in the base multivariable model improved predictive accuracy by 5% (AUC 0.79 to 0.84) and 6% (AUC 0.75 to 0.81) in the initial and repeat prostate biopsy settings, respectively. On decision curve analysis the highest net benefit was observed when PHI was added to the base multivariable model. CONCLUSIONS PHI and PCA3 provide a significant increase in sensitivity and specificity compared to all other examined markers and they may help guide biopsy decisions. PCA3 does not increase the accuracy of predicting prostate cancer when PHI is assessed.

Clinical performance of serum prostate-specific antigen isoform (-2)proPSA (p2PSA) and its derivatives, %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer: results from a multicentre European study, the PROMEtheuS project

To test the sensitivity, specificity and accuracy of serum prostate‐specific antigen isoform [‐2]proPSA (p2PSA), %p2PSA and the prostate health index (PHI), in men with a family history of prostate cancer (PCa) undergoing prostate biopsy for suspected PCa. To evaluate the potential reduction in unnecessary biopsies and the characteristics of potentially missed cases of PCa that would result from using serum p2PSA, %p2PSA and PHI.

Feasibility and Preliminary Clinical Outcomes of Robotic Laparoendoscopic Single-Site (R-LESS) Pyeloplasty Using a New Single-Port Platform

This study tested the technical feasibility and short-term perioperative outcomes of the novel da Vinci Single-Site Instrumentation platform for the treatment of upper ureteropelvic junction obstruction (UPJO) in a selected group of patients. Nine patients underwent robotic laparoendoscopic single-site (R-LESS) pyeloplasty using a new single-site platform for UPJO at our department of urology. All the procedures were completed without the need for traditional robotic surgery or laparoscopic/open conversion, although in one patient with congenital hepatomegaly it was necessary to use an auxiliary 3-mm trocar to retract the liver properly and expose the surgical field. Mean operative time was 166 min, and no intraoperative complications were recorded. The indwelling catheter was removed on postoperative day 2 in five patients and on postoperative day 3 in four patients. Patients were discharged the day after drain removal. One patient experienced transient hyperpyrexia, treated with antibiotics. No other complications were observed. All patients had the DJ stent removed 4 wk after surgery, following a negative urine culture and abdominal ultrasound evaluation. The five patients who reached a 3-mo follow-up had a clinical resolution of preoperative symptoms and hydronephrosis at the abdominal ultrasound. The same results were maintained in the two patients with 6-mo follow-up evaluations. In selected patients, R-LESS pyeloplasty using the new single-port platform appears to be a technically feasible and reproducible surgical procedure for the minimally invasive treatment of UPJO. Prolonged follow-up and larger series are required to confirm its potential role as a valid alternative to standard robotic pyeloplasty.

Multicenter European External Validation of a Prostate Health Index–based Nomogram for Predicting Prostate Cancer at Extended Biopsy

BACKGROUND External validation of a prediction tool is mandatory to assess the tools accuracy and generalizability within different patient cohorts. OBJECTIVE To externally validate a previously developed Prostate Health Index (PHI)-based nomogram for predicting the presence of prostate cancer (PCa) at biopsy. DESIGN, SETTING, AND PARTICIPANTS The study population consisted of 883 patients who were scheduled for a prostate biopsy at one of five European tertiary care centers. Total prostate-specific antigen (tPSA), free prostate-specific antigen (fPSA), and [-2]pro-prostate-specific antigen (p2PSA) levels were determined. The fPSA-to-tPSA ratio (%fPSA), p2PSA, and PHI ([p2PSA / fPSA] × √tPSA) were calculated. INTERVENTION Extended initial and repeat prostate biopsy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Logistic regression models were fitted to test the predictors of PCa and to determine their predictive accuracy. A calibration plot was used to evaluate the extent of overestimation or underestimation between nomogram predictions and observed PCa rate. Decision curve analysis (DCA) provided an estimate of the net benefit obtained by using the PHI-based nomogram. RESULTS AND LIMITATIONS Of 833 patients, 365 (41.3%) were diagnosed with PCa at extended prostate biopsy. In accuracy analyses, PHI was the most informative predictor of PCa (0.68), outperforming tPSA (0.51) and %fPSA (0.64). The predictive accuracy of the previously developed nomogram was 75.2% (95% confidence interval, 71.4-78.1). Calibration of the nomogram was good in patients at a low to intermediate predicted probability of PCa, while calibration was suboptimal, with a tendency to overestimate the presence of PCa, in high-risk patients. Finally, DCA demonstrated that the use of the PHI-based nomogram resulted in the highest net benefit. The main limitation of the study is the fact that only Caucasian patients were included. CONCLUSIONS At external validation, the previously developed PHI-based nomogram confirmed its ability to determine the presence of PCa at biopsy. These findings provide further evidence supporting the potential role of the nomogram in the biopsy decision pathway for European men with suspected PCa. PATIENT SUMMARY In the current study, we externally validated a Prostate Health Index-based nomogram to predict the presence of prostate cancer (PCa) at biopsy. This tool may help clinicians determine the need for a prostate biopsy in European patients with suspected PCa.

