Risk Stratification of Patients Candidate to Radical Prostatectomy Based on Clinical and Multiparametric Magnetic Resonance Imaging Parameters: Development and External Validation of Novel Risk Groups

Reducing Overtreatment of Prostate Cancer Patients: Revisiting the European Association of Urology Pretreatment Risk Group Classification Using Long-term Follow-up Data from the European Randomized Study of Screening for Prostate Cancer Rotterdam

BACKGROUND AND OBJECTIVE

Tailored treatment for prostate cancer (PCa) requires accurate risk stratification. This study examines the effectiveness of the European Association of Urology (EAU) classification in predicting long-term PCa-specific mortality (PCSM) and assesses whether an alternative system can improve the identification of patients with low-risk disease.

METHODS

This study included two cohorts of patients with localized PCa: one with screen-detected PCa (n = 1563; S-cohort) and the other with clinically detected PCa (n = 755; C-cohort), all from a population-based, randomized screening study, who underwent primary radical prostatectomy or radiation monotherapy. Patients were stratified according to the traditional EAU risk classification and an alternative risk classification where low-risk disease is adjusted according to contemporary active surveillance (AS) eligibility criteria. The 15-yr time-dependent area under the curve (AUC) and the cumulative incidence of PCSM at 15 yr after diagnosis were assessed for each risk classification and cohort.

KEY FINDINGS AND LIMITATIONS

With a median follow-up of 20 yr in the S-cohort and 12 yr in the C-cohort, the EAU classification demonstrated 15-yr AUCs of 0.76 (95% confidence interval [CI]: 0.71-0.80) and 0.72 (95% CI: 0.65-0.79), respectively, for predicting PCSM. The alternative classification showed a 15-yr AUC of 0.74 (95% CI: 0.69-0.79) in the S-cohort and 0.75 (95% CI: 0.68-0.81) in the C-cohort. The alternative classification identified 45% more men having a low risk in the S-cohort and 83% more in the C-cohort than the EAU classification, with no statistically significant increase in the 15-yr PCSM incidence (S-cohort subhazard ratio: 1.33 [95% CI: 0.66-2.68]; C-cohort subhazard ratio: 0.99 [95% CI: 0.29-3.38]).

CONCLUSIONS AND CLINICAL IMPLICATIONS

The EAU classification predicts PCSM accurately, but an alternative classification, adjusted for AS eligibility, identifies substantially more men as having a low risk. This could enhance AS acceptance and utilization in clinical practice, reducing overtreatment.

PATIENT SUMMARY

This study shows that while a commonly used pretreatment risk classification for prostate cancer predict disease prognosis accurately, an alternative system based on active surveillance eligibility criteria identifies many more men as having a low risk. Adopting this classification could enhance the acceptance and use of active surveillance, reducing unnecessary treatments.

The Added Value of Prostate-specific Membrane Antigen Positron Emission Tomography/Computed Tomography to Magnetic Resonance Imaging for Local Staging of Prostate Cancer in Patients Undergoing Radical Prostatectomy

BACKGROUND AND OBJECTIVE

The role of prostate-specific membrane antigen (PSMA)-based positron emission tomography (PET)/computed tomography (CT) in addition to magnetic resonance imaging (MRI) for local staging of prostate cancer (PC) has been poorly addressed so far. Our aim was to assess the diagnostic accuracy of PSMA PET/CT and MRI, alone and combined, for detection of extraprostatic extension (EPE) and seminal vesicle invasion (SVI) in PC.

METHODS

We conducted a multicenter retrospective study evaluating patients undergoing PSMA PET/CT and MRI before radical prostatectomy. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) for detection of EPE and SVI were calculated for MRI and PSMA PET/CT alone and combined.

KEY FINDINGS AND LIMITATIONS

We included 550 patients, of whom 2%, had low-risk, 43% had intermediate-risk, and 55% had high-risk PC. Overall, 52% of patients had EPE and 21% had SVI at histopathology. Patient-based comparison of MRI versus PSMA PET/CT for detection of EPE revealed sensitivity of 60% versus 41% (p < 0.001), specificity of 77% versus 83% (p = 0.075), PPV of 75% versus 73% (p = 0.6), NPV of 64% versus 56% (p < 0.001), and AUC of 69% versus 62% (p = 0.01). Combining the modalities increased the sensitivity (73%; p < 0.001) and NPV (69%; p < 0.001) and decreased the specificity (67%; p < 0.001) and PPV (71%; p = 0.01) over MRI alone. Patient-based comparison of MRI versus PSMA PET/CT for detection of SVI revealed sensitivity of 36% versus 44% (p = 0.2), specificity of 96% versus 96% (p > 0.99), PPV of 71% versus 75% (p = 0.6), NPV of 85% versus 87% (p = 0.2), and AUC of 66% versus 70% (p = 0.2). Combining the modalities increased the sensitivity (60%; p < 0.001), NPV (90%; p < 0.001), and AUC (76%; p < 0.001) and decreased the specificity (92%; p < 0.001) over MRI alone. Limitations include the retrospective nature of the study, selection of higher-risk cases for PSMA PET/CT, and lack of central review.

CONCLUSIONS AND CLINICAL IMPLICATIONS

PSMA PET/CT has lower sensitivity for EPE detection in comparison to MRI. However, addition of PSMA PET information to MRI improved the sensitivity for EPE and SVI detection. Thus, the two modalities should be combined to guide treatment selection.

PATIENT SUMMARY

Combining MRI (magnetic resonance imaging) scans with another type of imaging called PSMA PET/CT (prostate-specific membrane antigen positron emission tomography/computed tomography) for patients with prostate cancer leads to better identification of cancer growth outside the prostate in comparison to MRI alone. This could potentially improve the choice of prostate cancer treatment.

The Role of Prostate-specific Membrane Antigen Positron Emission Tomography for Assessment of Local Recurrence and Distant Metastases in Patients with Biochemical Recurrence of Prostate Cancer After Definitive Treatment: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVE

Positron emission tomography (PET) with prostate-specific membrane antigen (PSMA) radioligands has an established role in the assessment of recurrence of prostate cancer (PC) after primary treatment. However, an updated understanding of its diagnostic utility is warranted, particularly in the context of emerging targeted and systemic treatment options for recurrent PC. Our aim was to evaluate the diagnostic performance of PSMA PET for staging and detection of local or metastatic disease in patients with biochemical recurrence (BCR) following definitive treatment for PC.

METHODS

We conducted a systematic review (Web of Science/MEDLINE, Cochrane Library, and EMBASE from inception to April 25, 2024) and meta-analysis. Eligible retrospective and prospective studies had extractable data on PSMA PET for patients with BCR after radical prostatectomy (RP) or radiation therapy (RT). Risk of bias was assessed using the QUADAS-2 tool. Random-effects models were used to evaluate PSMA PET positivity rates across clinical subgroups stratified by PSA, primary treatment, PSMA PET radioligand, and anatomic lesion sites.

KEY FINDINGS AND LIMITATIONS

A total of 43 studies (8119 patients) were included. PSMA PET positivity rates varied substantially among patients with BCR after primary definitive treatment, with significant study heterogeneity (τ2 = 0.6; p < 0.001), which was mitigated in part after stratification by PSA category. Positivity rates were significantly higher after RT (92%) than after RP (60%; p < 0.001). PSMA PET positivity by anatomic location was 23% for local recurrence, 32% for pelvic nodes, 14% for extrapelvic nodes, 16% for bone metastases, and just 1% for visceral metastases. The positivity rate increased with PSA, from 48% at PSA 0.2-0.5 ng/ml to >90% at PSA >2 ng/ml. Gleason score (GS) at RP did not significantly influence the positivity rate (50% for GS ≤7 vs 62% for GS 8-10; p = 0.08). Heterogeneity limits the generalisability of our findings.

CONCLUSIONS AND CLINICAL IMPLICATIONS

We observed substantial variability in PSMA PET positivity rates in BCR because of significant study heterogeneity, mostly related to differences in treatment type, PSA, and anatomic sites. In post-RP BCR, approximately half of patients undergoing PSMA PET had positive findings, even at low PSA (0.2-0.5 ng/ml). In the post-RT setting, PSMA PET use was generally aligned with the Phoenix criterion for BCR, with most studies performing PSMA PET at PSA ≥2 ng/ml. Further research is needed to refine PSA thresholds for PSMA PET, particularly in the post-RT setting, and to assess its role in guiding salvage treatment decisions.

Clinical Predictors and Risk Factors of Gleason Score Upgrade: A Retrospective Cohort Analysis

Background: In prostate cancer (PCa) patients, discrepancies between biopsy-assigned Gleason Scores and those determined from surgical specimens are frequently reported. This phenomenon, known as Gleason score upgrade (GSU), can have significant clinical implications. This work aims to understand the factors contributing to GSU for refining prostate cancer management strategies. Methods: Data from 779 patients diagnosed with histologically confirmed PCa who underwent robot-assisted radical prostatectomy at a single tertiary care institution between January 2005 and December 2020 were examined. Results: In the univariable setting, 5-alpha reductase inhibitor (5-ARI) use was associated with a higher percentage of upgrading (42.3% vs. 30.4% among non-users; p = 0.03942). A more advanced pathological T stage (p = 0.01114) and lymph node positivity (p < 0.00001) correlated significantly with GSU. In the logistic regression model, advanced pathological stage increased the odds more than twofold (OR = 2.807, p = 0.00135). 5-ARI use was associated with notably higher odds of upgrading (OR = 3.809, p = 0.00004). Younger age slightly increased the likelihood of GSU (OR = 0.951 per year increase in age, p = 0.01101). Conclusions: Younger age, advanced pathological stage, and the use of 5-alpha reductase inhibitors were identified as significant predictors of GSU.

The prognostic role of prostate MRI in prostate cancer patients

PURPOSE OF REVIEW

Multiparametric MRI (mpMRI) has been included in the diagnostic pathway of prostate cancer (PCa). However, the role of this imaging modality in predicting clinical outcomes after diagnosis has been poorly addressed so far. This review aims to summarize the most relevant updates on the prognostic role of mpMRI.

