Association Between the Decipher Genomic Classifier and Prostate Cancer Outcome in the Real-world Setting.

BACKGROUND AND OBJECTIVE: Although the prognostic significance of the Decipher prostate cancer genomic classifier (GC) has been established largely from analyses of archival tissue, less is known about the associations between the results of Decipher testing and oncologic outcomes among patients receiving contemporaneous testing and treatment in the real-world practice setting. Our objective was to assess the associations between the Decipher GC and risks of metastasis and biochemical recurrence (BCR) following prostate biopsy and radical prostatectomy (RP) among patients tested and treated in the real-world setting. METHODS: A retrospective cohort study was conducted using a novel longitudinal linkage of transcriptomic data from the Decipher GC and real-world clinical data (RWD) aggregated from insurance claims, pharmacy records, and electronic health record data across payors and sites of care. Kaplan-Meier and Cox proportional hazards regressions were used to examine the associations between the GC and study outcomes, adjusting for clinical and pathologic factors. KEY FINDINGS AND LIMITATIONS: Metastasis from prostate cancer and BCR after radical prostatectomy, Decipher GC continuous score, and risk categories were evaluated. We identified 58 935 participants who underwent Decipher testing, including 33 379 on a biopsy specimen and 25 556 on an RP specimen. The median age was 67 yr (interquartile range [IQR] 62-72) at biopsy testing and 65 yr (IQR 59-69) at RP. The median GC score was 0.43 (IQR 0.27-0.66) among biopsy-tested patients and 0.54 (0.32-0.79) among RP-tested patients. The GC was independently associated with the risk of metastasis among biopsy-tested (hazard ratio [HR] per 0.1 unit increase in GC 1.21 [95% confidence interval {CI} 1.16-1.27], p < 0.001) and RP-tested (HR 1.20 [95% CI 1.17-1.24], p < 0.001) patients after adjusting for baseline clinical and pathologic risk factors. In addition, the GC was associated with the risk of BCR among RP-tested patients (HR 1.12 [95% CI 1.10-1.14], p < 0.001) in models adjusted for age and Cancer of the Prostate Risk Assessment postsurgical score. CONCLUSIONS AND CLINICAL IMPLICATIONS: This real-world study of a novel transcriptomic linkage conducted at a national scale supports the external prognostic validity of the Decipher GC among patients managed in contemporary practice. PATIENT SUMMARY: This study looked at the use of the Decipher genomic classifier, a test used to help understand the aggressiveness of a patient's prostate cancer. Looking at the results of 58 935 participants who underwent testing, we found that the Decipher test helped estimate the risk of cancer recurrence and metastasis.

Modern predictors and management of incidental prostate cancer at holmium enucleation of prostate.

BACKGROUND: To evaluate contemporary preoperative risk factors and subsequent postoperative management of incidental prostate cancer (iPCa) and incidental clinically significant prostate cancer (icsPCa, Grade Group [GG] ≥ 2 PCa). METHODS: A retrospective cohort of 811 men undergoing Holmium enucleation of the prostate (HoLEP) (January 2021-July 2022) were identified. Advanced preoperative testing was defined as prostate health index (PHI), prostate MRI, and/or negative preoperative biopsy. Descriptive statistics (Whitney-Mann U test, Chi-squared test) and multivariable logistic regression were performed. RESULTS: iPCa and icsPCa detection rates were 12.8% (104/811) and 4.4% (36/811), respectively. Advanced preoperative testing (406/811, 50%) was associated with younger age and higher (prostate specific antigen) PSA, prostate volume, and PSA density. On multivariable analysis, PHI ≥ 55 was associated with iPCa (OR 6.91, 95% CI 1.85-26.3, p = 0.004), and % free PSA (%fPSA) was associated with icsPCa (OR 0.83, 95% CI 0.67, 0.94, p = 0.01). GG1 disease comprised the majority of iPCa (65%, 68/104) with median 1% involvement. iPCa patients were followed with active surveillance (median follow up 9.3 months), with higher risk patients receiving prostate MRI and confirmatory biopsy. Three patients proceeded to radical prostatectomy or radiation. CONCLUSIONS: In the era of MRI and advanced biomarkers, the majority of iPCa following HoLEP is low volume GG1 suitable for active surveillance. A tentative follow-up strategy is proposed. Patients with PHI ≥ 55 or low %fPSA, even with negative prostate MRI, can consider preoperative prostate biopsy before HoLEP.

