Expanding Active Surveillance Inclusion Criteria: A Novel Nomogram Including Preoperative Clinical Parameters and Magnetic Resonance Imaging Findings

[68Ga]Ga‑PSMA‑617 PET-based radiomics model to identify candidates for active surveillance amongst patients with GGG 1-2 prostate cancer at biopsy

PURPOSE

To develop a radiomics-based model using [68Ga]Ga-PSMA PET/CT to predict postoperative adverse pathology (AP) in patients with biopsy Gleason Grade Group (GGG) 1-2 prostate cancer (PCa), assisting in the selection of patients for active surveillance (AS).

METHODS

A total of 75 men with biopsy GGG 1-2 PCa who underwent radical prostatectomy (RP) were enrolled. The patients were randomly divided into a training group (70%) and a testing group (30%). Radiomics features of entire prostate were extracted from the [68Ga]Ga-PSMA PET scans and selected using the minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator regression model. Logistic regression analyses were conducted to construct the prediction models. Receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curve were employed to evaluate the diagnostic value, clinical utility, and predictive accuracy of the models, respectively.

RESULTS

Among the 75 patients, 30 had AP confirmed by RP. The clinical model showed an area under the curve (AUC) of 0.821 (0.695-0.947) in the training set and 0.795 (0.603-0.987) in the testing set. The radiomics model achieved AUC values of 0.830 (0.720-0.941) in the training set and 0.829 (0.624-1.000) in the testing set. The combined model, which incorporated the Radiomics score (Radscore) and free prostate-specific antigen (FPSA)/total prostate-specific antigen (TPSA), demonstrated higher diagnostic efficacy than both the clinical and radiomics models, with AUC values of 0.875 (0.780-0.970) in the training set and 0.872 (0.678-1.000) in the testing set. DCA showed that the net benefits of the combined model and radiomics model exceeded those of the clinical model.

CONCLUSION

The combined model shows potential in stratifying men with biopsy GGG 1-2 PCa based on the presence of AP at final pathology and outperforms models based solely on clinical or radiomics features. It may be expected to aid urologists in better selecting suitable patients for AS.

Proficiency score as a predictor of early trifecta achievement during the learning curve of robot-assisted radical prostatectomy for high-risk prostate cancer: Results of a multicentric series

Background

Recently, an innovative tool called "proficiency score" was introduced to assess the learning curve for robot-assisted radical prostatectomy (RARP). However, the initial study only focused on patients with low-risk prostate cancer for whom pelvic lymph node dissection (PLND) was not required. To address this issue, we aimed to validate proficiency scores of a contemporary multicenter cohort of patients with high-risk prostate cancer treated with RARP plus extended PLND by trainee surgeons.

Material and methods

Between 2010 and 2020, 4 Italian institutional prostate-cancer datasets were merged and queried for "RARP" and "high-risk prostate cancer." High-risk prostate cancer was defined according to the most recent European Association of Urology guidelines as follows: prostate-specific antigen >20 ng/mL, International Society of Urological Pathology ≥4, and/or clinical stage (cT) ≥ 2c on preoperative imaging. The selected cohort (n = 144) included clinical cases performed by trainee surgeons (n = 4) after completing their RARP learning curve (50 procedures for low-risk prostate cancer). The outcome of interest, the proficiency score, was defined as the coexistence of all the following criteria: a comparable operation time to the interquartile range of the mentor surgeon at each center, absence of any significant perioperative complications Clavien-Dindo Grade 3-5, no perioperative blood transfusions, and negative surgical margins. A logistic binary regression model was built to identify the predictors of 1-year trifecta achievement in the trainee cohort. For all statistical analyses, a 2-sided p < 0.05 was considered significant.

Results

A proficiency score was achieved in 42.3% patients. At univariable level, proficiency score was associated with 1-year trifecta achievement (odds ratio, 8.77; 95% confidence interval, 2.42-31.7; p = 0.001). After multivariable adjustments for age, nerve-sparing, and surgical technique, the proficiency score independently predicted 1-year trifecta achievement (odds ratio, 9.58; 95% confidence interval, 1.83-50.1; p = 0.007).

Conclusions

Our findings support the use of proficiency scores in patients and require extended PLND in addition to RARP.

MRI lesion size is more important than the number of positive biopsy cores in predicting adverse features and recurrence after radical prostatectomy: implications for active surveillance criteria in intermediate-risk patients

INTRODUCTION

To determine associations between prostate cancer (PCa) tumor burden measured on biopsy or multiparametric magnetic resonance imaging (mpMRI) and outcomes in intermediate-risk (IR) International Society of Urological Pathology (ISUP) grade 2 men managed with primary radical prostatectomy (RP).