RECENT FINDINGS

Baseline mpMRI features help to predict adverse pathology at radical prostatectomy (RP) and grade reclassification during active surveillance. Parameters derived at prostate mpMRI such as PI-RADS score 4-5, the maximum diameter of the index lesion and the presence of extracapsular invasion/seminal vesicle invasion are among the strongest predictors of biochemical recurrence (BCR) for men treated with RP. mpMRI-based predictive models can achieve similar accuracy for BCR prediction when compared with validated models that relied on final pathology. Moreover, the use of mpMRI findings to predict disease recurrence after radiotherapy or focal therapy seems to optimize patient's risk stratification after treatment, ruling out disease recurrence.

SUMMARY

Clinicians should account for prostate mpMRI findings when predicting clinical outcomes in patients diagnosed with PCa.

Impact of Nerve-Sparing Techniques on Prostate-Specific Antigen Persistence Following Robot-Assisted Radical Prostatectomy: A Multivariable Analysis of Clinical and Pathological Predictors

Background/Objectives: Prostate-specific antigen (PSA) persistence, defined as a postoperative PSA level ≥ 0.1 ng/mL measured within 4-8 weeks after radical prostatectomy (RP), predicts biochemical recurrence (BCR) and adverse oncological outcomes. The influence of nerve-sparing (NS) surgical techniques on PSA persistence remains debated, especially among patients with high-risk pathological features. This study aimed to evaluate the impact of NS techniques on PSA persistence following robot-assisted radical prostatectomy (RARP), considering tumor characteristics, surgical parameters, and patient-specific factors. Methods: A retrospective cohort analysis was performed on 779 patients who underwent RARP at a single institution between January 2002 and December 2015. The inclusion criteria consisted of histologically confirmed prostate cancer with available preoperative and postoperative data, including PSA measurements taken 4-8 weeks after surgery. PSA persistence served as the primary outcome. Statistical analyses included descriptive statistics, univariate and multivariable logistic regression models to identify predictors of PSA persistence, and Spearman's correlation along with the Kruskal-Wallis H test to evaluate associations. Results: Of the 779 patients included, 55% underwent NS surgery (51% unilateral, 49% bilateral). The mean preoperative PSA was 11.85 ng/mL (SD: 7.63), while the mean postoperative PSA was 0.70 ng/mL (SD: 4.42). An elevated postoperative PSA was associated with a larger tumor size (r = 0.1285, p < 0.001), advanced pathological stages (χ2 = 45.10, p = 3.79 × 10-9), and higher Gleason scores (χ2 = 24.74, p = 1.57 × 10-4). NS surgery correlated with a lower postoperative PSA (mean: 0.20 ng/mL) compared to non-NS procedures (mean: 0.65 ng/mL), with slight differences between unilateral (mean: 0.30 ng/mL) and bilateral (mean: 0.35 ng/mL) NS approaches. Multivariable regression analysis identified advanced pathological stage (coefficient = 1.16, p = 0.04) as an independent predictor of PSA persistence, while NS techniques had no significant independent effect (coefficient = -0.01, p = 0.99). Conclusions: Nerve-sparing surgical techniques do not independently predict PSA persistence after RARP when adjusting for tumor-related factors and confounders. Advanced pathological stage, particularly stage pT3b, primarily determines PSA persistence. These findings highlight the necessity of personalized surgical planning informed by preoperative imaging and patient-centered decision making to optimize oncological and functional outcomes.

Accuracy of MRI in detecting seminal vesicle invasion in prostate cancer: a systematic review and meta-analysis

OBJECTIVE

To determine the diagnostic test accuracy of multiparametric magnetic resonance imaging (mpMRI) in detecting seminal vesicle invasion (SVI).

METHODS

The Medical Literature Analysis and Retrieval System Online (MEDLINE), PubMed, the Excerpta Medica dataBASE (EMBASE) and Cochrane databases were search up to May 2023. We included studies that investigated the accuracy of mpMRI in detecting SVI when compared to radical prostatectomy specimens as the reference standard. Data extraction was performed by two independent reviewers to construct 2 × 2 tables, as well as patient and study characteristics. The methodological quality of the included studies was assessed with the Quality of Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled and presented graphically with summary receiver operator characteristic (SROC) plots.

RESULTS

A total of 27 articles with 4862 patients were included for analysis. The summary sensitivity and specificity were 0.57 (95% confidence interval [CI] 0.45-0.68) and 0.95 (95% CI 0.92-0.99), respectively. Meta-regression indicated that there was no evidence that coil strength (P = 0.079), coil type (P = 0.589), year of publication (P = 0.503) or use of the Prostate Imaging-Reporting and Data System (P = 0.873) significantly influenced these results. The summary diagnostic odds ratio was 28.3 (95% CI 15.0-48.8) and the area under the curve for the SROC curve was 0.87. The I2 statistic was a modest 11.9%. In general, methodological quality was good.

CONCLUSION

The use of mpMRI in detecting SVI has excellent specificity but poor sensitivity. Both endorectal coils and magnetic field strength do not significantly impact the accuracy of MRI. These findings suggest that mpMRI cannot reliably rule out SVI in patients with prostate cancer.

Prediction of adverse pathology in prostate cancer using a multimodal deep learning approach based on [18F]PSMA-1007 PET/CT and multiparametric MRI

PURPOSE

Accurate prediction of adverse pathology (AP) in prostate cancer (PCa) patients is crucial for formulating effective treatment strategies. This study aims to develop and evaluate a multimodal deep learning model based on [18F]PSMA-1007 PET/CT and multiparametric MRI (mpMRI) to predict the presence of AP, and investigate whether the model that integrates [18F]PSMA-1007 PET/CT and mpMRI outperforms the individual PET/CT or mpMRI models in predicting AP.

METHODS

341 PCa patients who underwent radical prostatectomy (RP) with mpMRI and PET/CT scans were retrospectively analyzed. We generated deep learning signature from mpMRI and PET/CT with a multimodal deep learning model (MPC) based on convolutional neural networks and transformer, which was subsequently incorporated with clinical characteristics to construct an integrated model (MPCC). These models were compared with clinical models and single mpMRI or PET/CT models.

RESULTS

The MPCC model showed the best performance in predicting AP (AUC, 0.955 [95% CI: 0.932-0.975]), which is higher than MPC model (AUC, 0.930 [95% CI: 0.901-0.955]). The performance of the MPC model is better than that of single PET/CT (AUC, 0.813 [95% CI: 0.780-0.845]) or mpMRI (AUC, 0.865 [95% CI: 0.829-0.901]). Additionally, MPCC model is also effective in predicting single adverse pathological features.

CONCLUSION

The deep learning model that integrates mpMRI and [18F]PSMA-1007 PET/CT enhances the predictive capabilities for the presence of AP in PCa patients. This improvement aids physicians in making informed preoperative decisions, ultimately enhancing patient prognosis.

Combination of Abiraterone Acetate, Prostate Bed Radiotherapy, and Luteinizing Hormone-releasing Hormone Agonists in Biochemically Relapsing Patients After Prostatectomy (CARLHA): A Phase 2 Clinical Trial

BACKGROUND

The relevance of next-generation hormone therapies and circulating tumor cells (CTCs) are not elucidated in biochemical recurrence after prostatectomy.

OBJECTIVE

To evaluate the combination of abiraterone acetate plus prednisone (AAP), prostate bed radiotherapy (PBRT), and goserelin in biochemically relapsing men after prostatectomy, and to investigate the utility of CTCs.

DESIGN, SETTING, AND PARTICIPANTS

In this single-arm multicenter phase 2 trial, 46 biochemically relapsing men were enrolled between December 2012 and January 2019. The median follow-up was 47 mo.

INTERVENTION

All patients received AAP 1000 mg daily (but 750 mg during PBRT), salvage PBRT, and goserelin.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was 3-yr biochemical recurrence-free survival (bRFS) when prostate-specific antigen (PSA) levels were ≥0.2 ng/ml. The secondary outcomes included alternative bRFS (alt-bRFS) when PSA levels were ≥0.5 ng/ml and safety assessment. CTC count was assessed.

RESULTS AND LIMITATIONS

The 3-yr bRFS and alt-bRFS were 81.5% (95% confidence interval or CI [66.4-90.3%]) and 95.6% (95% CI [83.5-98.9%]), respectively. The most common acute radiotherapy-related adverse effect (AE; all grades was pollakiuria (41.3%). The most common late AE (all grades) was urinary incontinence (15.2%). Grade 3-4 acute or late radiotherapy-related AEs were scarce. Most frequent AEs nonrelated to radiotherapy were hot flashes (76%), hypertension (63%), and hepatic cytolysis (50%, of which 20% were of grades 3-4). Of the patients, 11% had a CTC count of ≥5, which was correlated with poorer bRFS (p = 0.042) and alt-bRFS (p = 0.008). The association between CTC count and higher rates of relapse was independent of the baseline PSA level and PSA doubling time (p = 0.42 and p = 0.09, respectively). This study was nonrandomized with a limited number of patients, and few clinical events were reported.

CONCLUSIONS

Adding AAP to salvage radiation therapy and goserelin resulted in high bRFS and alt-bRFS. AEs remained manageable, although a close liver surveillance is advised. CTC count appears as a promising biomarker for prognosis and predicting response to treatment.

PATIENT SUMMARY

Our study was a phase 2 clinical trial that exhibited the efficacy and tolerance of a novel androgen-receptor targeting agent (abiraterone acetate plus prednisone) in patients with prostate cancer who experienced rising prostate-specific antigen after radical prostatectomy, in combination with prostate bed radiotherapy. The results also indicated the feasibility and potential value of circulating tumor cell detection, which constitutes a possible advance in managing prostate cancers.

