Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.

BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale. METHODS: In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5-10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4-6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341. FINDINGS: Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87-0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83-0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6-63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3-92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3-72·4] vs 69·0% [65·5-72·5]) at the same sensitivity (96·1%, 94·0-98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (-0·04) was greater than the non-inferiority margin (-0·05) and a p value below the significance threshold was reached (p<0·001). INTERPRETATION: An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system. FUNDING: Health~Holland and EU Horizon 2020.

Acoustic Enrichment of Heterogeneous Circulating Tumor Cells and Clusters from Metastatic Prostate Cancer Patients.

BACKGROUND: There are important unmet clinical needs to develop cell enrichment technologies to enable unbiased label-free isolation of both single cell and clusters of circulating tumor cells (CTCs) manifesting heterogeneous lineage specificity. Here, we report a pilot study based on the microfluidic acoustophoresis enrichment of CTCs using the CellSearch CTC assay as a reference modality. METHODS: Acoustophoresis uses an ultrasonic standing wave field to separate cells based on biomechanical properties (size, density, and compressibility), resulting in inherently label-free and epitope-independent cell enrichment. Following red blood cell lysis and paraformaldehyde fixation, 6 mL of whole blood from 12 patients with metastatic prostate cancer and 20 healthy controls were processed with acoustophoresis and subsequent image cytometry. RESULTS: Acoustophoresis enabled enrichment and characterization of phenotypic CTCs (EpCAM+, Cytokeratin+, DAPI+, CD45-/CD66b-) in all patients with metastatic prostate cancer and detected CTC-clusters composed of only CTCs or heterogeneous aggregates of CTCs clustered with various types of white blood cells in 9 out of 12 patients. By contrast, CellSearch did not detect any CTC clusters, but detected comparable numbers of phenotypic CTCs as acoustophoresis, with trends of finding a higher number of CTCs using acoustophoresis. CONCLUSION: Our preliminary data indicate that acoustophoresis provides excellent possibilities to detect and characterize CTC clusters as a putative marker of metastatic disease and outcomes. Moreover, acoustophoresis enables the sensitive label-free enrichment of cells with epithelial phenotypes in blood and offers opportunities to detect and characterize CTCs undergoing epithelial-to-mesenchymal transitioning and lineage plasticity.

Investigating Ras homolog gene family member C (RhoC) and Ki67 expression following external beam radiation therapy show increased RhoC expression in relapsing prostate cancer xenografts.

Ras homolog gene family member C (RhoC) is a GTPase involved in cell migration, implicated in epithelial-mesenchymal transition and treatment resistance and metastasis of cancer. For example, RhoC has been shown to be involved in resistance to radiation in cervical carcinoma. Here, the effect of X-ray irradiation on RhoC expression in prostate cancer (PCa) xenografts was investigated in both xenografts in regression and relapse. Male BALB/cAnNRj-Foxn1nu/nu mice were inoculated with 4-6 million LNCaP-FGC cells and established xenografts were irradiated with X-rays (200 kV, 1 Gymin-1), 5, 10 or 15 Gy using a Gulmay Medical X-ray system. Expression of RhoC and Ki67, a known proliferation marker, was investigated in xenografts, given 15 Gy, 7 days (midst response as measured by size) or 3 weeks (relapse) post irradiation. Staining was quantified using the Halo software (v2.3.2089.34) with the Indica Labs - cytonuclear v1.6 algorithm. RhoC and Ki67 staining was divided into weak, medium, and strong staining and the percentage of cells stained, single and dual staining, was quantified. The HALO software was further used to classify the tissue in each section so that analysis of RhoC and Ki67 expression in cancer cells, stroma and necrotic areas could be done separately. The results showed that RhoC expression in cancer and stroma cells was significantly higher in relapsed xenografts than in those in regression. This was not seen for Ki67 staining, where the percentage of stained cells were the same in regressing and relapsing tumors. RhoC could be a useful biomarker to confirm relapse following external beam radiation therapy.

A pilot study of an organised population-based testing programme for prostate cancer.