METHODS

This retrospective, multicenter study was conducted in eight referral centers. The cohort included IR PCa patients who had ISUP 2 at biopsy. We defined biopsy tumor burden as low/high based on the absence/presence of more than 25% positive cores. Tumor burden on imaging was defined as low/high based on maximum lesion diameter, <15 mm and ≥15 mm at mpMRI, respectively. The histological endpoint of the study was adverse features at RP, defined as ≥pT3a stage and/or lymph node invasion and/or ISUP ≥3 at final pathology. The clinical endpoint was biochemical recurrence (BCR) after RP.

RESULTS

A total of 698 IR patients was included, of whom 335 (48%) had adverse features. In multivariate logistic regression analysis, there was no statistical association between tumor burden at biopsy and adverse features (p = 0.7). Tumor size ≥15 mm at mpMRI was significantly associated with adverse pathology (OR 1.65, 95%CI 1.14-2.39; p = 0.01). No significant association was observed between tumor burden at biopsy and BCR (p = 0.4). Tumor size ≥15 mm at mpMRI was significantly associated with BCR (HR 1.96, 95% CI 1.01-3.80; p = 0.04).

CONCLUSIONS

Our data support extending the inclusion criteria to ISUP 2 men with >25% positive cores, provided they have a low tumor size at mpMRI (<15 mm). Prospective studies should be performed to validate these findings.

Navigating the evolving diagnostic and therapeutic landscape of low- and intermediate-risk prostate cancer

ABSTRACT

In this nonsystematic review of the literature, we explored the changing landscape of detection and treatment of low- and intermediate-risk prostate cancer (PCa). Through emphasizing improved cancer assessment with histology classification and genomics, we investigated key developments in PCa detection and risk stratification. The pivotal role of prostate magnetic resonance imaging (MRI) in the novel diagnostic pathway is examined, alongside the benefits and drawbacks of MRI-targeted biopsies for detection and tumor characterization. We also delved into treatment options, particularly active surveillance for intermediate-risk PCa. Outcomes are compared between intermediate- and low-risk patients, offering insights into tailored management. Surgical techniques, including Retzius-sparing surgery, precision prostatectomy, and partial prostatectomy for anterior cancer, are appraised. Each technique has the potential to enhance outcomes and minimize complications. Advancements in technology and radiobiology, including computed tomography (CT)/MRI imaging and positron emission tomography (PET) fusion, allow for precise dose adjustment and daily target monitoring with imaging-guided radiotherapy, opening new ways of tailoring patients' treatments. Finally, experimental therapeutic approaches such as focal therapy open new treatment frontiers, although they create new needs in tumor identification and tracking during and after the procedure.

Prostate cancer detection and complications of MRI-targeted prostate biopsy using cognitive registration, software-assisted image fusion or in-bore guidance: a systematic review and meta-analysis of comparative studies

BACKGROUND

Three primary strategies for MRI-targeted biopsies (TB) are available: Cognitive TB (COG-TB), MRI-US Fusion TB (FUS-TB), and In Bore TB (IB-TB). Despite nearly a decade of practice, a consensus on the preferred approach is lacking, with previous studies showing comparable PCa detection rates among the three methods.

METHODS

We conducted a search of PubMed, EMBASE, PubMed, Web of Science, and Scopus databases from 2014 to 2023, to identify studies comparing at least two of the three methods and reporting clinically significant PCa (csPCa) detection rates. The primary and secondary outcomes were to compare the csPCa and insignificant prostate cancer (iPCa, ISUP GG 1) detection rates between TB techniques. The tertiary outcome was to compare the complication rate between TB techniques. Detection rates were pooled using random-effect models. Planned sensitivity analyses included subgroup analysis according to the definition of csPCa and positive MRI, previous biopsy status, biopsy route, prostate volume, and lesion characteristics.

RESULTS

A total of twenty studies, involving 4928 patients, were included in the quantitative synthesis. The meta-analysis unveiled comparable csPCa detection rates among COG-TB (0.37), FUS-TB (0.39), and IB-TB (0.47). iPCa detection rate was also similar between TB techniques (COG-TB: 0.12, FUS-TB: 0.17, IB-TB: 0.18). All preplanned sensitivity analyses were conducted and did not show any statistically significant difference in the detection of csPCa between TB methods. Complication rates, however, were infrequently reported, and when available, no statistically significant differences were observed among the techniques.

CONCLUSIONS

This unique study, exclusively focusing on comparative research, indicates no significant differences in csPCa and iPCa detection rates between COG-TB, FUS-TB, and IB-TB. Decisions between these techniques may extend beyond diagnostic accuracy, considering factors such as resource availability and operator preferences. Well-designed prospective studies are warranted to refine our understanding of the optimal approach for TB in diverse clinical scenarios.

Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer

OBJECTIVE

To develop and validate a nomogram to improve the specificity of prostate imaging reporting and data system (PI-RADS) on multiparametric magnetic resonance imaging (MRI) for clinically significant prostate cancer on targeted fusion biopsy.

METHODS

A retrospective review of patients who underwent fusion biopsy for PI-RADS 3-5 lesions using UroNav and Artemis systems between 2016 and 2022 was performed. Patients were divided into those with CS disease on fusion biopsy (Gleason grade group ≥2) versus those without. Multivariable analysis was used to identify variables associated with CS disease. A 100-point nomogram was constructed, and ROC curve was generated.

RESULTS

1485 lesions (1032 patients) were identified, 510 (34%) were PI-RADS 3, 586 (40%) were PI-RADS 4, and 389 (26%) were PI-RADS 5. Of these, 11% of PI-RADS 3, 39% of PI-RADS 4, and 61% of PI-RADS 5 showed CS disease. CS disease was associated with older age (OR 1.04, 95% CI 1.02-1.06, p < 0.01), previous negative biopsy (OR 0.52, 95% CI 0.36-0.74, p < 0.01), presence of multiple PI-RADS 3-5 lesions (OR 0.61, 95% CI 0.45-0.83, p < 0.01), peripheral zone location (OR 1.88, 95% CI 1.30-2.70, p < 0.01), PSA density (OR 1.48 per 0.1 unit, 95% CI 1.33-1.64, p < 0.01), PI-RADS score 4 (OR 3.28, 95% CI 2.21-4.87, p < 0.01), and PI-RADS score 5 (OR 7.65, 95% CI 4.93-11.85, p < 0.01). Area under ROC curve was 82% for nomogram compared to 75% for PI-RADS score alone.

CONCLUSION

We report a nomogram that combines PI-RADS score with other clinical parameters. The nomogram outperforms PI-RADS score for the detection of CS prostate cancer.

Active surveillance should not be routinely considered in ISUP grade group 2 prostate cancer

Active surveillance has been proposed as a therapeutic option in selected intermediate risk patients with biopsy grade group 2 prostate cancer. However, its oncologic safety in this setting is debated. Therefore, we conducted a non-systematic literature research of contemporary surveillance protocols including patients with grade group 2 disease to collect the most recent evidence in this setting. Although no randomized controlled trial compared curative-intent treatments, namely radical prostatectomy and radiotherapy vs. active surveillance in patients with grade group 2 disease, surgery is associated with a benefit in terms of disease control and survival when compared to expectant management in the intermediate risk setting. Patients with grade group 2 on active surveillance were at higher risk of disease progression and treatment compared to their grade group 1 counterparts. Up to 50% of those patients were eventually treated at 5 years, and the metastases-free survival rate was as low as 85% at 15-years. When considering low- and intermediate risk patients treated with radical prostatectomy, grade group 2 was one of the strongest predictors of grade upgrading and adverse features. Available data is insufficient to support the oncologic safety of active surveillance in all men with grade group 2 prostate cancer. Therefore, those patients should be counselled regarding the oncologic efficacy of upfront active treatment modalities and the lack of robust long-term data supporting the safety of active surveillance in this setting.

Biochemical Recurrence and Risk of Mortality Following Radiotherapy or Radical Prostatectomy

Importance

Stratifying patients with biochemical recurrence (BCR) after primary treatment for prostate cancer based on the risk of prostate cancer-specific mortality (PCSM) is essential for determining the need for further testing and treatments.

Objective

To evaluate the association of BCR after radical prostatectomy or radiotherapy and its current risk stratification with PCSM.

Design, Setting, and Participants

This population-based cohort study included a total of 16 311 male patients with 10 364 (64%) undergoing radical prostatectomy and 5947 (36%) undergoing radiotherapy with curative intent (cT1-3, cM0) and PSA follow-up in Stockholm, Sweden, between 2003 and 2019. Follow-up for all patients was until death, emigration, or end of the study (ie, December 31, 2018). Data were analyzed between September 2022 and March 2023.

Main Outcomes and Measures

Primary outcomes of the study were the cumulative incidence of BCR and PCSM. Patients with BCR were stratified in low- and high-risk according to European Association of Urology (EAU) criteria.

Exposures

Radical prostatectomy or radiotherapy.