Development and Internal Validation of a Prostate Health Index Based Nomogram for Predicting Prostate Cancer at Extended Biopsy

PURPOSE We developed and validated a Prostate Health Index (Beckman Coulter, Brea, California) based nomogram to predict prostate cancer at extended prostate biopsy. MATERIALS AND METHODS The study population consisted of 729 patients who were scheduled for prostate biopsy following suspicious digital rectal examination and/or increased prostate specific antigen. Total and free prostate specific antigen, percent free-to-total prostate specific antigen, [-2]proPSA and the prostate health index [([-2]proPSA/free prostate specific antigen) × √total prostate specific antigen)] were determined. Logistic regression models were fitted to test prostate cancer predictors. Predictive accuracy estimates of biopsy outcome predictions were quantified. Regression coefficients were used to create a decision making tool to predict prostate cancer. A calibration plot was used to evaluate the extent of overestimating or underestimating the observed prostate cancer rate. Decision curve analysis provided an estimate of the net benefit obtained using the prostate health index based nomogram. RESULTS Overall 280 of 729 patients (38.4%) were diagnosed with prostate cancer at extended prostate biopsy. On accuracy analyses prostate health index emerged as the most informative predictor of prostate cancer (AUC 0.70) compared to established predictors, such as total prostate specific antigen (0.51) and percent free-to-total prostate specific antigen (0.62). Including the prostate health index in a multivariable logistic regression model based on patient age, prostate volume, digital rectal examination and biopsy history significantly increased predictive accuracy by 7% from 0.73 to 0.80 (p <0.001). Nomogram calibration was good. Decision curve analysis showed that using the prostate health index based nomogram resulted in the highest net benefit. CONCLUSIONS The prostate health index based nomogram can assist clinicians in the decision to perform biopsy by providing an accurate estimation of an individual risk of prostate cancer.

Serum index test %[-2]proPSA and Prostate Health Index are more accurate than prostate specific antigen and %fPSA in predicting a positive repeat prostate biopsy.

PURPOSE We tested the hypothesis that serum isoform [-2]proPSA derivatives %p2PSA and Prostate Health Index are accurate predictors of prostate cancer in men scheduled for repeat biopsy. MATERIALS AND METHODS The study was an observational prospective evaluation of a clinical cohort of men with 1 or 2 previous negative prostate biopsies, with persistent suspicion of prostate cancer. They were enrolled in the study to determine the diagnostic accuracy of %p2PSA using the formula, (p2PSA pg/ml)/(free prostate specific antigen ng/ml × 1,000)]× 100, and Beckman-Coulter Prostate Health Index using the formula, (p2PSA/free prostate specific antigen) × √total prostate specific antigen), and to compare it with the accuracy of established prostate cancer serum tests (total prostate specific antigen, free prostate specific antigen and percent free prostate specific antigen). Multivariable logistic regression models were complemented by predictive accuracy analysis and decision curve analysis. RESULTS Prostate cancer was found in 71 of 222 (31.9%) subjects. %p2PSA and Prostate Health Index were the most accurate predictors of disease. %p2PSA significantly outperformed total prostate specific antigen, free prostate specific antigen, percent free prostate specific antigen and p2PSA in the prediction of prostate cancer (p ≤0.01), but not Prostate Health Index (p = 0.094). Prostate Health Index significantly outperformed total prostate specific antigen and p2PSA (p ≤0.001) but not free prostate specific antigen (p = 0.109) and free/total prostate specific antigen (p = 0.136). In multivariable logistic regression models %p2PSA and Prostate Health Index achieved independent predictor status, and significantly increased the accuracy of multivariable models including prostate specific antigen and prostate volume with or without percent free prostate specific antigen and prostate specific antigen density by 8% to 11% (p ≤0.034). At a %p2PSA cutoff of 1.23, 153 (68.9%) biopsies could have been avoided, missing prostate cancer in 6 patients. At a Prostate Health Index cutoff of 28.8, 116 (52.25%) biopsies could have been avoided, missing prostate cancer in 6 patients. CONCLUSIONS Serum %p2PSA and Prostate Health Index are more accurate than standard reference tests in predicting repeat prostate biopsy outcome, and could avoid unnecessary repeat biopsies.

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.

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.