OBJECTIVE: To determine the feasibility of a digitally automated population-based programme for organised prostate cancer testing (OPT) in Southern Sweden. PATIENTS AND METHODS: A pilot project for a regional OPT was conducted between September 2020 and February 2021, inviting 999 randomly selected men aged 50, 56, or 62 years. Risk stratification was based on prostate-specific antigen (PSA) level, PSA density (PSAD), and bi-parametric prostate magnetic resonance imaging (MRI). Men with a PSA level of 3-99 ng/mL had an MRI, and men with elevated PSA level (≥3 ng/mL) had a urological check-up, including a digital rectal examination and transrectal ultrasonography (TRUS). Indications for targeted and/or systematic transrectal prostate biopsies were suspicious lesions on MRI (Prostate Imaging-Reporting and Data System [PI-RADS] 4-5) and/or PSAD > 0.15 ng/mL/mL. Additional indications for prostate biopsies were palpable tumours, PSA ratio < 0.1, or cancer suspicion on TRUS. Patient selection, mail correspondence, data collection, and algorithm processing were performed by an automated digital management system. Feasibility is reported descriptively. RESULTS: A total of 418 men had a PSA test (42%), with increasing participation rates by age (50 years, 38%; 56 years, 44%; and 62 years, 45%). Among these, 35 men (8%) had elevated PSA levels (≥3 ng/mL: one of 139, aged 50 years; 10/143, aged 56 years; and 24/146, aged 62 years). On MRI, 16 men (48%) had a negative scan (PI-RADS < 3), seven men (21%) had PI-RADS 3, nine men (27%) had PI-RADS 4, and one man (3%) had PI-RADS 5. All men with PI-RADS 4 or 5 underwent prostate biopsies, as well as two men with PI-RADS 3 due to PSAD > 0.15 ng/mL/mL or a suspicious finding on TRUS. Prostate cancer was diagnosed in 10 men. Six men underwent active treatment, whereas four men were assigned to active surveillance. CONCLUSION: Our OPT model is feasible from an operational point of view, but due to the limited scale of this study no conclusions can be made regarding the efficacy of the diagnostic model or outcome.

Artificial intelligence for detection of prostate cancer in biopsies during active surveillance.

OBJECTIVES: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active surveillance (AS). PATIENTS AND METHODS: A total of 180 patients in the Prostate Cancer Research International Active Surveillance (PRIAS) cohort were prospectively monitored using pre-defined criteria. Diagnostic and re-biopsy slides from 2011 to 2020 (n = 4744) were scanned and analysed by an in-house AI-based cancer detection algorithm. The algorithm was analysed for sensitivity, specificity, and for accuracy to predict need for active treatment. Prognostic properties of cancer size, prostate-specific antigen (PSA) level and PSA density at diagnosis were evaluated. RESULTS: The sensitivity and specificity of the AI algorithm was 0.96 and 0.73, respectively, for correct detection of cancer areas. Original pathology report diagnosis was used as the reference method. The area of cancer estimated by the pathologists correlated highly with the AI detected cancer size (r = 0.83). By using the AI algorithm, 63% of the slides would not need to be read by a pathologist as they were classed as benign, at the risk of missing 0.55% slides containing cancer. Biopsy cancer content and PSA density at diagnosis were found to be prognostic of whether the patient stayed on AS or was discontinued for active treatment. CONCLUSION: The AI-based biopsy cancer detection algorithm could be used to reduce the pathologists' workload in an AS cohort. The detected cancer amount correlated well with the cancer length measured by the pathologist and the algorithm performed well in finding even small areas of cancer. To our knowledge, this is the first report on an AI-based algorithm in digital pathology used to detect cancer in a cohort of patients on AS.

Targeted Investigational Treatment Analysis of Novel Anti-androgen (TITAN) study: ultralow prostate-specific antigen decline with apalutamide plus androgen-deprivation therapy.

OBJECTIVE: To assess the association between achievement of prostate-specific antigen (PSA) levels ≤0.2 ng/mL (henceforth 'ultralow') and clinical outcomes in patients in the 'Targeted Investigational Treatment Analysis of Novel Anti-androgen' (TITAN) study (ClinicalTrials.gov Identifier NCT02489318) with metastatic castration-sensitive prostate cancer (mCSPC). PATIENTS AND METHODS: Patients in the TITAN study with mCSPC were randomised to 240 mg/day apalutamide (n = 525) or placebo (n = 527) plus androgen-deprivation therapy. This post hoc analysis assessed the achievement of a PSA level of 0.2->0.02 ng/mL ('ultralow one' [UL1]) and ≤0.02 ng/mL ('ultralow two' [UL2]) vs >0.2 ng/mL with apalutamide treatment and its association with radiographic progression-free survival (rPFS), overall survival (OS), time to castration-resistant PC (TTCRPC), and time to PSA progression (TTPP). The landmark analysis and Kaplan-Meier methods were used. RESULTS: By 3 months, more patients achieved UL1 and UL2 with apalutamide (38% and 23%) vs placebo (15% and 5%). In the apalutamide-treated patients, UL2 vs PSA >0.2 ng/mL at landmark 3 months was associated with significantly longer rPFS (hazard ratio [HR] 0.28, 95% confidence interval [CI] 0.14-0.54), OS (HR 0.24, 95% CI 0.13-0.43), TTCRPC (HR 0.2, 95% CI 0.11-0.38), and TTPP (HR 0.11, 95% CI 0.04-0.27; nominal P values all <0.001); this association was also observed but less pronounced for UL1. Similar findings were observed at 6 months. Early onset of decline to UL2 by 3 months was associated with improved survival vs PSA >0.2 ng/mL anytime (HR 0.12, 95% CI 0.06-0.22; P < 0.001) in apalutamide-treated patients. CONCLUSIONS: In this post hoc analysis of TITAN, patients with the deepest PSA decline derived the greatest benefit. These results extend our findings of apalutamide efficacy in the overall TITAN population, underscoring the clinical value of PSA kinetics as a marker for treatment efficacy. PATIENT SUMMARY: Patients with metastatic prostate cancer that is sensitive to ongoing hormonal treatment benefited significantly from the addition of apalutamide compared with placebo. Those who achieved rapid and deep PSA reduction had the greatest survival benefit.