Results

A total of 16 311 patients were included. Median (IQR) age was 64 (59-68) years in the radical prostatectomy cohort (10 364 patients) and 69 (64-73) years in the radiotherapy cohort (5947 patients). Median (IQR) follow-up for survivors was 88 (55-138) months and 89 (53-134) months, respectively. Following radical prostatectomy, the 15-year cumulative incidences of BCR were 16% (95% CI, 15%-18%) for the 4024 patients in the low D'Amico risk group, 30% (95% CI, 27%-32%) for the 5239 patients in the intermediate D'Amico risk group, and 46% (95% CI, 42%-51%) for 1101 patients in the high D'Amico risk group. Following radiotherapy, the 15-year cumulative incidences of BCR were 18% (95% CI, 15%-21%) for the 1230 patients in the low-risk group, 24% (95% CI, 21%-26%) for the 2355 patients in the intermediate-risk group, and 36% (95% CI, 33%-39%) for the 2362 patients in the high-risk group. The 10-year cumulative incidences of PCSM after radical prostatectomy were 4% (95% CI, 2%-6%) for the 1101 patients who developed low-risk EAU-BCR and 9% (95% CI, 5%-13%) for 649 patients who developed high-risk EAU-BCR. After radiotherapy, the 10-year PCSM cumulative incidences were 24% (95% CI, 19%-29%) for the 591 patients in the low-risk EAU-BCR category and 46% (95% CI, 40%-51%) for the 600 patients in the high-risk EAU-BCR category.

Conclusions and Relevance

These findings suggest the validity of EAU-BCR stratification system. However, while the risk of dying from prostate cancer in low-risk EAU-BCR after radical prostatectomy was very low, patients who developed low-risk EAU-BCR after radiotherapy had a nonnegligible risk of prostate cancer mortality. Improving risk stratification of patients with BCR is pivotal to guide salvage treatment decisions, reduce overtreatment, and limit the number of staging tests in the event of PSA elevations after primary treatment.

Unanswered questions in prostate cancer - findings of an international multi-stakeholder consensus by the PIONEER consortium

PIONEER is a European network of excellence for big data in prostate cancer consisting of 37 private and public stakeholders from 9 countries across Europe. Many progresses have been done in prostate cancer management, but unanswered questions in the field still exist, and big data could help to answer these questions. The PIONEER consortium conducted a two-round modified Delphi survey aiming at building consensus between two stakeholder groups - health-care professionals and patients with prostate cancer - about the most important questions in the field of prostate cancer to be answered using big data. Respondents were asked to consider what would be the effect of answering the proposed questions on improving diagnosis and treatment outcomes for patients with prostate cancer and to score these questions on a scale of 1 (not important) to 9 (critically important). The mean percentage of participants who scored each of the proposed questions as critically important was calculated across the two stakeholder groups and used to rank the questions and identify the highest scoring questions in the critically important category. The identification of questions in prostate cancer that are important to various stakeholders will help the PIONEER consortium to provide answers to these questions to improve the clinical care of patients with prostate cancer.

Intermediate-risk Prostate Cancer-A Sheep in Wolf's Clothing?

This case-based discussion describes a 65-year-old man newly diagnosed with International Society of Urological Pathology (ISUP) grade 2 prostate cancer (PCa). According to the European Association of Urology classification system, the patient harbors an intermediate-risk cancer. In step-by step discussion, we elaborate guideline-based treatment modalities for intermediate-risk PCa focused on debating active surveillance versus active treatment. Thereby, we discuss the importance of patient characteristics, including age, hereditary factors, life expectancy and comorbidity status, findings of multiparametric magnetic resonance imaging, as well as prostate-specific antigen (PSA) density and PSA kinetics, in predicting the clinical course of the disease. In addition, we focus on cribriform pathology as a predictor of adverse outcomes and critically discuss its relevance in patient management. Lastly, we outline genomic stratification in ISUP 2 cancer as a future tool to predict PCa aggressiveness. PATIENT SUMMARY: Based on current guidelines, patients with intermediate-risk prostate cancer are treated actively or can alternatively undergo an active surveillance approach when favorable risk factors are present. One major issue is to discriminate between patients who benefit from an active therapy approach and those who benefit from a deferred treatment. Therefore, reliable biomarkers and early predictors of disease progression are needed urgently.

When to order genomic tests: development and external validation of a model to predict high-risk prostate cancer at the genotypic level

PURPOSE

The aim of this study was to develop a model to predict high-genomic-risk prostate cancer (PCa) according to Decipher score, a validated 22 gene prognostic panel. By doing so, one might select the individuals who are likely to benefit from genomic testing and improve pre-op counseling about the need for adjuvant treatments.