Neoadjuvant Cisplatin, Gemcitabine, and Docetaxel in Sarcomatoid Bladder Cancer: Clinical Activity and Whole Transcriptome Analysis.

BACKGROUND: Sarcomatoid urothelial cancer of the bladder (SBC) is a rare, but aggressive histological subtype for which novel treatments are needed. OBJECTIVE: We evaluated the clinical activity and safety of neoadjuvant cisplatin plus gemcitabine plus docetaxel (CGD) in muscle-invasive patients with SBC and assessed SBC tumor biology by whole transcriptome RNA sequencing. METHODS: A single-institution, retrospective analysis of muscle-invasive SBC patients treated with neoadjuvant CGD with molecular analysis. Patients received cisplatin 35 mg/m2 + gemcitabine 800 mg/m2 + docetaxel 35 mg/m2 intravenously on days 1 and 8 + pegfilgrastim 6 mg subcutaneously on day 9 every 3 weeks for 4 cycles followed by cystectomy. The primary endpoint was pathologic complete response (ypCR) rate. RESULTS: Sixteen patients with SBC received neoadjuvant CGD with a ypCR rate of 38% and a < ypT2 rate of 50%. Grade 3 and 4 toxicity occurred in 80% and 40% of patients, but was manageable with 81% of patients completing > 3 CGD cycles. Whole transcriptome RNA sequencing demonstrates co-clustering of SBC with conventional urothelial tumors. SBC tumors are characterized by basal-squamous and stroma rich gene signatures with frequent increased expression of immune checkpoint (CD274 (PD-L1)), chemokine (CXCL9), and T-cell (CD8A) genes. CONCLUSIONS: SBC is a chemosensitive subtype, with ypCR rate similar to urothelial bladder cancer following CGD neoadjuvant therapy. Whole transcriptome tissue analyses demonstrate increased expression of immune checkpoint and T-cell genes with therapeutic implications.

Plasma-treated gold microelectrodes for subsecond detection of Zn(II) with fast-scan cyclic voltammetry.

The sensitivity of zinc (Zn(II)) detection using fast-scan cyclic voltammetry (FSCV) with carbon fiber microelectrodes (CFMEs) is low compared to other neurochemicals. We have shown previously that Zn(II) plates to the surface of CFME's and we speculate that it is because of the abundance of oxide functionality on the surface. Plating reduces sensitivity over time and causes significant disruption to detection stability. This limited sensitivity and stability hinders Zn(II) detection, especially in complex matrices like the brain. To address this, we developed plasma-treated gold fiber microelectrodes (AuMEs) which enable sensitive and stable Zn(II) detection with FSCV. Typically, gold fibers are treated using corrosive acids to clean the surface and this step is important for preparing the surface for electrochemistry. Likewise, because FSCV is an adsorption-based technique, it is also important for Zn(II) to adsorb and desorb to prevent irreversible plating. Because of these requirements, careful optimization of the electrode surface was necessary to render the surface for Zn(II) adsorption yet strike a balance between attraction to the surface vs. irreversible interactions. In this study, we employed oxygen plasma treatment to activate the gold fiber surface without inducing significant morphological changes. This treatment effectively removes the organic layer while functionalizing the surface with oxygen, enabling Zn(II) detection that is not possible on untreated gold surfaces. Our results demonstrate significantly improved Zn(II) detection sensitivity and stability on AuME compared to CFME's. Overall, this work provides an advance in our understanding of Zn(II) electrochemistry and a new tool for improved metallotransmitter detection in the brain.

Use of Decipher Prostate Biopsy Test in Patients with Favorable-risk Disease Undergoing Conservative Management or Radical Prostatectomy in the Surveillance, Epidemiology, and End Results Registry.