Prostate-specific antigen (PSA) decline with apalutamide therapy is associated with longer survival and improved outcomes in individuals with metastatic prostate cancer: a plain language summary of the TITAN study.

WHAT IS THIS SUMMARY ABOUT?: This summary describes the results from an additional (or post hoc) analysis of the TITAN study. The TITAN study looked at whether the prostate cancer treatment apalutamide could be used to treat individuals with metastatic castration-sensitive prostate cancer (or mCSPC). A total of 1052 participants with mCSPC were included in the TITAN study. Treatment with apalutamide was compared with treatment with placebo. All participants received androgen deprivation therapy (or ADT), which is a type of hormone therapy that has been part of the main treatment for mCSPC for many years. The results showed that apalutamide plus ADT increased the length of time that participants remained alive compared with placebo plus ADT. Apalutamide plus ADT also controlled the growth of the cancer for a longer length of time compared with placebo plus ADT. Additionally, participants who received apalutamide plus ADT experienced a greater reduction in the blood levels of prostate-specific antigen (or PSA), called a deep PSA decline, compared with those who received placebo plus ADT. An additional (or post hoc) analysis was carried out to understand whether a decrease in blood PSA levels, in response to treatment, was associated with improved outcomes, including longer survival time. WHAT WERE THE RESULTS OF THE ADDITIONAL ANALYSIS?: In participants who received apalutamide plus ADT, a deep PSA decline in response to treatment was associated with longer survival time and improved outcomes. WHAT DO THESE RESULTS MEAN FOR INDIVIDUALS WITH MCSPC?: These results demonstrate that individuals with mCSPC can benefit from treatment with apalutamide plus ADT. The association seen between deep PSA decline and the longer survival time and improved outcomes highlights how PSA measurements can be used to help monitor cancer disease evolution in response to treatment. Monitoring PSA levels will assist doctors and other healthcare professionals to understand how effectively a treatment is working for a patient and to tailor their treatment approach to improve PSA decline.

Quantification of microRNA editing using two-tailed RT-qPCR for improved biomarker discovery.

Even though microRNAs have been viewed as promising biomarkers for years, their clinical implementation is still lagging far behind. This is in part due to the lack of RT-qPCR technologies that can differentiate between microRNA isoforms. For example, A-to-I editing of microRNAs through adenosine deaminase acting on RNA (ADAR) enzymes can affect their expression levels and functional roles, but editing isoform-specific assays are not commercially available. Here, we describe RT-qPCR assays that are specific for editing isoforms, using microRNA-379 (miR-379) as a model. The assays are based on two-tailed RT-qPCR, and we show them to be compatible both with SYBR Green and hydrolysis-based chemistries, as well as with both qPCR and digital PCR. The assays could readily detect different miR-379 editing isoforms in various human tissues as well as changes of editing levels in ADAR-overexpressing cell lines. We found that the miR-379 editing frequency was higher in prostate cancer samples compared to benign prostatic hyperplasia samples. Furthermore, decreased expression of unedited miR-379, but not edited miR-379, was associated with treatment resistance, metastasis, and shorter overall survival. Taken together, this study presents the first RT-qPCR assays that were demonstrated to distinguish A-to-I-edited microRNAs, and shows that they can be useful in the identification of biomarkers that previously have been masked by other isoforms.

Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index.