Efficacy and Predictive Factors Analysis of Androgen Deprivation Plus Novel Hormone Therapy as Neoadjuvant Treatment for High-Risk Prostate Cancer

BACKGROUND

This investigation explored the clinical features, pathological outcomes, and biochemical recurrence (BCR) duration among high-risk prostate cancer (HRPC) patients who have undergone neoadjuvant therapy (NAT) in combination with radical prostatectomy (RP) and pelvic lymph node dissection (PLND). Additionally, we identified prognostic indicators that discern pathological complete response (pCR) or minimal residual disease (MRD) and BCR.

METHODS

In total, we examined 76 HRPC patients, who received NAT with either androgen deprivation therapy (ADT) plus apalutamide or ADT plus abiraterone, with subsequent RP and PLND. We conducted a genetic evaluation of patients receiving neoadjuvant apalutamide. Additionally, patient pathological outcomes, circulating prostate-specific antigen (PSA) response rates, and BCR duration were analyzed. Lastly, we employed uni- and multivariate analyses to screen for prognostic factors that govern pCR or MRD and BCR duration.

RESULTS

Patient median age and median PSA at presentation were 69 years (IQR: 66-73), and 47.6 ng/mL (IQR: 24.1-105.75), respectively. We observed marked changes in pCR or MRD rates between the two cohorts. In particular, the ADT plus apalutamide cohort (51.5%) exhibited enhanced rates relative to the ADT plus abiraterone cohort (25.6%) (p = 0.03). The median BCR duration was substantially prolonged among neoadjuvant apalutamide cohort relative to the neoadjuvant abiraterone cohort (261 days vs. 76 days, p = 0.04). Using multivariate analysis, we revealed that the postintervention pre-RP PSA content (≤ 0.1 ng/mL vs. > 0.1 ng/mL) remained a substantial stand-alone indicator of pCR or MRD (odds ratio: 10.712, 95% CI: 2.725-42.105, p < 0.001). Furthermore, supplemental analyses revealed that the ADT plus apalutamide cohort exhibited an augmented serum response rate, which, in turn, reduced the post-intervention pre-RP PSA content. Based on our genetic profiling of the neoadjuvant apalutamide cohort demonstrated high-frequency deleterious changes in the AR axis (30.3%), followed by TP53 mutations (15.15%). Patients with defective AR axis experienced a remarkably shorter median BCR duration relative to patients with other or no genetic alterations (52.5 days vs. 286 and 336 days, respectively, p < 0.0001). Furthermore, using multivariate analysis, we demonstrated that achieving pCR or MRD (hazard ratio [HR]: 0.170, 95% CI: 0.061-0.477, p < 0.001) and presence of defective AR signaling (HR: 11.193, 95% CI: 3.499-35.806, p < 0.001) were strong stand-alone indicators of BCR.

CONCLUSIONS

Herein, we demonstrated the superior performance of ADT plus apalutamide in achieving pCR or MRD and in extending BCR duration among HRPC patients. Post-intervention pre-RP PSA content as well as genetic shifts, especially in the AR axis, are critical indicators of patient pathological and clinical outcomes. These findings highlight the significance of genetic testing and PSA content monitoring in treating HRPC patients.

Oncological outcomes after radical prostatectomy of localized prostate cancer: stratified by magnetic resonance imaging and risk classification

Background

We investigated whether combining T2-weighted magnetic resonance imaging (MRI) findings and clinical risk categories improves upon established prognostic indicators of oncological outcomes in prostate cancer.

Methods

Patients who underwent radical prostatectomy, but not preoperative hormone therapy, radiotherapy, or chemotherapy, for localized prostate cancer at Seoul National University Bundang Hospital from October 2007 to April 2016 were included. MRIs were classified according to the Prostate Imaging-Reporting and Data System (PI-RADS). Patients were divided into the following five groups: 1, no focal suspicious lesion; 2, organ-confined suspicious lesion PI-RADS ≤3; 3, organ-confined suspicious lesion PI-RADS 4 or 5; 4, suspicious lesion with extraprostatic extension (EPE), no seminal vesicle invasion (SVI); 5, suspicious lesion with EPE and SVI. Risk classified according to the National Comprehensive Cancer Network (NCCN) and MRI findings were combined to analyze survival curves for biochemical recurrence (BCR)-free and metastasis-free survival. The area under a time-dependent receiver operating characteristic was analyzed for event prediction after 5 years.

Results

We analyzed 1,290 patients. In multivariate Cox regression models, PI-RADS ≥4 (hazard ratio [HR] 2.33, P < 0.001), EPE (HR 1.46, P = 0.027), SVI (HR 5.03, P < 0.001) and NCCN high-risk (HR 2.33, 95% CI 1.66-3.26, P < 0.001) were associated with BCR. For metastasis, EPE (HR 2.33, P = 0.047), SVI (HR 13.08, P < 0.001) and NCCN high-risk (HR 2.78, P = 0.026) were independent risk factors. Depending on MRI group, BCR-free survival significantly decreased in NCCN intermediate-risk (P = 0.001) and high-risk (P < 0.001) groups, and metastasis-free survival decreased in the intermediate-risk group (P = 0.39) and significantly decreased in the high-risk (P < 0.001) group. Adding MRI group to NCCN risk classification significantly improved the predictive accuracy for BCR in comparison with NCCN risk classification alone (P = 0.042), but not for metastasis (P = 0.012).

Conclusion

Combining prostate MRI with NCCN risk classification improves the prediction value of BCR following radical prostatectomy for localized prostate cancer.

Preoperative multiparametric magnetic resonance imaging based risk stratification system for predicting biochemical recurrence after radical prostatectomy

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) is used as a current marker in preoperative staging and surgical decision-making, but current evidence on predicting post-surgical oncological outcomes based on preoperative mpMRI findings is limited. In this study We aimed to develop a risk classification based on mpMRI and mpMRI-derived biopsy findings to predict early biochemical recurrence (BCR) after radical prostatectomy.

METHODS

Between January 2017 and January 2023, the data of 289 patients who underwent mpMRI, transrectal ultrasound-guided cognitive and fusion targeted biopsies, and subsequent radical prostatectomy (RP) with or without pelvic lymph node dissection in a single center were retrospectively re-evaluated. BCR was defined as a prostate specific-antigen (PSA) ≥ 0.2 ng/mL at least twice after RP. Multivariate logistic regression models tested the predictors of BCR. The regression tree analysis stratified patients into risk groups based on preoperative mpMRI characteristics. Receiver operating characteristic (ROC)-derived area under the curve (AUC) estimates were used to test the accuracy of the regression tree-derived risk stratification tool.

RESULTS

BCR was detected in 47 patients (16.2 %) at a median follow-up of 24 months. In mpMRI based multivariate analyses, the maximum diameter of the index lesion (HR 1.081, 95%Cl 1.015-1.151, p = 0.015) the presence of PI-RADS 5 lesions (HR 2.604, 95%Cl 1.043-6.493, p = 0.04), ≥iT3a stage (HR 2.403, 95%Cl 1.013-5.714, p = 0.046) and ISUP grade ≥4 on biopsy (HR 2.440, 95%Cl 1.123-5.301, p = 0.024) were independent predictors of BCR. In regression tree analysis, patients were stratified into three risk groups: maximum diameter of index lesion, biopsy ISUP grade, and clinical stage on mpMRI. The regression tree-derived risk stratification model had moderate-good accuracy in predicting early BCR (AUC 77 %) CONCLUSION: Straightforward mpMRI and mpMRI-derived biopsy-based risk stratification for BCR prediction provide an additional clinical predictive model to the currently available pathological risk tools.

Prostate cancer risk assessment and avoidance of prostate biopsies using fully automatic deep learning in prostate MRI: comparison to PI-RADS and integration with clinical data in nomograms

OBJECTIVES

Risk calculators (RCs) improve patient selection for prostate biopsy with clinical/demographic information, recently with prostate MRI using the prostate imaging reporting and data system (PI-RADS). Fully-automated deep learning (DL) analyzes MRI data independently, and has been shown to be on par with clinical radiologists, but has yet to be incorporated into RCs. The goal of this study is to re-assess the diagnostic quality of RCs, the impact of replacing PI-RADS with DL predictions, and potential performance gains by adding DL besides PI-RADS.

MATERIAL AND METHODS

One thousand six hundred twenty-seven consecutive examinations from 2014 to 2021 were included in this retrospective single-center study, including 517 exams withheld for RC testing. Board-certified radiologists assessed PI-RADS during clinical routine, then systematic and MRI/Ultrasound-fusion biopsies provided histopathological ground truth for significant prostate cancer (sPC). nnUNet-based DL ensembles were trained on biparametric MRI predicting the presence of sPC lesions (UNet-probability) and a PI-RADS-analogous five-point scale (UNet-Likert). Previously published RCs were validated as is; with PI-RADS substituted by UNet-Likert (UNet-Likert-substituted RC); and with both UNet-probability and PI-RADS (UNet-probability-extended RC). Together with a newly fitted RC using clinical data, PI-RADS and UNet-probability, existing RCs were compared by receiver-operating characteristics, calibration, and decision-curve analysis.

RESULTS

Diagnostic performance remained stable for UNet-Likert-substituted RCs. DL contained complementary diagnostic information to PI-RADS. The newly-fitted RC spared 49% [252/517] of biopsies while maintaining the negative predictive value (94%), compared to PI-RADS ≥ 4 cut-off which spared 37% [190/517] (p < 0.001).

CONCLUSIONS

Incorporating DL as an independent diagnostic marker for RCs can improve patient stratification before biopsy, as there is complementary information in DL features and clinical PI-RADS assessment.

CLINICAL RELEVANCE STATEMENT

For patients with positive prostate screening results, a comprehensive diagnostic workup, including prostate MRI, DL analysis, and individual classification using nomograms can identify patients with minimal prostate cancer risk, as they benefit less from the more invasive biopsy procedure.