METHODS

We retrospectively reviewed IRB-approved databases at two institutions. All patients had preoperative magnetic resonance imaging (MRI) and Decipher prostate radical prostatectomy (RP), a validated 22 gene prognostic panel. We used binary logistic regression to estimate high-risk Decipher (Decipher score > 0.60) probability on RP specimen. Area under the curve (AUC) and calibration were used to assess the accuracy of the model in the development and validation cohort. Decision curve analysis (DCA) was performed to assess the clinical benefit of the model.

RESULTS

The development and validation cohort included 622 and 185 patients with 283 (35%) and 80 (43%) of those with high-risk Decipher. The multivariable model included PSA density, biopsy Gleason Grade Group, percentage of positive cores and MRI extracapsular extension. AUC was 0.73 after leave-one-out cross-validation. DCA showed a clinical benefit in a range of probabilities between 15 and 60%. In the external validation cohort, AUC was 0.70 and calibration showed that the model underestimates the actual probability of the outcome.

CONCLUSIONS

The proposed model to predict high-risk Decipher score at RP is helpful to improve risk stratification of patients with PCa and to assess the need for additional testing and treatments.

Development and validation of a predictive model for diagnosing prostate cancer after transperineal prostate biopsy

Objective

This study aimed to develop and validate a nomogram to predict the probability of prostate cancer (PCa) after transperineal prostate biopsy by combining patient clinical information and biomarkers.

Methods

First, we retrospectively collected the clinicopathologic data from 475 patients who underwent prostate biopsy at our hospital between January 2019 to August 2021. Univariate and multivariate logistic regression analyses were used to select risk factors. Then, we established the nomogram prediction model based on the risk factors. The model performance was assessed by receiver operating characteristic (ROC) curves, calibration plots and the Hosmer–Lemeshow test. Decision curve analysis (DCA) was used to evaluate the net benefit of the model at different threshold probabilities. The model was validated in an independent cohort of 197 patients between September 2021 and June 2022.

Results

The univariate and multivariate logistic regression analyses based on the development cohort indicated that the model should include the following factors: age (OR = 1.056, p = 0.001), NEUT (OR = 0.787, p = 0.008), HPR (OR = 0.139, p &lt; 0.001), free/total (f/T) PSA (OR = 0.013, p = 0.015), and PI-RADS (OR = 3.356, p &lt; 0.001). The calibration curve revealed great agreement. The internal nomogram validation showed that the C-index was 0.851 (95% CI 0.809-0.894). Additionally, the AUC was 0.851 (95% CI 0.809-0.894), and the Hosmer–Lemeshow test result presented p = 0.143 &gt; 0.05. Finally, according to decision curve analysis, the model was clinically beneficial.

Conclusion

Herein, we provided a nomogram combining patients’ clinical data with biomarkers to help diagnose prostate cancers.

Adverse upgrading and/or upstaging in contemporary low-risk prostate cancer patients

BACKGROUND

Upgrading and/or upstaging in low-risk prostate cancer (PCa) patients may represent an indication for active treatment instead of active surveillance (AS). We addressed contemporary upgrading and/or upstaging rates in a large population based-cohort of low-risk PCa patients.

MATERIALS AND METHODS

Whitin the SEER database (2010-2015), NCCN low-risk PCa patients were identified across management modalities: radical prostatectomy (RP), radiotherapy (RT) and non-local treatment (NLT). In RP patients, upgrading and/or upstaging rates were assessed in logistic regression models.

RESULTS

Overall, of 27,901 low-risk PCa patients, 38% underwent RP vs 28% RT vs 34% NLT. RP patients were the youngest and harbored the highest percentage of positive cores and a higher rate of cT2a than NLT. At RP, 46.2% were upgraded to GGG ≥ 2, 6.0% to GGG ≥ 3 and 10.5% harbored nonorgan-confined stage (NOC, pT3-4 or pN1). Of NOC patients, 1.6% harbored GGG ≥ 3, 6.3% harbored GGG2 and 2.6% harbored GGG1. Of pT2 patients, 4.4% harbored GGG ≥ 3, 33.9% harbored GGG2 and 51.3% harbored GGG1. Age, PSA, percentage of positive cores and number of positive cores independently predicted the presence of NOC and/or GGG ≥ 3, but with low accuracy (63.9%).

CONCLUSIONS

In low-risk PCa, critical changes between tumor grade and stage at biopsy vs RP may be expected in very few patients: NOC with GGG ≥ 3 in 1.6% and NOC with GGG2 in 6.3%. Other patients with upgrading and/or upstaging combinations will invariably harbor either pT2 or GGG1 that far less critically affect PCa prognosis.