PURPOSE: Consistent assessment of bone metastases is crucial for patient management and clinical trials in prostate cancer (PCa). We aimed to develop a fully automated convolutional neural network (CNN)-based model for calculating PET/CT skeletal tumor burden in patients with PCa. METHODS: A total of 168 patients from three centers were divided into training, validation, and test groups. Manual annotations of skeletal lesions in [18F]fluoride PET/CT scans were used to train a CNN. The AI model was evaluated in 26 patients and compared to segmentations by physicians and to a SUV 15 threshold. PET index representing the percentage of skeletal volume taken up by lesions was estimated. RESULTS: There was no case in which all readers agreed on prevalence of lesions that the AI model failed to detect. PET index by the AI model correlated moderately strong to physician PET index (mean r = 0.69). Threshold PET index correlated fairly with physician PET index (mean r = 0.49). The sensitivity for lesion detection was 65-76% for AI, 68-91% for physicians, and 44-51% for threshold depending on which physician was considered reference. CONCLUSION: It was possible to develop an AI-based model for automated assessment of PET/CT skeletal tumor burden. The model's performance was superior to using a threshold and provides fully automated calculation of whole-body skeletal tumor burden. It could be further developed to apply to different radiotracers. Objective scan evaluation is a first step toward developing a PET/CT imaging biomarker for PCa skeletal metastases.

Comparison of outcomes of different biopsy schedules among men on active surveillance for prostate cancer: An analysis of the G.A.P.3 global consortium database.

BACKGROUND: The optimal interval for repeat biopsy during active surveillance (AS) for prostate cancer is yet to be defined. This study examined whether risk of upgrading (to grade group ≥ 2) or risk of converting to treatment varied according to intensity of repeat biopsy using data from the GAP3 consortium's global AS database. MATERIALS AND METHODS: Intensity of surveillance biopsy schedules was categorized according to centers' protocols: (a) Prostate Cancer Research International Active Surveillance project (PRIAS) protocols with biopsies at years 1, 4, and 7 (10 centers; 7532 men); (b) biennial biopsies, that is, every other year (8 centers; 4365 men); and (c) annual biopsy schedules (4 centers; 1602 men). Multivariable Cox regression was used to compare outcomes according to biopsy intensity. RESULTS: Out of the 13,508 eligible participants, 56% were managed according to PRIAS protocols (biopsies at years 1, 4, and 7), 32% via biennial biopsy, and 12% via annual biopsy. After adjusting for baseline characteristics, risk of converting to treatment was greater for those on annual compared with PRIAS biopsy schedules (hazard ratio [HR] = 1.66; 95% confidence interval [CI] = 1.51-1.83; p < 0.001), while risk of upgrading did not differ (HR = 0.96; 95% CI = 0.84-1.10). CONCLUSION: Results suggest more frequent biopsy schedules may deter some men from continuing AS despite no evidence of grade progression.

Apalutamide for Metastatic, Castration-Sensitive Prostate Cancer.

BACKGROUND: Apalutamide is an inhibitor of the ligand-binding domain of the androgen receptor. Whether the addition of apalutamide to androgen-deprivation therapy (ADT) would prolong radiographic progression-free survival and overall survival as compared with placebo plus ADT among patients with metastatic, castration-sensitive prostate cancer has not been determined. METHODS: In this double-blind, phase 3 trial, we randomly assigned patients with metastatic, castration-sensitive prostate cancer to receive apalutamide (240 mg per day) or placebo, added to ADT. Previous treatment for localized disease and previous docetaxel therapy were allowed. The primary end points were radiographic progression-free survival and overall survival. RESULTS: A total of 525 patients were assigned to receive apalutamide plus ADT and 527 to receive placebo plus ADT. The median age was 68 years. A total of 16.4% of the patients had undergone prostatectomy or received radiotherapy for localized disease, and 10.7% had received previous docetaxel therapy; 62.7% had high-volume disease, and 37.3% had low-volume disease. At the first interim analysis, with a median of 22.7 months of follow-up, the percentage of patients with radiographic progression-free survival at 24 months was 68.2% in the apalutamide group and 47.5% in the placebo group (hazard ratio for radiographic progression or death, 0.48; 95% confidence interval [CI], 0.39 to 0.60; P<0.001). Overall survival at 24 months was also greater with apalutamide than with placebo (82.4% in the apalutamide group vs. 73.5% in the placebo group; hazard ratio for death, 0.67; 95% CI, 0.51 to 0.89; P = 0.005). The frequency of grade 3 or 4 adverse events was 42.2% in the apalutamide group and 40.8% in the placebo group; rash was more common in the apalutamide group. CONCLUSIONS: In this trial involving patients with metastatic, castration-sensitive prostate cancer, overall survival and radiographic progression-free survival were significantly longer with the addition of apalutamide to ADT than with placebo plus ADT, and the side-effect profile did not differ substantially between the two groups. (Funded by Janssen Research and Development; TITAN ClinicalTrials.gov number, NCT02489318.).

Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians.

PURPOSE: The aim of this study was to develop and validate an artificial intelligence (AI)-based method using convolutional neural networks (CNNs) for the detection of pelvic lymph node metastases in scans obtained using [18F]PSMA-1007 positron emission tomography-computed tomography (PET-CT) from patients with high-risk prostate cancer. The second goal was to make the AI-based method available to other researchers. METHODS: [18F]PSMA PET-CT scans were collected from 211 patients. Suspected pelvic lymph node metastases were marked by three independent readers. A CNN was developed and trained on a training and validation group of 161 of the patients. The performance of the AI method and the inter-observer agreement between the three readers were assessed in a separate test group of 50 patients. RESULTS: The sensitivity of the AI method for detecting pelvic lymph node metastases was 82%, and the corresponding sensitivity for the human readers was 77% on average. The average number of false positives was 1.8 per patient. A total of 5-17 false negative lesions in the whole cohort were found, depending on which reader was used as a reference. The method is available for researchers at www.recomia.org . CONCLUSION: This study shows that AI can obtain a sensitivity on par with that of physicians with a reasonable number of false positives. The difficulty in achieving high inter-observer sensitivity emphasizes the need for automated methods. On the road to qualifying AI tools for clinical use, independent validation is critical and allows performance to be assessed in studies from different hospitals. Therefore, we have made our AI tool freely available to other researchers.

Analytical performance of aPROMISE: automated anatomic contextualization, detection, and quantification of [18F]DCFPyL (PSMA) imaging for standardized reporting.

PURPOSE: The application of automated image analyses could improve and facilitate standardization and consistency of quantification in [18F]DCFPyL (PSMA) PET/CT scans. In the current study, we analytically validated aPROMISE, a software as a medical device that segments organs in low-dose CT images with deep learning, and subsequently detects and quantifies potential pathological lesions in PSMA PET/CT. METHODS: To evaluate the deep learning algorithm, the automated segmentations of the low-dose CT component of PSMA PET/CT scans from 20 patients were compared to manual segmentations. Dice scores were used to quantify the similarities between the automated and manual segmentations. Next, the automated quantification of tracer uptake in the reference organs and detection and pre-segmentation of potential lesions were evaluated in 339 patients with prostate cancer, who were all enrolled in the phase II/III OSPREY study. Three nuclear medicine physicians performed the retrospective independent reads of OSPREY images with aPROMISE. Quantitative consistency was assessed by the pairwise Pearson correlations and standard deviation between the readers and aPROMISE. The sensitivity of detection and pre-segmentation of potential lesions was evaluated by determining the percent of manually selected abnormal lesions that were automatically detected by aPROMISE. RESULTS: The Dice scores for bone segmentations ranged from 0.88 to 0.95. The Dice scores of the PSMA PET/CT reference organs, thoracic aorta and liver, were 0.89 and 0.97, respectively. Dice scores of other visceral organs, including prostate, were observed to be above 0.79. The Pearson correlation for blood pool reference was higher between any manual reader and aPROMISE, than between any pair of manual readers. The standard deviations of reference organ uptake across all patients as determined by aPROMISE (SD = 0.21 blood pool and SD = 1.16 liver) were lower compared to those of the manual readers. Finally, the sensitivity of aPROMISE detection and pre-segmentation was 91.5% for regional lymph nodes, 90.6% for all lymph nodes, and 86.7% for bone in metastatic patients. CONCLUSION: In this analytical study, we demonstrated the segmentation accuracy of the deep learning algorithm, the consistency in quantitative assessment across multiple readers, and the high sensitivity in detecting potential lesions. The study provides a foundational framework for clinical evaluation of aPROMISE in standardized reporting of PSMA PET/CT.

Inhibition of STAT3 augments antitumor efficacy of anti-CTLA-4 treatment against prostate cancer.