KEY POINTS

The current MRI-based nomograms result in many negative prostate biopsies. The addition of DL to nomograms with clinical data and PI-RADS improves patient stratification before biopsy. Fully automatic DL can be substituted for PI-RADS without sacrificing the quality of nomogram predictions. Prostate nomograms show cancer detection ability comparable to previous validation studies while being suitable for the addition of DL analysis.

Addressing intra- and inter-institution variability of a radiomic framework based on Apparent Diffusion Coefficient in prostate cancer

BACKGROUND

Prostate cancer (PCa) is a highly heterogeneous disease, making tailored treatment approaches challenging. Magnetic resonance imaging (MRI), notably diffusion-weighted imaging (DWI) and the derived Apparent Diffusion Coefficient (ADC) maps, plays a crucial role in PCa characterization. In this context, radiomics is a very promising approach able to disclose insights from MRI data. However, the sensitivity of radiomic features to MRI settings, encompassing DWI protocols and multicenter variations, requires the development of robust and generalizable models.

PURPOSE

To develop a comprehensive radiomics framework for noninvasive PCa characterization using ADC maps, focusing on identifying reliable imaging biomarkers against intra- and inter-institution variations.

MATERIALS AND METHODS

Two patient cohorts, including an internal cohort (118 PCa patients) used for both training (75%) and hold-out testing (25%), and an external cohort (50 PCa patients) for independent testing, were employed in the study. DWI images were acquired with three different DWI protocols on two different MRI scanners: two DWI protocols acquired on a 1.5-T scanner for the internal cohort, and one DWI protocol acquired on a 3-T scanner for the external cohort. One hundred and seven radiomics features (i.e., shape, first order, texture) were extracted from ADC maps of the whole prostate gland. To address variations in DWI protocols and multicenter variability, a dedicated pipeline, including two-way ANOVA, sequential-feature-selection (SFS), and ComBat features harmonization was implemented. Mann-Whitney U-tests (α = 0.05) were performed to find statistically significant features dividing patients with different tumor characteristics in terms of Gleason score (GS) and T-stage. Support-Vector-Machine models were then developed to predict GS and T-stage, and the performance was assessed through the area under the curve (AUC) of receiver-operating-characteristic curves.

RESULTS

Downstream of ANOVA, two subsets of 38 and 41 features stable against DWI protocol were identified for GS and T-stage, respectively. Among these, SFS revealed the most predictive features, yielding an AUC of 0.75 (GS) and 0.70 (T-stage) in the hold-out test. Employing ComBat harmonization improved the external-test performance of the GS model, raising AUC from 0.72 to 0.78.

CONCLUSION

By incorporating stable features with a harmonization procedure and validating the model on an external dataset, model robustness, and generalizability were assessed, highlighting the potential of ADC and radiomics for PCa characterization.

Optimizing risk stratification for intermediate-risk prostate cancer - the prognostic value of baseline health-related quality of life

OBJECTIVE

To investigate the prognostic value of baseline health-related quality of life (HRQOL) for patients with intermediate-risk localized prostate cancer (IR-PCa) undergoing radical prostatectomy (RP).

METHODS

4780 patients with IR-PCa according to NCCN risk stratification were identified from a prospectively maintained database. All patients were treated with RP and had prospectively assessed baseline HRQOL. Main outcomes were oncologic endpoints metastasis-free survival (MFS); biochemical recurrence free survival (BRFS) and overall survival (OS). Multivariable Cox regression models assessed prognostic significance of baseline global health status (GHS) on survival outcomes. Harrell's discrimination C-index was applied to calculate the predictive accuracy of the model. Decision curve analysis (DCA) tested the clinical net benefit associated with adding the GHS domain to our multivariable model (p < 0.05).

RESULTS

Median follow-up was 51 months. Multivariable analysis confirmed baseline GHS as an independent predictor for increased MFS (HR 0.976, 95%CI 0.96-0.99; p < 0.001), increased BRFS (HR 0.993, 95%CI 0.99-1.00; p = 0.027) and increased OS (HR 0.969, 95%CI 0.95-0.99; p = 0.002), indicating a relative risk reduction of 2.4% for MFS, 0.7% for BRFS and 3.1% for OS per 1-point increase of baseline GHS. Baseline HRQOL improved discrimination in predicting MFS, BRFS and OS. DCA revealed a net benefit over all threshold probabilities.

CONCLUSIONS

We found baseline HRQOL to substantially improve risk stratification for the heterogeneous cohort of IR-PCa. Baseline HRQOL accurately predicts increased MFS, BRFS and OS. Our findings therefore support the role of preoperative HRQOL as an adjunct to established prognosticators for IR-PCa, potentially facilitating guidance of therapy.

AI-derived Tumor Volume from Multiparametric MRI and Outcomes in Localized Prostate Cancer

Background An artificial intelligence (AI)-based method for measuring intraprostatic tumor volume based on data from MRI may provide prognostic information. Purpose To evaluate whether the total volume of intraprostatic tumor from AI-generated segmentations (VAI) provides independent prognostic information in patients with localized prostate cancer treated with radiation therapy (RT) or radical prostatectomy (RP). Materials and Methods For this retrospective, single-center study (January 2021 to August 2023), patients with cT1-3N0M0 prostate cancer who underwent MRI and were treated with RT or RP were identified. Patients who underwent RT were randomly divided into cross-validation and test RT groups. An AI segmentation algorithm was trained to delineate Prostate Imaging Reporting and Data System (PI-RADS) 3-5 lesions in the cross-validation RT group before providing segmentations for the test RT and RP groups. Cox regression models were used to evaluate the association between VAI and time to metastasis and adjusted for clinical and radiologic factors for combined RT (ie, cross-validation RT and test RT) and RP groups. Areas under the receiver operating characteristic curve (AUCs) were calculated for VAI and National Comprehensive Cancer Network (NCCN) risk categorization for prediction of 5-year metastasis (RP group) and 7-year metastasis (combined RT group). Results Overall, 732 patients were included (combined RT group, 438 patients; RP group, 294 patients). Median ages were 68 years (IQR, 62-73 years) and 61 years (IQR, 56-66 years) for the combined RT group and the RP group, respectively. VAI was associated with metastasis in the combined RT group (median follow-up, 6.9 years; adjusted hazard ratio [AHR], 1.09 per milliliter increase; 95% CI: 1.04, 1.15; P = .001) and the RP group (median follow-up, 5.5 years; AHR, 1.22; 95% CI: 1.08, 1.39; P = .001). AUCs for 7-year metastasis for the combined RT group for VAI and NCCN risk category were 0.84 (95% CI: 0.74, 0.94) and 0.74 (95% CI: 0.80, 0.98), respectively (P = .02). Five-year AUCs for the RP group for VAI and NCCN risk category were 0.89 (95% CI: 0.80, 0.98) and 0.79 (95% CI: 0.64, 0.94), respectively (P = .25). Conclusion The volume of AI-segmented lesions was an independent, prognostic factor for localized prostate cancer. © RSNA, 2024 Supplemental material is available for this article.

Development and External Validation of Nomograms for Predicting Disease-Free Survival and Overall Survival in Patients with cT1-ccRCC After Partial Nephrectomy: A Multicenter Retrospective Study

BACKGROUND

To develop a novel nomogram for predicting 2-year and 5-year disease-free survival (DFS) and overall survival (OS) in patients with cT1-clear cell renal cell carcinoma (ccRCC) undergoing partial nephrectomy (PN).

METHODS

A retrospective study was conducted across five urological centers, including 940 patients who underwent PN for cT1N0M0-ccRCC. Four centers were randomly selected to constitute the training group, while the remaining center served as the testing group. We employed the LASSO and multivariate Cox regression to develop new nomograms. The 1,000 bootstrap-corrected c-index, net reclassification improvement (NRI) and receiver operating characteristic curve were employed to compare the predictive abilities of new nomograms with the widely used UUIS and SSIGN models. Finally, the novel nomograms underwent external validation.

RESULTS

The training group included 714 patients, while the testing group consisted of 226 patients. The bootstrap-corrected c-indexes for the DFS and OS model were 0.870 and 0.902, respectively. In the training cohort, the AUC for the DFS and OS models at 2 years and 5 years were 0.953, 0.902, 0.988, and 0.911, respectively. These values were also assessed in the testing cohort. The predictive capabilities of the new nomograms surpassed those of the UUIS and SSIGN models (NRI > 0). Decision curve analysis demonstrated that the novel nomograms provide greater net benefits compared to the UUIS and SSIGN models.

CONCLUSIONS

Our novel nomograms demonstrated strong predictive ability for forecasting oncological outcomes in cT1-ccRCC patients after PN. These user-friendly nomograms are simple and convenient for clinical application, providing tangible clinical benefits.

Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

Prostate cancer (PCa) is the most common malignant tumor in men. Currently, there are few prognosis indicators for predicting PCa outcomes and guiding treatments. Here, we perform comprehensive proteomic profiling of 918 tissue specimens from 306 Chinese patients with PCa using data-independent acquisition mass spectrometry (DIA-MS). We identify over 10,000 proteins and define three molecular subtypes of PCa with significant clinical and proteomic differences. We develop a 16-protein panel that effectively predicts biochemical recurrence (BCR) for patients with PCa, which is validated in six published datasets and one additional 99-biopsy-sample cohort by targeted proteomics. Interestingly, this 16-protein panel effectively predicts BCR across different International Society of Urological Pathology (ISUP) grades and pathological stages and outperforms the D'Amico risk classification system in BCR prediction. Furthermore, double knockout of NUDT5 and SEPTIN8, two components from the 16-protein panel, significantly suppresses the PCa cells to proliferate, invade, and migrate, suggesting the combination of NUDT5 and SEPTIN8 may provide new approaches for PCa treatment.

Development and validation of [18 F]-PSMA-1007 PET-based radiomics model to predict biochemical recurrence-free survival following radical prostatectomy

PURPOSE

Biochemical recurrence (BCR) following radical prostatectomy (RP) is a significant concern for patients with prostate cancer. Reliable prediction models are needed to identify patients at risk for BCR and facilitate appropriate management. This study aimed to develop and validate a clinical-radiomics model based on preoperative [18 F]PSMA-1007 PET for predicting BCR-free survival (BRFS) in patients who underwent RP for prostate cancer.