Improving the stratification of intermediate risk prostate cancer

BACKGROUND

Intermediate risk prostate cancer (IR PCa) may exhibit a wide array of phenotypes, from favorable to unfavorable. NCCN criteria help distinguishing between favorable versus unfavorable subgroups. We studied and attempted to improve this classification.

METHODS

Within the SEER database 2010-2016, we identified 19,193 IR PCa patients treated with radical prostatectomy. A multivariable logistic regression model predicting unfavorable IR PCa was developed and externally validated, in addition to a head-to-head comparison with NCCN IR PCa stratification.

RESULTS

Model development (development cohort N.=13,436: 3585 unfavorable versus 9851 favorable) rested on age, PSA, clinical T stage, biopsy Gleason Grade Group (GGG) and percentage of positive cores. All were independent predictors of unfavorable IR PCa. In external validation cohort (N.=5757: 1652 unfavorable versus 4105 favorable), NCCN stratification was 61.8% accurate in discriminating between favorable versus unfavorable, compared to 67.6% for nomogram, which exhibited excellent calibration, less pronounced departures from ideal prediction and greater net-benefit in decision curve analyses (DCA) than NCCN stratification. The optimal nomogram cutoff misclassified 312 of 1976 patients (15.8%) versus 598 of 2877 (20.8%) for NCCN stratification. Of NCCN misclassified patients, 90.0% harbored pT3-4 stages versus 84.6% of nomogram.

CONCLUSIONS

The newly developed, externally validated nomogram discriminates better between favorable versus unfavorable IR PCa, according to overall accuracy, calibration, DCA, and actual numbers and stage distribution of misclassified patients.

Expanding Active Surveillance Criteria for Low- and Intermediate-risk Prostate Cancer: Can We Accurately Predict the Risk of Misclassification for Patients Diagnosed by Multiparametric Magnetic Resonance Imaging–targeted Biopsy?

Models predicting the risk of adverse pathology (ie, International Society of Urological Pathology [ISUP] grade group ≥3, pT3, and/or pN1) among patients operated by radical prostatectomy (RP) have been proposed to expand active surveillance (AS) inclusion criteria. We aimed to test these models in a set of 1062 low-risk and favorable intermediate-risk prostate cancer (PCa) patients diagnosed by multiparametric magnetic resonance imaging (MRI) and MRI-targeted biopsy. We hypothesized that the inclusion of radiological features into a novel model would improve patient selection. Performance was assessed using discrimination, calibration, and decision curve analysis (DCA). Available models were characterized by poor discrimination (areas under the receiver operating characteristic curve [AUCs] of 59% and 60%), underestimation of predicted risk on calibration plots, and a small amount of net benefit against a probability threshold of 40-50% at the DCA. The development of a novel model slightly improved discrimination (AUC of 63% vs 59%, p = 0.001, and 63% vs 60%, p = 0.07) and net benefit against threshold probabilities of ≥30%. This first multicenter study demonstrated the poor performance of models predicting adverse pathology and that implementation of MRI and MRI-targeted biopsy in this setting was not associated with a clear improvement in patient selection. Patients harboring low-risk or favorable intermediate-risk PCa and candidates for RP cannot be referred accurately to an AS program without a non-negligible risk of misclassification. PATIENT SUMMARY: We tested prediction models that could expand the selection of prostate cancer patients for active surveillance. Models were inaccurate and associated with a high risk of misclassification despite the implementation of multiparametric magnetic resonance imaging and targeted biopsies.

Grade group 1 prostate cancer on biopsy: are we still missing aggressive disease in the era of image-directed therapy?

PURPOSE

Recently, Eggener et al. reignited a debate consisting to redefine Gleason Grade Group (GGG) 1 prostate cancer (PCa) as a precancerous lesion to reduce overdiagnosis and overtreatment. However, historical cohorts showed that some GGG1-labeled disease at biopsy may be underestimated by the standard PCa diagnostic workup. The aim was to assess whether the risk of adverse features at radical prostatectomy (RP) in selected GGG1 patients still exists in the era of pre-biopsy mpMRI and image-guided biopsies.

METHODS

We retrospectively reviewed our data from a European RP dataset to assess in contemporary patients with GGG1 at mpMRI-targeted biopsy the rate of adverse features at final pathology, defined as ≥ pT3a and/or pN+ and/or GGG ≥ 3.

RESULTS

A total of 419 patients with cT1-T2 cN0 GGG1-PCa were included. At final pathology, 143 (34.1%) patients had adverse features. In multivariate analysis, only unfavorable intermediate-risk/high-risk disease (defined on PSA or stage) was predictive of adverse features (OR 2.45, 95% CI 1.11-5.39, p = 0.02). A significant difference was observed in the 3-year biochemical recurrence-free survival between patients with and without adverse features (93.4 vs 87.8%, p = 0.026). In sensitivity analysis restricted low- and favorable intermediate-risk PCa, 122/383 patients (31.8%) had adverse features and no preoperative factors were statistically associated with this risk.