There is an urgent need for new treatment options in metastatic drug-resistant prostate cancer. Combining immunotherapy with other targeted therapies may be an effective strategy for advanced prostate cancer. In the present study, we sought to investigate to enhance the efficacy of anti-CTLA-4 therapy against prostate cancer by the combination with STAT3 inhibition.Male C57BL6 mice were subcutaneously inoculated with the murine prostate cancer cell line RM-1. Tumor progression was monitored following treatment with vehicle, the small molecule STAT3 inhibitor GPB730, anti-CTLA-4 or GPB730 + anti-CTLA-4. Treatment with anti-CTLA-4 or anti-CTLA-4 + GPB730 significantly inhibited tumor growth and enhanced survival compared to vehicle. Combining anti-CTLA-4 treatment with GPB730 resulted in a significantly prolonged survival compared to anti-CTLA-4 alone. GPB730 significantly increased infiltration of CD45 + cells in tumors of anti-CTLA-4-treated mice compared to anti-CTLA-4 alone. The levels of tumor-infiltrating Tregs were significantly decreased and the CD8:Treg ratio significantly increased by GPB730 treatment in combination with anti-CTLA-4 compared to anti-CTLA-4 alone. Immunohistochemical analysis showed a significant increase in CD45-positive cells in anti-CTLA-4 and anti-CTLA-4 + GPB730-treated tumors compared to vehicle or GPB730 monotherapy. Plasma levels of IL10 were significantly increased by anti-CTLA-4 compared to vehicle but no increase was observed when combining anti-CTLA-4 with GPB730.In conclusion, STAT3 inhibition by GPB730 enhances the antitumoral activity of anti-CTLA-4 and decreases the intratumoral Treg frequency in a prostate cancer mouse model. These results support the combination of STAT3 inhibition with anti-CTLA-4 therapy to increase clinical responses in patients with prostate cancer.

A European Registry Evaluating Symptomatic Effectiveness of Pharmacologically Treated Patients with Lower Urinary Tract Symptoms due to Benign Prostatic Enlargement: Lessons Learned.

PURPOSE: We evaluated unmet needs of lower urinary tract symptoms-benign prostatic enlargement pharmacological treatment by measuring symptom improvement, persistence and deterioration in real life. A prospective registry was conducted for 24 months in 5 European countries and analyzed by the European Association of Urology Research Foundation. MATERIALS AND METHODS: Previously untreated and treated patients were enrolled to the registry in both primary care and urology referral centers in France, Germany, Italy, Spain and the UK. RESULTS: Overall, 2,175 patients were enrolled with 1,838 analyzed, consisting of 575 previously untreated lower urinary tract symptoms-benign prostatic enlargement patients (no alpha blockers for at least 1 month or no 5-alpha reductase inhibitors for at least 6 months) and 1,263 previously treated patients. During the registry 90% of patients adhered to the prescribed regimen. After 24 months, 70% of previously untreated and 42% of previously treated patients experienced symptom improvement (International Prostate Symptom Score [IPSS] reduction of ≥3 points). Symptomatic patients (IPSS ≥8) remained in both groups (59% in previously untreated and 61% in previously treated), with greater symptom deterioration (IPSS increase ≥3 points) in 18.9% in previously treated vs 7.8% in previously untreated patients. Both clinical lower urinary tract symptoms-benign prostatic enlargement progression and surgery rates were similar in untreated vs treated groups at 16% vs 17% and 5% vs 7%, respectively, at 24 months. CONCLUSIONS: This prospective registry confirmed lower urinary tract symptoms-benign prostatic enlargement pharmacological treatment effectiveness in a real-world setting, with low clinical progression observed in about 1 in 6 patients and lower surgery rates below 1 in 20, by 24 months.

Apalutamide plus Androgen Deprivation Therapy for Metastatic Castration-Sensitive Prostate Cancer: Analysis of Pain and Fatigue in the Phase 3 TITAN Study.

PURPOSE: We performed an exploratory analysis of prostate cancer-related pain and fatigue on health-related quality of life in patients with metastatic castration-sensitive prostate cancer receiving apalutamide (240 mg/day) or placebo, with continuous androgen deprivation therapy (ADT), in the phase 3, randomized, double-blind, placebo controlled TITAN trial (NCT02489318). MATERIALS AND METHODS: Patient-reported outcomes for pain and fatigue were evaluated using the Brief Pain Inventory-Short Form and Brief Fatigue Inventory. Time to deterioration (TTD) was estimated by Kaplan-Meier method; hazard ratios and 95% confidence intervals were calculated using Cox proportional hazards model. General estimating equations for logistic regression estimated treatment-related differences in the likelihood of worsening pain or fatigue. RESULTS: Compliance for completing the Brief Pain Inventory-Short Form and Brief Fatigue Inventory was high (96% to 97%) in the first year. Median followup times were similar between treatments (19 to 22 months). Median pain TTD was longer with apalutamide than placebo for "pain at its least in the last 24 hours" (28.7 vs 21.8 months, respectively; p=0.0146), "pain interfered with mood" (not estimable vs 22.4 months; p=0.0017), "pain interfered with walking ability" (28.7 vs 20.2 months; p=0.0027), "pain interfered with relations" (not estimable vs 23.0 months; p=0.0139) and "pain interfered with sleep" (28.7 vs 20.9 months; p=0.0167). Likelihood for fatigue and worsening fatigue were similar between groups. CONCLUSIONS: Patients with metastatic castration-sensitive prostate cancer receiving apalutamide plus ADT vs placebo plus ADT reported consistently favorable TTD of pain. No difference for change in fatigue was observed with apalutamide vs placebo.