MATERIALS AND METHODS

A total of 236 patients with histologically confirmed prostate cancer who underwent RP were retrospectively analyzed. All patients had a preoperative [18 F]PSMA-1007 PET/CT scan. Radiomics features were extracted from the primary tumor region on PET images. A radiomics signature was developed using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The performance of the radiomics signature in predicting BRFS was assessed using Harrell's concordance index (C-index). The clinical-radiomics nomogram was constructed using the radiomics signature and clinical features. The model was externally validated in an independent cohort of 98 patients.

RESULTS

The radiomics signature comprised three features and demonstrated a C-index of 0.76 (95% CI: 0.60-0.91) in the training cohort and 0.71 (95% CI: 0.63-0.79) in the validation cohort. The radiomics signature remained an independent predictor of BRFS in multivariable analysis (HR: 2.48, 95% CI: 1.47-4.17, p < 0.001). The clinical-radiomics nomogram significantly improved the prediction performance (C-index: 0.81, 95% CI: 0.66-0.95, p = 0.007) in the training cohort and (C-index: 0.78 95% CI: 0.63-0.89, p < 0.001) in the validation cohort.

CONCLUSION

We developed and validated a novel [18 F]PSMA-1007 PET-based clinical-radiomics model that can predict BRFS following RP in prostate cancer patients. This model may be useful in identifying patients with a higher risk of BCR, thus enabling personalized risk stratification and tailored management strategies.

Surgery with or Without Darolutamide in High-risk and/or Locally Advanced Prostate Cancer: The SUGAR (CCAFU-PR2) Phase 2 Trial Rationale and Protocol

BACKGROUND

High-risk prostate cancer (PCa) patients frequently experience recurrence and progression after radical prostatectomy (RP). Neoadjuvant androgen deprivation therapy (ADT) has not demonstrated a clear oncological benefit and is not currently recommended.

OBJECTIVE

The SUGAR trial is the first phase 2, randomised, controlled, multicentre, noncommercial, open-label study investigating single-agent perioperative darolutamide compared with the standard of care (ie, upfront RP, without neoadjuvant ADT).

DESIGN, SETTING, AND PARTICIPANTS

SUGAR aims to randomise 240 men affected by nonmetastatic PCa, with the major eligibility criteria being International Society of Urological Pathology grade group ≥4, seminal vesicle invasion at magnetic resonance imaging and/or clinically node-positive disease. Patients in the experimental arm will undergo neoadjuvant darolutamide monotherapy, RP, and adjuvant darolutamide, completing 9 mo of treatment.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary endpoint is noncurable recurrence-free survival, an innovative and clinically meaningful measure; the secondary endpoints encompass safety; recurrence-free, metastasis-free, and overall survival; pathological response; and quality of life. A predictive biomarker analysis will also be performed.

RESULTS AND LIMITATIONS

Initial data suggest that intensified neoadjuvant treatment with androgen receptor signalling inhibitors (ARSIs) is associated with a sustained pathological response and may improve outcomes, via tumour downstaging and micrometastasis eradication. ARSI monotherapy could further enhance tolerability.

CONCLUSIONS

SUGAR will provide efficacy and safety information on perioperative darolutamide monotherapy compared with upfront RP, in a contemporary high-risk PCa population undergoing surgery.

PATIENT SUMMARY

The on-going SUGAR clinical trial evaluates 9 mo of darolutamide treatment in addition to radical prostatectomy, in men affected by prostate cancer with specific high-risk characteristics. It investigates whether this hormonal treatment can lower the rates of noncurable recurrences, maintaining a favourable tolerability profile.

Which Patients with Prostate Cancer and Lymph Node Uptake at Preoperative Prostate-specific Membrane Antigen Positron Emission Tomography/Computerized Tomography Scan Are at a Higher Risk of Prostate-specific Antigen Persistence After Radical Prostatectomy? Identifying Indicators of Systemic Disease by Integrating Clinical, Magnetic Resonance Imaging, and Functional Imaging Parameters

BACKGROUND

The role of local therapies including radical prostatectomy (RP) in prostate cancer (PCa) patients with clinical lymphadenopathies on prostate-specific membrane antigen (PSMA) positron emission tomography/computerized tomography (PET/CT) has scarcely been explored. Limited data are available to identify men who would benefit from RP; on the contrary, those more likely to benefit already have systemic disease.

OBJECTIVE

We aimed to assess the predictors of prostate-specific antigen (PSA) persistence in surgically managed PCa patients with lymphadenopathies on a PSMA PET/CT scan by integrating clinical, magnetic resonance imaging (MRI), and PSMA PET/CT parameters.

DESIGN, SETTING, AND PARTICIPANTS

We identified 519 patients treated with RP and extended lymph node dissection, and who received preoperative PSMA PET between 2017 and 2022 in nine referral centers. Among them, we selected 88 patients with nodal uptake at preoperative PSMA PET (miTxN1M0).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The outcome was PSA persistence, defined as a PSA value of ≥0.1 ng/ml at the first measurement after surgery. Multivariable logistic regression models tested the predictors of PSA persistence. Covariates consisted of biopsy International Society of Urological Pathology (ISUP) grade group, clinical stage at MRI, and number of positive spots at a PET/CT scan. A regression tree analysis stratified patients into risk groups based on preoperative characteristics.

RESULTS AND LIMITATIONS

Overall, lymph node invasion (LNI) was detected in 63 patients (72%) and 32 (36%) experienced PSA persistence after RP. At multivariable analyses, having more than two lymph nodal positive findings at PSMA PET, seminal vesicle invasion (SVI) at MRI, and ISUP grade group >3 at biopsy were independent predictors of PSA persistence (all p < 0.05). At the regression tree analysis, patients were stratified in four risk groups according to biopsy ISUP grade, number of positive findings at PET/CT, and clinical stage at MRI. The model depicted good discrimination at internal validation (area under the curve 78%).

CONCLUSIONS

One out of three miN1M0 patients showed PSA persistence after surgery. Patients with ISUP grade 2-3, as well as patients with organ-confined disease at MRI and a single or two positive nodal findings at PET are those in whom RP may achieve the best oncological outcomes in the context of a multimodal approach. Conversely, patients with a high ISUP grade and extracapsular extension or SVI or more than two spots at PSMA PET should be considered as potentially affected by systemic disease upfront.

PATIENT SUMMARY

Our novel and straightforward risk classification integrates currently available preoperative risk tools and should, therefore, assist physician in preoperative counseling of men candidates for radical treatment for prostate cancer with positive lymph node uptake at prostate-specific membrane antigen positron emission tomography.

Proteomic-based stratification of intermediate-risk prostate cancer patients

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

MRI characteristics and oncological follow-up of patients with ISUP grade group 4 or 5 prostate cancer

OBJECTIVES

To analyze multiparametric MRI (mpMRI) characteristics of patients with International Society of Urological Pathology (ISUP) grade group (GG) 4 or 5 prostate cancer (PC) and to correlate MRI parameters with the occurrence of biochemical recurrence (BCR) after radical prostatectomy (RPE).

METHODS

In this single-center cohort study consecutive patients with mpMRI and ISUP GG 4 or 5 PC were retrospectively analyzed. Clinical, MR-guided biopsy, and diagnostic mpMRI parameter were assessed. A subcohort of patients with RPE and follow-up was analyzed separately. A univariate and multivariate analyses were performed to determine parameters that are associated to patients with BCR after RPE.

RESULTS

145 patients (mean age 70y, median PSA 10.9 ng/ml) were analyzed. 99% had a PI-RADS classification of 4 or 5, 48% revealed MRI T3 stage, and median diameter of the MRI index lesion (IL) was 15 mm. IL showed a median ADC value of 668 ×10-6 mm2/s and exhibited contrast enhancement in 94% of the cases. For patients with follow-up after RPE (n = 82; mean follow-up time 68 ± 27 m), MRI parameters were significantly different for contact length of the IL to the pseudocapsule (LCC), MRI T3 stage, and IL localization (p < 0.05). Higher PSAD and MRI T3 stage were independent parameters for the risk of BCR when incorporating clinical, biopsy, and MRI parameters.

CONCLUSION

ISUP GG 4 or 5 PC has distinctive characteristics on mpMRI and were detected on MRI in all cases. In addition, higher PSAD and MRI T3 stage were significant predictors for BCR after RPE.

Imaging tumor lactate is feasible for identifying intermediate-risk prostate cancer patients with postsurgical biochemical recurrence

While radical prostatectomy remains the mainstay of prostate cancer (PCa) treatment, 20 to 40% of patients develop postsurgical biochemical recurrence (BCR). A particularly challenging clinical cohort includes patients with intermediate-risk disease whose risk stratification would benefit from advanced approaches that complement standard-of-care diagnostic tools. Here, we show that imaging tumor lactate using hyperpolarized 13C MRI and spatial metabolomics identifies BCR-positive patients in two prospective intermediate-risk surgical cohorts. Supported by spatially resolved tissue analysis of established glycolytic biomarkers, this study provides the rationale for multicenter trials of tumor metabolic imaging as an auxiliary tool to support PCa treatment decision-making.

Managing postoperative biochemical relapse in prostate cancer, from the perspective of the Francophone group of Urological radiotherapy (GFRU)

Up to 50% of patients treated with radical surgery for localized prostate cancer may experience biochemical recurrence that requires appropriate management. Definitions of biochemical relapse may vary, but, in all cases, consist of an increase in a PSA without clinical or radiological signs of disease. Molecular imaging through to positron emission tomography has taken a preponderant place in relapse diagnosis, progressively replacing bone scan and CT-scan. Prostate bed radiotherapy is currently a key treatment, the action of which should be potentiated by androgen deprivation therapy. Nowadays perspectives consist in determining the best combination therapies, particularly thanks to next-generation hormone therapies, but not exclusively. Several trials are ongoing and should address these issues. We present here a literature review aiming to discuss the current management of biochemical relapse in prostate cancer after radical surgery, in lights of recent findings, as well as future perspectives.