CONCLUSION

In this European study, we showed that there is still a risk of underestimating GGG1 disease at biopsy despite the routine use of image-guided biopsies. Future studies are warranted to improve the detection of aggressive disease in GGG1-labeled patients by incorporating the latest tools such as genomic testing or radiomics.

Grade and stage misclassification in intermediate unfavorable-risk prostate cancer radiotherapy candidates

BACKGROUND

We tested for upgrading (Gleason grade group [GGG] ≥ 4) and/or upstaging to non-organ-confined stage ([NOC] ≥ pT3/pN1) in intermediate unfavorable-risk (IU) prostate cancer (PCa) patients treated with radical prostatectomy, since both change the considerations for dose and/or type of radiotherapy (RT) and duration of androgen deprivation therapy (ADT).

METHODS

We relied on Surveillance, Epidemiology, and End Results (2010-2015). Proportions of (a) upgrading, (b) upstaging, or (c) upgrading and/or upstaging were tabulated and tested in multivariable logistic regression models.

RESULTS

We identified 7269 IU PCa patients. Upgrading was recorded in 479 (6.6%) and upstaging in 2398 (33.0%), for a total of 2616 (36.0%) upgraded and/or upstaged patients, who no longer fulfilled the IU grade and stage definition. Prostate-specific antigen, clinical stage, biopsy GGG, and percentage of positive cores, neither individually nor in multivariable logistic regression models, discriminated between upgraded and/or upstaged patients versus others.

CONCLUSIONS

IU PCa patients showed very high (36%) upgrading and/or upstaging proportion. Interestingly, the overwhelming majority of those were upstaged to NOC. Conversely, very few were upgraded to GGG ≥ 4. In consequence, more than one-third of IU PCa patients treated with RT may be exposed to suboptimal dose and/or type of RT and to insufficient duration of ADT, since their true grade and stage corresponded to high-risk PCa definition, instead of IU PCa. Data about magnetic resonance imaging were not available but may potentially help with better stage discrimination.

Prostate cancer biomarkers: a practical review based on different clinical scenarios

Traditionally, diagnosis and staging of prostate cancer (PCa) have been based on prostate-specific antigen (PSA) level, digital rectal examination (DRE), and transrectal ultrasound (TRUS) guided prostate biopsy. Biomarkers have been introduced into clinical practice to reduce the overdiagnosis and overtreatment of low-grade PCa and increase the success of personalized therapies for high-grade and high-stage PCa. The purpose of this review was to describe available PCa biomarkers and examine their use in clinical practice. A nonsystematic literature review was performed using PubMed and Scopus to retrieve papers related to PCa biomarkers. In addition, we manually searched websites of major urological associations for PCa guidelines to evaluate available evidence and recommendations on the role of biomarkers and their potential contribution to PCa decision-making. In addition to PSA and its derivates, thirteen blood, urine, and tissue biomarkers are mentioned in various PCa guidelines. Retrospective studies have shown their utility in three main clinical scenarios: (1) deciding whether to perform a biopsy, (2) distinguishing patients who require active treatment from those who can benefit from active surveillance, and (3) defining a subset of high-risk PCa patients who can benefit from additional therapies after RP. Several validated PCa biomarkers have become commercially available in recent years. Guidelines now recommend offering these tests in situations in which the assay result, when considered in combination with routine clinical factors, is likely to affect management. However, the lack of direct comparisons and the unproven benefits, in terms of long-term survival and cost-effectiveness, prevent these biomarkers from being integrated into routine clinical use.

Integration of magnetic resonance imaging into prostate cancer nomograms

The decision whether to undergo prostate biopsy must be carefully weighed. Nomograms have widely been utilized as risk calculators to improve the identification of prostate cancer by weighing several clinical factors. The recent inclusion of multiparametric magnetic resonance imaging (mpMRI) findings into nomograms has drastically improved their nomogram's accuracy at identifying clinically significant prostate cancer. Several novel nomograms have incorporated mpMRI to aid in the decision-making process in proceeding with a prostate biopsy in patients who are biopsy-naïve, have a prior negative biopsy, or are on active surveillance. Furthermore, novel nomograms have incorporated mpMRI to aid in treatment planning of definitive therapy. This literature review highlights how the inclusion of mpMRI into prostate cancer nomograms has improved upon their performance, potentially reduce unnecessary procedures, and enhance the individual risk assessment by improving confidence in clinical decision-making by both patients and their care providers.