Consensus statements on PSMA PET/CT response assessment criteria in prostate cancer.

PURPOSE: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET)/computed tomography (CT) is used for (re)staging prostate cancer (PCa) and as a biomarker for evaluating response to therapy, but lacks established response criteria. A panel of PCa experts in nuclear medicine, radiology, and/or urology met on February 21, 2020, in Amsterdam, The Netherlands, to formulate criteria for PSMA PET/CT-based response in patients treated for metastatic PCa and optimal timing to use it. METHODS: Panelists received thematic topics and relevant literature prior to the meeting. Statements on how to interpret response and progression on therapy in PCa with PSMA PET/CT and when to use it were developed. Panelists voted anonymously on a nine-point scale, ranging from strongly disagree (1) to strongly agree (9). Median scores described agreement and consensus. RESULTS: PSMA PET/CT consensus statements concerned utility, best timing for performing, criteria for evaluation of response, patients who could benefit, and handling of radiolabeled PSMA PET tracers. Consensus was reached on all statements. PSMA PET/CT can be used before and after any local and systemic treatment in patients with metastatic disease to evaluate response to treatment. Ideally, PSMA PET/CT imaging criteria should categorize patients as responders, patients with stable disease, partial response, and complete response, or as non-responders. Specific clinical scenarios such as oligometastatic or polymetastatic disease deserve special consideration. CONCLUSIONS: Adoption of PSMA PET/CT should be supported by indication for appropriate use and precise criteria for interpretation. PSMA PET/CT criteria should categorize patients as responders or non-responders. Specific clinical scenarios deserve special consideration.

Personalised biopsy schedules based on risk of Gleason upgrading for patients with low-risk prostate cancer on active surveillance.

OBJECTIVE: To develop a model and methodology for predicting the risk of Gleason upgrading in patients with prostate cancer on active surveillance (AS) and using the predicted risks to create risk-based personalised biopsy schedules as an alternative to one-size-fits-all schedules (e.g. annually). Furthermore, to assist patients and doctors in making shared decisions on biopsy schedules, by providing them quantitative estimates of the burden and benefit of opting for personalised vs any other schedule in AS. Lastly, to externally validate our model and implement it along with personalised schedules in a ready to use web-application. PATIENTS AND METHODS: Repeat prostate-specific antigen (PSA) measurements, timing and results of previous biopsies, and age at baseline from the world's largest AS study, Prostate Cancer Research International Active Surveillance (PRIAS; 7813 patients, 1134 experienced upgrading). We fitted a Bayesian joint model for time-to-event and longitudinal data to this dataset. We then validated our model externally in the largest six AS cohorts of the Movember Foundation's third Global Action Plan (GAP3) database (>20 000 patients, 27 centres worldwide). Using the model predicted upgrading risks; we scheduled biopsies whenever a patient's upgrading risk was above a certain threshold. To assist patients/doctors in the choice of this threshold, and to compare the resulting personalised schedule with currently practiced schedules, along with the timing and the total number of biopsies (burden) planned, for each schedule we provided them with the time delay expected in detecting upgrading (shorter is better). RESULTS: The cause-specific cumulative upgrading risk at the 5-year follow-up was 35% in PRIAS, and at most 50% in the GAP3 cohorts. In the PRIAS-based model, PSA velocity was a stronger predictor of upgrading (hazard ratio [HR] 2.47, 95% confidence interval [CI] 1.93-2.99) than the PSA level (HR 0.99, 95% CI 0.89-1.11). Our model had a moderate area under the receiver operating characteristic curve (0.6-0.7) in the validation cohorts. The prediction error was moderate (0.1-0.2) in theGAP3 cohorts where the impact of the PSA level and velocity on upgrading risk was similar to PRIAS, but large (0.2-0.3) otherwise. Our model required re-calibration of baseline upgrading risk in the validation cohorts. We implemented the validated models and the methodology for personalised schedules in a web-application (http://tiny.cc/biopsy). CONCLUSIONS: We successfully developed and validated a model for predicting upgrading risk, and providing risk-based personalised biopsy decisions in AS of prostate cancer. Personalised prostate biopsies are a novel alternative to fixed one-size-fits-all schedules, which may help to reduce unnecessary prostate biopsies, while maintaining cancer control. The model and schedules made available via a web-application enable shared decision-making on biopsy schedules by comparing fixed and personalised schedules on total biopsies and expected time delay in detecting upgrading.