Multiparametric MRI-based 5-year Risk Prediction Model for Biochemical Recurrence of Prostate Cancer after Radical Prostatectomy

Background Current predictive tools to estimate the risk of biochemical recurrence (BCR) after treatment of prostate cancer do not consider multiparametric MRI (mpMRI) information. Purpose To develop a risk prediction tool that considers mpMRI findings to assess the risk of 5-year BCR after radical prostatectomy. Materials and Methods In this retrospective single-center analysis in 1459 patients with prostate cancer who underwent mpMRI before radical prostatectomy (in 2012-2015), the outcome of interest was 5-year BCR (two consecutive prostate-specific antigen [PSA] levels > 0.2 ng/mL [0.2 µg/L]). Patients were randomly divided into training (70%) and test (30%) sets. Kaplan-Meier plots were applied to the training set to estimate survival probabilities. Multivariable Cox regression models were used to test the relationship between BCR and different sets of exploratory variables. The C-index of the final model was calculated for the training and test sets and was compared with European Association of Urology, University of California San Francisco Cancer of the Prostate Risk Assessment, Memorial Sloan-Kettering Cancer Center, and Partin risk tools using the partial likelihood ratio test. Five risk categories were created. Results The median duration of follow-up in the whole cohort was 59 months (IQR, 32-81 months); 376 of 1459 (25.8%) patients had BCR. A multivariable Cox regression model (referred to as PIPEN, and composed of PSA density, International Society of Urological Pathology grade group, Prostate Imaging Reporting and Data System category, European Society of Urogenital Radiology extraprostatic extension score, nodes) fitted to the training data yielded a C-index of 0.74, superior to that of other predictive tools (C-index 0.70 for all models; P ≤ .01) and a median higher C-index on 500 test set replications (C-index, 0.73). Five PIPEN risk categories were identified with 5-year BCR-free survival rates of 92%, 84%, 71%, 56%, and 26% in very low-, low-, intermediate-, high-, and very high-risk patients, respectively (all P < .001). Conclusion A five-item model for predicting the risk of 5-year BCR after radical prostatectomy for prostate cancer was developed and internally verified, and five risk categories were identified. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Aguirre and Ortegón in this issue.

Higher Preoperative Maximum Standardised Uptake Values (SUVmax) Are Associated with Higher Biochemical Recurrence Rates after Robot-Assisted Radical Prostatectomy for [68Ga]Ga-PSMA-11 and [18F]DCFPyL Positron Emission Tomography/Computed Tomography

This study aimed to investigate the association between the 68Ga- or 18F-radiolabeled prostate-specific membrane antigen (PSMA) tracer expression, represented by the maximum standardised uptake value (SUVmax) of the dominant intraprostatic lesion, and biochemical recurrence (BCR) in primary prostate cancer (PCa) patients prior to robot-assisted radical prostatectomy (RARP). This was a retrospective, multi-centre cohort study of 446 patients who underwent [68Ga]Ga-PSMA-11 (n = 238) or [18F]DCFPyL (n = 206) Positron Emission Tomography/Computed Tomography (PET/CT) imaging prior to RARP. SUVmax was measured in the dominant intraprostatic PCa lesions. [18F]DCFPyL patients were scanned 60 ([18F]DCFPyL-60; n = 106) or 120 ([18F]DCFPyL-120; n = 120) minutes post-injection of a radiotracer and were analysed separately. To normalise the data, SUVmax was log transformed for further analyses. During a median follow-up of 24 months, 141 (30.4%) patients experienced BCR. Log2SUVmax was a significant predictor for BCR (p < 0.001). In the multivariable analysis accounting for these preoperative variables: initial prostate-specific antigen (PSA), radiologic tumour stage (mT), the biopsy International Society of Urological Pathology grade group (bISUP) and the prostate imaging and reporting data system (PI-RADS), Log2SUVmax was found to be an independent predictor for BCR in [68Ga]Ga-PSMA-11 (HR 1.32, p = 0.04) and [18F]DCFPyL-120 PET/CT scans (HR 1.55, p = 0.04), but not in [18F]DCFPyL-60 ones (HR 0.92, p = 0.72). The PSMA expression of the dominant intraprostatic lesion proved to be an independent predictor for BCR in patients with primary PCa who underwent [68Ga]Ga-PSMA-11 or [18F]DCFPyL-120 PET/CT scans, but not in those who underwent [18F]DCFPyL-60 PET/CT scans.

Risk stratification for early biochemical recurrence of prostate cancer in the era of multiparametric magnetic resonance imagining-targeted biopsy

BACKGROUND

Multiparametric magnetic resonance imaging (MRI) and MRI-targeted biopsy are nowadays recommended in the prostate cancer (PCa) diagnostic pathway. Ploussard and Mazzone have integrated these tools into novel risk classification systems predicting the risk of early biochemical recurrence (eBCR) in PCa patients who underwent radical prostatectomy (RP). We aimed to assess available risk classification systems and to define the best-performing.

METHODS

Data on 1371 patients diagnosed by MRI-targeted biopsy and treated by RP between 2014 and 2022 at eight European tertiary referral centers were analyzed. Risk classifications systems included were the European Association of Urology (EAU) and National Comprehensive Cancer Network (NCCN) risk groups, the Cancer of the Prostate Risk Assessment (CAPRA) score, the International Staging Collaboration for Cancer of the Prostate (STAR-CAP) classification, the Ploussard and Mazzone models, and ISUP grade group. Kaplan-Meier analyses were used to compare eBCR among risk classification systems. Performance was assessed in terms of discrimination quantified using Harrell's c-index, calibration, and decision curve analysis (DCA).

RESULTS

Overall, 152 (11%) patients had eBCR at a median follow-up of 31 months (interquartile range: 19-45). The 3-year eBCR-free survival rate was 91% (95% confidence interval [CI]: 89-93). For each risk classification system, a significant difference among survival probabilities was observed (log-rank test p < 0.05) except for NCCN classification (p = 0.06). The highest discrimination was obtained with the STAR-CAP classification (c-index 66%) compared to CAPRA score (63% vs. 66%, p = 0.2), ISUP grade group (62% vs. 66, p = 0.07), Ploussard (61% vs. 66%, p = 0.003) and Mazzone models (59% vs. 66%, p = 0.02), and EAU (57% vs. 66%, p < 0.001) and NCCN (57% vs. 66%, p < 0.001) risk groups. Risk classification systems demonstrated good calibration characteristics. At DCA, the CAPRA score showed the highest net benefit at a probability threshold of 9%-15%.

CONCLUSIONS

The performance of risk classification systems using MRI and MRI-targeted information was less optimistic when tested in a contemporary set of patients. CAPRA score and STAR-CAP classification were the best-performing and should be preferred for treatment decision-making.

Prognostic significance of PI-RADS 5 lesions in patients treated by radical prostatectomy

PURPOSE

To analyse the pathological features and survival of patients with a PI-RADS 5 lesion on pre-biopsy MRI.

METHODS

We extracted from a European multicentre prospectively gathered database the data of patients with a PI-RADS 5 lesion on pre-biopsy MRI, diagnosed using both systematic and targeted biopsies and subsequently treated by radical prostatectomy. The Kaplan-Meier model was used to assess the biochemical-free survival of the whole cohort and univariable and multivariable Cox models were set up to study factors associated with survival.

RESULTS

Between 2013 and 2019, 539 consecutive patients with a PI-RADS 5 lesion on pre-biopsy MRI were treated by radical prostatectomy and included in the analysis. Follow-up data were available for 448 patients. Radical prostatectomy and lymph node dissection specimens showed non-organ confined disease in 297/539 (55%), (including 2 patients with a locally staged pT2 lesion and lymph node involvement (LNI)). With a median follow-up of 25 months (12-39), the median biochemical recurrence-free survival was 54% at 2 years (95% CI 45-61) and 28% at 5 years (95% CI 18-39). Among the factors studied, MRI T stage [T3a vs T2 HR 3.57 (95%CI 1.78-7.16); T3b vs T2 HR 6.17 (95% CI 2.99-12.72)] and PSA density (HR 4.47 95% CI 1.55-12.89) were significantly associated with a higher risk of biochemical recurrence in multivariable analysis.

CONCLUSION

Patients with a PI-RADS 5 lesion on pre-biopsy MRI have a high risk of early biochemical recurrence after radical prostatectomy. MRI T stage and PSA density can be used to improve patient selection and counselling.

Expanding inclusion criteria for active surveillance in intermediate-risk prostate cancer: a machine learning approach

PURPOSE

To develop new selection criteria for active surveillance (AS) in intermediate-risk (IR) prostate cancer (PCa) patients.

METHODS

Retrospective study including patients from 14 referral centers who underwent pre-biopsy mpMRI, image-guided biopsies and radical prostatectomy. The cohort included biopsy-naive IR PCa patients who met the following inclusion criteria: Gleason Grade Group (GGG) 1-2, PSA < 20 ng/mL, and cT1-cT2 tumors. We relied on a recursive machine learning partitioning algorithm developed to predict adverse pathological features (i.e., ≥ pT3a and/or pN + and/or GGG ≥ 3).

RESULTS

A total of 594 patients with IR PCa were included, of whom 220 (37%) had adverse features. PI-RADS score (weight:0.726), PSA density (weight:0.158), and clinical T stage (weight:0.116) were selected as the most informative risk factors to classify patients according to their risk of adverse features, leading to the creation of five risk clusters. The adverse feature rates for cluster #1 (PI-RADS ≤ 3 and PSA density < 0.15), cluster #2 (PI-RADS 4 and PSA density < 0.15), cluster #3 (PI-RADS 1-4 and PSA density ≥ 0.15), cluster #4 (normal DRE and PI-RADS 5), and cluster #5 (abnormal DRE and PI-RADS 5) were 11.8, 27.9, 37.3, 42.7, and 65.1%, respectively. Compared with the current inclusion criteria, extending the AS criteria to clusters #1 + #2 or #1 + #2 + #3 would increase the number of eligible patients (+ 60 and + 253%, respectively) without increasing the risk of adverse pathological features.