PSA Density Help to Identify Patients With Elevated PSA Due to Prostate Cancer Rather Than Intraprostatic Inflammation: A Prospective Single Center Study

The association between PSA density, prostate cancer (PCa) and BPH is well established. The aim of the present study was to establish whether PSA density can be used as a reliable parameter to predict csPCa and to determine its optimal cutoff to exclude increased PSA levels due to intraprostatic inflammation. This is a large prospective single-center, observational study evaluating the role of PSA density in the discrimination between intraprostatic inflammation and clinically significant PCa (csPCa). Patients with PSA ≥ 4 ng/ml and/or positive digito-rectal examination (DRE) and scheduled for prostate biopsy were enrolled. Prostatic inflammation (PI) was assessed and graded using the Irani Scores. Multivariable binary logistic regression analysis was used to assess if PSA density was associated with clinically significant PCa (csPCa) rather than prostatic inflammation. A total of 1988 patients met the inclusion criteria. Any PCa and csPCa rates were 47% and 24% respectively. In the group without csPCa, patients with prostatic inflammation had a higher PSA (6.0 vs 5.0 ng/ml; p=0.0003), higher prostate volume (58 vs 52 cc; p<0.0001), were more likely to have a previous negative biopsy (29% vs 21%; p=0.0005) and a negative DRE (70% vs 65%; p=0.023) but no difference in PSA density (0.1 vs 0.11; p=0.2). Conversely in the group with csPCa, patients with prostatic inflammation had a higher prostate volume (43 vs 40 cc; p=0.007) but no difference in the other clinical parameters. At multivariable analysis adjusting for age, biopsy history, DRE and prostate volume, PSA density emerged as a strong predictor of csPCA but was not associated with prostatic inflammation. The optimal cutoffs of PSA density to diagnose csPCa and rule out the presence of prostatic inflammation in patients with an elevated PSA (>4 ng/ml) were 0.10 ng/ml² in biopsy naïve patients and 0.15 ng/ml² in patients with a previous negative biopsy. PSA density rather than PSA, should be used to evaluate patients at risk of prostate cancer who may need additional testing or prostate biopsy. This readily available parameter can potentially identify men who do not have PCa but have an elevated PSA secondary to benign conditions.

Reliability of Serial Prostate Magnetic Resonance Imaging to Detect Prostate Cancer Progression During Active Surveillance: A Systematic Review and Meta-analysis

CONTEXT

Although magnetic resonance imaging (MRI) is broadly implemented into active surveillance (AS) protocols, data on the reliability of serial MRI in order to help guide follow-up biopsy are inconclusive.

OBJECTIVE

To assess the diagnostic estimates of serial prostate MRI for prostate cancer (PCa) progression during AS.

EVIDENCE ACQUISITION

We systematically searched PubMed, Scopus, and Web of Science databases to select studies analyzing the association between changes on serial prostate MRI and PCa progression during AS. We included studies that provided data for MRI progression, which allowed us to calculate diagnostic estimates. We compared Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) accuracy with institution-specific definitions.

EVIDENCE SYNTHESIS

We included 15 studies with 2240 patients. Six used PRECISE criteria and nine institution-specific definitions of MRI progression. The pooled PCa progression rate, which included histological progression to Gleason grade ≥2, was 27%. The pooled sensitivity and specificity were 0.59 (95% confidence interval [CI] 0.44-0.73) and 0.75 (95% CI 0.66-0.84) respectively. There was significant heterogeneity between included studies. Depending on PCa progression prevalence, the pooled negative predictive value for serial prostate MRI ranged from 0.81 (95% CI 0.73-0.88) to 0.88 (95% CI 0.83-0.93) and the pooled positive predictive value ranged from 0.37 (95% CI 0.24-0.54) to 0.50 (95% CI 0.36-0.66). There were no significant differences in the pooled sensitivity (p = 0.37) and specificity (p = 0.74) of PRECISE and institution-specific schemes.

CONCLUSIONS

Serial MRI still should not be considered a sole factor for excluding PCa progression during AS, and changes on MRI are not accurate enough to indicate PCa progression. There was a nonsignificant trend toward improved diagnostic estimates of PRECISE recommendations. These findings highlight the need to further define the optimal triggers and timing of biopsy during AS, as well as the need for optimizing the quality, interpretation, and reporting of serial prostate MRI.

PATIENT SUMMARY

Our study suggests that serial prostate magnetic resonance imaging (MRI) alone in patients on active surveillance is not accurate enough to reliably rule out or rule in prostate cancer progression. Other clinical factors and biomarkers along with serial MRI are required to safely tailor the intensity of follow-up biopsies.