Surgeon heterogeneity significantly affects functional and oncological outcomes after radical prostatectomy in the Swedish LAPPRO trial.

OBJECTIVES: To evaluate how surgeon heterogeneity - the variation in outcomes between individual surgeons - influences functional and oncological outcomes after robot-assisted laparoscopic prostatectomy (RALP) and retropubic radical prostatectomy (RRP), and to assess whether surgeon heterogeneity affects the comparison between RALP and RRP. PATIENTS AND METHODS: Laparoscopic Prostatectomy Robot Open (LAPPRO) is a prospective, controlled, non-randomized trial performed at 14 Swedish centres with 68 operating surgeons. A total of 4003 men with localized prostate cancer were enrolled between 2008 and 2011. The endpoints were urinary incontinence, erectile dysfunction (ED) and recurrence at 24 months after surgery. Logistic regression models were built to evaluate surgeon heterogeneity and, secondarily, surgeon-specific factors were added to the models to investigate their influence on heterogeneity and the comparison between RALP and RRP. RESULTS: Among surgeons who performed at least 20 surgeries during the study period (n=25), we observed statistically significant heterogeneity for incontinence (P = 0.001), ED (P < 0.001) and rate of recurrent disease (P < 0.001). The significant heterogeneity remained when analysing only experienced surgeons with a stated experience of at least 250 radical prostatectomies (n=12). Among all participating surgeons (n=68), differences in surgeon volume explained 42% of the observed heterogeneity for incontinence (P = 0.003), 11% for ED (P = 0.03) and 19% for recurrence (P = 0.01). Taking surgeon volume into account when comparing RALP and RRP had a significant impact on the results. The effect was greatest for functional outcomes, and the additional adjustments for the surgeons' previous experience changed whether the difference between techniques was statistically significant or not. The surgeons' annual volume had the greatest effect on the recurrence rate. CONCLUSIONS: There was a large degree of heterogeneity among surgeons regarding both functional and oncological outcomes and this had a significant impact on the results when comparing RALP and RRP. Some of the observed heterogeneity was explained by differences in surgeon volume. Efforts to decrease heterogeneity are warranted and variation among surgeons must be accounted for when conducting comparative analyses between surgical techniques.

Urinary continence recovery and oncological outcomes after surgery for prostate cancer analysed by risk category: results from the LAParoscopic prostatectomy robot and open trial.

PURPOSE: To evaluate urinary continence (UC) recovery and oncological outcomes in different risk-groups after robot-assisted radical prostatectomy (RALP) and open retropubic radical prostatectomy (RRP). PATIENTS AND METHODS: We analysed 2650 men with prostate cancer from seven open (n = 805) and seven robotic (n = 1845) Swedish centres between 2008 and 2011 in a prospective non-randomised trial, LAPPRO. UC recovery was defined as change of pads less than once in 24 h. Information was collected through validated questionnaires. Rate of positive surgical margins (PSM) and biochemical recurrence (BCR), defined as prostate-specific antigen (PSA) > 0.25 mg/ml, were recorded. We stratified patients into two risk groups (low-intermediate and high risk) based on the D'Amico risk classification system. RESULT: Among men with high-risk prostate cancer, we found significantly higher rates of UC recovery up to 24 months after RRP compared to RALP (66.1% vs 60.5%) RR 0.85 (CI 95% 0.73-0.99) while PSM was more frequent after RRP compared to RALP (46.8% vs 23.5%) RR 1.56 (CI 95% 1.10-2.21). In the same group no significant difference was seen in BCR. Overall, however, BCR was significantly more common after RRP compared to RALP at 24 months (9.8% vs 6.6%) RR 1.43 (Cl 95% 1.08-1.89). The limitations of this study are its non-randomized design and the relatively short time of follow-up. CONCLUSIONS: Our study indicates that men with high-risk tumour operated with open surgery had better urinary continence recovery but with a higher risk of PSM than after robotic-assisted laparoscopic surgery. No significant difference was seen in biochemical recurrence.  TRIAL REGISTRATION: ISRCTN06393679.