CONCLUSIONS

The newly developed model has the potential to expand the number of patients eligible for AS without compromising oncologic outcomes. Prospective validation is warranted.

Urinary Continence Recovery after Robotic Radical Prostatectomy without Anterior or Posterior Reconstruction: Experience from a Tertiary Referral Center

BACKGROUND

The aim of our study is to evaluate the prevalence and predictive factors of short- (30 d) and mid-term continence in a contemporary cohort of patients treated with robotic-assisted laparoscopic prostatectomy (RALP) without any posterior or anterior reconstruction at our referral academic center.

METHODS

Data from patients undergoing RALP between January 2017 and March 2021 were prospectively collected. RALP was performed by three highly experienced surgeons following the principles of the Montsouris technique, with a bladder-neck-sparing intent and maximal preservation of the membranous urethra (if oncologically safe) without any anterior/posterior reconstruction. (Self-assessed urinary incontinence (UI) was defined as the need of one or more pads per die (excluding the need for a safety pad/die. Univariable and multivariable logistic regression analysis was used to assess the independent predictors of early incontinence among routinely collected patient- and tumor-related variables).

RESULTS

A total of 925 patients were included; of these, 353 underwent RALP (38.2%) without nerve-sparing intent. The median patient age and BMI were 68 years (IQR 63-72) and 26 (IQR 24.0-28.0), respectively. Overall, 159 patients (17.2%) reported early (30 d) incontinence. In multivariable analysis adjusting for patient- and tumor-related features, a non-nerve-sparing procedure (OR: 1.57 [95% CI: 1.03-2.59], p = 0.035) was independently associated with the risk of urinary incontinence in the short-term period, while the absence of cardiovascular diseases before surgery (OR: 0.46 [95% CI: 0.320.67], p ≤ 0.01) was a protective factor for this outcome. At a median follow-up of 17 months (IQR 10-24), 94.5% of patients reported to be continent.

CONCLUSIONS

In experienced hands, most patients fully recover urinary continence after RALP at mid-term follow-up. On the contrary, the proportion of patients who reported early incontinence in our series was modest but not negligible. The implementation of surgical techniques advocating anterior and/or posterior fascial reconstruction might improve the early continence rate in candidates for RALP.

The impact of local staging of prostate cancer determined on MRI or DRE at time of radical prostatectomy on progression-free survival: A Will Rogers phenomenon

INTRODUCTION

We aimed to test whether the current practice of using mpMRI stage might lead to a Will Rogers phenomenon with a stage migration compared to DRE in men undergoing radical prostatectomy.

MATERIAL AND METHODS

A total of 572 consecutive patients who underwent radical prostatectomy at a single institution (2007-2017) were included. Clinical stage using digital rectal examination was determined on table by the operating surgeon; mpMRI and pathological stage were recorded after tumor board review. Progression-free survival (PFS) was defined as no rising PSA, no adjuvant/salvage treatment, and no metastases or mortality. PFS was compared between groups and a model incorporating mpMRI into the EAU risk groups was created.

RESULTS

Median age was 63 years (IQR 58.5-67) and median PSA was 8.9 ng/ml (IQR 6.5-13.2). Using DRE stage, 20% were NCCN low risk, 43% were intermediate, and 37% high. Median follow-up was 48 months (IQR 22-73). Estimated PFS at 1, 3, and 5 years was 75%, 59%, and 54%, respectively. When comparing PFS between DRE and mpMRI stages, patients deemed T1 (P < 0.01) or T3 (P = 0.03) by mpMRI showed better outcomes than patients staged T1 or T3 by DRE. On univariable analysis lower risk for failure was seen for MRI T1 disease (HR 0.10 95%, CI 0.01-0.73, P = 0.02) or MRI T3 (HR 0.70, CI 0.51-0.97, P = 0.03). On multivariable analysis, only MRI T1 remained a significant predictor (HR 0.08, 95% CI 0.01-0.59, P = 0.01). The subsequent, modified EAU risk model using both DRE and mpMRI performed significantly better than the DRE model.

CONCLUSION

PFS based on mpMRI is not the same as DRE staging. Current risk groups which use DRE should be used with caution in whom local stage is based on mpMRI. Our modified EAU-risk categories can provide greater accuracy.

Magnetic Resonance Imaging–based T-staging to Predict Biochemical Recurrence after Radical Prostatectomy: A Step Towards the iTNM Classification

BACKGROUND

Local staging of prostate cancer (PCa) still relies on digital rectal examination (DRE), which therefore remains the standard for risk stratification in guideline recommendations, clinical trials, and patient counseling. This issue is increasingly controversial as multiparametric magnetic resonance imaging (mpMRI) has become the most influential diagnostic tool for local staging of PCa over the past two decades.

OBJECTIVE

To compare various models of T category based on DRE or mpMRI to predict early biochemical recurrence (BCR) after radical prostatectomy (RP).

DESIGN, SETTING, AND PARTICIPANTS

A retrospective multicenter cohort study was conducted between 2014 and 2021. A total of 1436 patients were recruited across eight referral centers in France, Italy, Switzerland, and Belgium.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

BCR was defined as two prostate-specific antigen values of ≥0.2 ng/ml during follow-up. Harrell's concordance index (C index) was used to compare the discrimination of four models of T staging based on DRE (model 1: cT1 vs cT2 vs cT3) or mpMRI (model 2: organ-confined disease vs extracapsular extension [iECE] vs seminal vesicle invasion [iSVI]; model 3: Prostate Imaging-Reporting and Data System [PI-RADS] ≤3 vs PI-RADS 4 vs PI-RADS 5; and model 4: iT2a [PI-RADS ≤3] vs iT2b [PI-RADS 4] vs iT2c [PI-RADS 5 excluding ECE or SVI] vs iT3a [ECE] vs iT3b [SVI]) to predict BCR.

RESULTS AND LIMITATIONS

Overall, 74 (5%), 845 (59%), 482 (34%), and 35 (2%) patients had low-, intermediate-, high-, and very high-risk PCa, respectively, according to the Mazzone risk classification. After median follow-up of 16 mo, 113 patients experienced BCR. Although the new five-group mpMRI-based T classification system (model 4) had the highest prognostic discrimination (C index 0.694) for predicting early BCR on multivariable analysis, there was overlap between the 95% confidence intervals of the models. On sensitivity analysis, the new mpMRI-based T staging still had a higher C index than DRE for predicting BCR when excluding cN1 patients and comparing it with a five-group DRE-based T classification (cT1c vs cT2a vs cT2b vs cT2c vs cT3), but the overlap between the 95% confidence intervals of the models remained. The main limitation is the short follow-up.

CONCLUSIONS

We described an alternative mpMRI-based T staging for prediction of early BCR after RP for PCa. Our results need to be validated externally before they can be applied in clinical practice.

PATIENT SUMMARY

At present, digital rectal examination of the prostate is used to stage prostate cancer. We developed an alternative model for staging that uses information from magnetic resonance imaging (MRI) scans to predict cancer outcomes for men undergoing surgical removal of the prostate.

Identification and validation of a poor clinical outcome subtype of primary prostate cancer with Midkine abundance

Recent studies identified Midkine (MDK) as playing a key role in immune regulation. In this study, we aimed to discover the clinical significance and translational relevance in prostate cancer (PCa). We retrospectively analyzed 759 PCa patients who underwent radical prostatectomy from Huashan Hospital, Fudan University (training cohort, n = 369) and Chinese Prostate Cancer Consortium (validation cohort, n = 390). A total of 325 PCa patients from The Cancer Genome Atlas (TCGA) database (external cohort) were analyzed for exploration. Immune landscape and antitumor immunity were assessed through immunohistochemistry and flow cytometry. Patient‐derived explant culture system was applied for evaluating the targeting potential of MDK. We found that intratumoral MDK expression correlated with PCa progression, which indicated an unfavorable biochemical recurrence (BCR)‐free survival for postoperative PCa patients. Addition of MDK expression to the postoperative risk assessment tool CAPRA‐S could improve its prognostic value. Tumors with MDK abundance characterized the tumor‐infiltrating CD8⁺ T cells with less cytotoxicity production and increased immune checkpoint expression, which were accompanied by enriched immunosuppressive contexture. Moreover, MDK inhibition could reactivate CD8⁺ T cell antitumor immunity. MDK mRNA expression negatively correlated with androgen receptor activity signature and positively associated with radiotherapy‐related signature. In conclusion, intratumoral MDK expression could serve as an independent prognosticator for BCR in postoperative PCa patients. MDK expression impaired the antitumor function of CD8⁺ T cells through orchestrating an immunoevasive microenvironment, which could be reversed by MDK inhibition. Moreover, tumors with MDK enrichment possessed potential sensitivity to postoperative radiotherapy while resistance to adjuvant hormonal therapy of PCa. MDK could be considered as a potential therapeutic target for PCa.

Risk Estimation of Metastatic Recurrence After Prostatectomy: A Model Using Preoperative Magnetic Resonance Imaging and Targeted Biopsy

Background

The risk of prostate cancer metastatic is correlated with its volume and grade. These parameters are now best estimated preoperatively with magnetic resonance imaging (MRI) and MRI-guided biopsy.

Objective

To estimate the risk of metastatic recurrence after radical prostatectomy (RP) in our model versus conventional clinical European Association of Urology (EAU) classification. The secondary objective is biochemical recurrence (BCR).

Design, setting, and participants

A retrospective study was conducted of a cohort of 713 patients having undergone MRI-guided biopsies and RP between 2009 and 2018. The preoperative variables included prostate-specific antigen, cT stage, tumor volume (TV) based on the lesion’s largest diameter at MRI, percentage of Gleason pattern 4/5 (%GP4/5) at MRI-guided biopsy, and volume of GP4/5 (VolGP4/5) calculated as TV × %GP4/5.

Outcome measurements and statistical analysis

The variables’ ability to predict recurrence was determined in univariable and multivariable Fine-and-Gray models, according to the Akaike information criterion (AIC) and Harrell’s C-index.

Results and limitations

Overall, 176 (25%), 430 (60%), and 107 (15%) patients had low, intermediate, and high-risk disease, respectively, according to the EAU classification. During a median follow-up period of 57 mo, metastatic recurrence was observed in 48 patients with a 5-yr probability of 5.6% (95% confidence interval [CI] 3.9–7.7). VolGP4/5 (categories: <0.5, 0.5–1.0, 1.01–3.2, and >3.2 ml) was the parameter with the lowest AIC and the highest C-index for metastatic recurrence of 0.82 (95% CI 0.76–0.88), and for BCR it was 0.73 (95% CI 0.68–0.78). In a multivariable model that included %GP4/5 and TV, C-index values were 0.86 (95% CI 0.79–0.91) for metastatic recurrence and 0.77 (0.72–0.82) for BCR. The same results for EAU classification were 0.74 (0.67–0.80) and 0.67 (0.63–0.72), respectively. Limitations are related to short follow-up and expertise of radiologists and urologists.

Conclusions

We developed a preoperative risk tool integrating the VolGP4/5 based on MRI and MRI-guided biopsies to predict metastatic recurrence after RP. Our model showed higher accuracy than conventional clinical risk models. These findings might enable physicians to provide more personalized patient care.

Patient summary

Aggressiveness of prostate cancer evaluated before treatment by incorporating magnetic resonance imaging (MRI) and MRI-guided biopsy results gives a better estimate of the risk of metastatic recurrence than previous parameters not based on MRI.

Overexpression of CDCA8 Predicts Poor Prognosis and Promotes Tumor Cell Growth in Prostate Cancer

Human cell division cycle-related protein 8 (CDCA8) is an essential component of the vertebrate chromosomal passenger complex (CPC). CDCA8 was confirmed to play a role in promoting malignant tumor progression. However, the exact function of CDCA8 in the development and progression of prostate cancer (PCa) remains unclear. In this study, the database GSE69223 was downloaded by the gene expression omnibus (GEO) database, as well as CDCA8 expression differences in multiple tumor tissues and normal tissues were detected by The Cancer Genome Atlas (TCGA), TIMER, Oncomine, and Ualcan databases. Kaplan-Meier and Cox regression methods were used to analyze the correlation between CDCA8 expression and prognosis in PCa. We confirmed the expression of CDCA8 in PCa tissues by HPA. We also analyzed the association of CDCA8 expression with PCa clinical characteristics in the TCGA database. To further understand the role of CDCA8 in PCa, we assessed the effects of CDCA8 on PCa cell growth, proliferation, and migration in vitro studies. As a result, CDCA8 was significantly overexpressed in PCa cells compared with normal prostate cells. High CDCA8 expression predicts poor prognosis in PCa patients, and CDCA8 expression was higher in high-grade PCa. In addition, silencing of CDCA8 significantly inhibited PCa cell proliferation and migration. In summary, CDCA8 promoted the proliferation and migration of PCa cells.

High Keratin-7 Expression in Benign Peri-Tumoral Prostatic Glands Is Predictive of Bone Metastasis Onset and Prostate Cancer-Specific Mortality

BACKGROUND

New predictive biomarkers are needed to accurately predict metastasis-free survival (MFS) and cancer-specific survival (CSS) in localized prostate cancer (PC). Keratin-7 (KRT7) overexpression has been associated with poor prognosis in several cancers and is described as a novel prostate progenitor marker in the mouse prostate.

METHODS

KRT7 expression was evaluated in prostatic cell lines and in human tissue by immunohistochemistry (IHC, on advanced PC, n = 91) and immunofluorescence (IF, on localized PC, n = 285). The KRT7 mean fluorescence intensity (MFI) was quantified in different compartments by digital analysis and correlated to clinical endpoints in the localized PC cohort.

RESULTS

KRT7 is expressed in prostatic cell lines and found in the basal and supra-basal compartment from healthy prostatic glands and benign peri-tumoral glands from localized PC. The KRT7 staining is lost in luminal cells from localized tumors and found as an aberrant sporadic staining (2.2%) in advanced PC. In the localized PC cohort, high KRT7 MFI above the 80th percentile in the basal compartment was significantly and independently correlated with MFS and CSS, and with hypertrophic basal cell phenotype.

CONCLUSION

High KRT7 expression in benign glands is an independent biomarker of MFS and CSS, and its expression is lost in tumoral cells. These results require further validation on larger cohorts.

Primary tumour PSMA intensity is an independent prognostic biomarker for biochemical recurrence-free survival following radical prostatectomy

Purpose

The prognostic value of PSMA intensity on PSMA PET/CT due to underlying biology and subsequent clinical implications is an emerging topic of interest. We sought to investigate whether primary tumour PSMA PET intensity contributes to pre- and post-operative prediction of oncological outcomes following radical prostatectomy.

Methods

We performed a retrospective cohort study of 848 men who underwent all of multiparametric MRI (mpMRI), transperineal prostate biopsy, and ⁶⁸ Ga-PSMA PET/CT prior to radical prostatectomy. PSMA intensity, quantified as maximum standard uptake value (SUVmax), and other clinical variables were considered relative to post-operative biochemical recurrence-free survival (BRFS) using Cox regression and Kaplan–Meier analysis.

Results

After a median follow-up of 41 months, 219 events occurred; the estimated 3-year BRFS was 79% and the 5-year BRFS was 70%. Increasing PSMA intensity was associated with less favourable BRFS overall (Log rank p < 0.001), and within subgroups of Gleason score category (Log rank p < 0.03). PSMA intensity was significantly associated with shorter time to biochemical recurrence, after adjusting for pre-operative (HR per 5-unit SUVmax increase = 1.15) and post-operative (HR per 5-unit SUVmax increase = 1.10) parameters.

Conclusion

These results in a large series of patients confirm PSMA intensity to be a novel, independent prognostic factor for BRFS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05756-2.

Improving the Early Detection of Clinically Significant Prostate Cancer in Men in the Challenging Prostate Imaging-Reporting and Data System 3 Category

BACKGROUND

Prostate Imaging-Reporting and Data System (PI-RADS) category 3 is a challenging scenario for detection of clinically significant prostate cancer (csPCa) and some tools can improve the selection of appropriate candidates for prostate biopsy.

OBJECTIVE

To assess the performance of the European Randomized Study of Screening for Prostate Cancer (ERSPC) magnetic resonance imaging (MRI) model, the new Proclarix test, and prostate-specific antigen density (PSAD) in selecting candidates for prostate biopsy among men in the PI-RADS 3 category.

DESIGN SETTING AND PARTICIPANTS

We conducted a head-to-head prospective analysis of 567 men suspected of having PCa for whom guided and systematic biopsies were scheduled between January 2018 and March 2020 in a single academic institution. A PI-RADS v.2 category 3 lesion was identified in 169 men (29.8%).

OUTCOME MEASUREMENT AND STATISTICAL ANALYSIS

csPCa, insignificant PCa (iPCa), and unnecessary biopsy rates were analysed. csPCa was defined as grade group ≥2. Receiver operating characteristic (ROC) curves, decision curve analysis curves, and clinical utility curves were plotted.

RESULTS AND LIMITATIONS

PCa was detected in 53/169 men (31.4%) with a PI-RADS 3 lesion, identified as csPCa in 25 (14.8%) and iPCa in 28 (16.6%). The area under the ROC curve for csPCa detection was 0.703 (95% confidence interval [CI] 0.621-0.768) for Proclarix, 0.657 (95% CI 0.547-0.766) for the ERSPC MRI model, and 0.612 (95% CI 0.497-0.727) for PSAD (p = 0.027). The threshold with the highest sensitivity was 10% for Proclarix, 1.5% for the ERSPC MRI model, and 0.07 ng/ml/cm3 for PSAD, which yielded sensitivity of 100%, 91%, and 84%, respectively. Some 21.3%, 26.2%, and 7.1% of biopsies would be avoided with Proclarix, PSAD, and the ERSPC MRI model, respectively. Proclarix showed a net benefit over PSAD and the ERSPC MRI model. Both Proclarix and PSAD reduced iPCa overdetection from 16.6% to 11.3%, while the ERSPC MRI model reduced iPCa overdetection to 15.4%.

CONCLUSIONS

Proclarix was more accurate in selecting appropriate candidates for prostate biopsy among men in the PI-RADS 3 category when compared to PSAD and the ERSPC MRI model. Proclarix detected 100% of csPCa cases and would reduce prostate biopsies by 21.3% and iPCa overdetection by 5.3%.

PATIENT SUMMARY

We compared three methods and found that the Proclarix test can optimise the detection of clinically significant prostate cancer in men with a score of 3 on the Prostate Imaging-Reporting and Data System for magnetic resonance imaging scans.

Active surveillance for intermediate-risk prostate cancer

INTRODUCTION

Active surveillance (AS) is an established approach in the management of low-risk, localized prostate cancer. While the use of AS to manage intermediate-risk (IR) disease has gradually increased over time, there remains uncertainty with regards to its safety, with only a minority of IR patients currently being managed with this approach.

MATERIALS AND METHODS

We conducted a narrative review based on an analysis of the literature focusing on articles describing AS for IR prostate cancer. We focus on the uncertainty surrounding AS in IR disease by discussing variations in the definitions and guideline recommendations associated with IR disease, and describing the limitations of the evidence from observational studies and randomized trials.

CONCLUSION

The safety of AS for IR disease remains unknown, given the lack of randomized trials and the limitations of the current observational studies. Further research is needed to identify select patients with IR prostate cancer that can be managed safely with AS.

Radiomics in prostate cancer: an up-to-date review

Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.