BACKGROUND AND OBJECTIVE: The extent of prostate cancer found on biopsy, as well as prostate cancer grade and genomic tests, can affect clinical decision-making. The impact of these factors on the initial management approach and subsequent patient outcomes for men with favorable-grade prostate cancer has not yet been determined on a population level. Our objective was to explore the association of Decipher 22-gene genomic classifier (GC) biopsy testing on the initial use of conservative management versus radical prostatectomy (RP) and to determine the independent effect of GC scores on RP pathologic outcomes. METHODS: A total of 87 140 patients diagnosed with grade group 1 and 2 prostate cancer between 2016 and 2018 from the Surveillance, Epidemiology, and End Results registry data were linked to GC testing results (2576 tested and 84 564 untested with a GC). The primary endpoints of interest were receipt of conservative management or RP, pathologic upgrading (pathologic grade group 3-5), upstaging (pathologic ≥T3b), and adverse pathologic features (pathologic upgrading, upstaging, or lymph node invasion). Multivariable logistic regressions quantified the association of variables with outcomes of interest. KEY FINDINGS AND LIMITATIONS: GC tested patients were more likely to have grade group 2 on biopsy (51% vs 46%, p < 0.001) and lower prostate-specific antigen (6.1 vs 6.3, p = 0.016). Conservative management increased from 37% to 39% and from 22% to 24% during 2016-2018 for the GC tested and untested populations, respectively. GC testing was significantly associated with increased odds of conservative management (odds ratio [OR] 2.1, 95% confidence interval [CI] 1.9-2.4, p < 0.001). The distribution of biopsy GC risk was as follows: 45% low risk, 30% intermediate risk, and 25% high risk. In adjusted analyses, higher GC (per 0.1 increment) scores (OR 1.24, 95% CI 1.17-1.31, p < 0.001) and percent positive cores (1.07, 95% CI 1.02-1.12, p = 0.009) were significantly associated with the receipt of RP. A higher GC score was significantly associated with all adverse outcomes (pathologic upgrading [OR 1.29, 95% CI 1.12-1.49, p < 0.001], upstaging [OR 1.31, 95% CI 1.05-1.62, p = 0.020], and adverse pathology [OR 1.27, 95% CI 1.12-1.45, p < 0.001]). Limitations include observational biases associated with the retrospective study design. CONCLUSIONS AND CLINICAL IMPLICATIONS: Men who underwent GC testing were more likely to undergo conservative management. GC testing at biopsy is prognostic of adverse pathologic outcomes in a large population-based registry. PATIENT SUMMARY: In this population analysis of men with favorable-risk prostate cancer, those who underwent genomic testing at biopsy were more likely to undergo conservative management. Of men who initially underwent radical prostatectomy, higher genomic risk but not tumor volume was associated with adverse pathologic outcomes. The use of genomic testing at prostate biopsy improves risk stratification and may better inform treatment decisions than the use of tumor volume alone.

Transcriptomic Profiling of Primary Prostate Cancers and Nonlocalized Disease on Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study.

PURPOSE: To characterize the relationship between Decipher genomic classifier scores and prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT)-based metastatic spread. MATERIALS AND METHODS: We identified patients from four institutions who underwent PSMA PET/CT scans pretreatment for primary staging or postradical prostatectomy (RP) for suspected recurrence and had Decipher transcriptomic data available from biopsy or RP specimens. PSMA PET/CT-based patterns of spread were classified as localized (miT + N0M0) or nonlocalized (miN1M0 or miM1a-c). We calculated the association between Decipher scores and the risk of nonlocalized disease on PSMA PET/CT using multivariable logistic regression for pretreatment patients and multivariable Cox regression for post-RP patients. We also compared select transcriptomic signatures between patients with localized and nonlocalized diseases. RESULTS: Five hundred eighty-six patients were included (pretreatment: n = 329; post-RP: n = 257). Higher Decipher scores were associated with nonlocalized disease on PSMA PET/CT both pretreatment (odds ratio, 1.18 [95% CI, 1.03 to 1.36] per 0.1 increase in Decipher score, P = .02) and post-RP (hazard ratio, 1.15 [95% CI, 1.05 to 1.27] per 0.1 increase in Decipher score, P = .003). In the pretreatment setting, nonlocalized disease was associated with higher rates of TP53 mutations and lower rates of PAM50 luminal A subtype compared with localized disease. In the post-RP setting, overexpression of signatures related to metabolism, DNA repair, and androgen receptor signaling were associated with higher rates of nonlocalized disease. CONCLUSION: Higher Decipher scores were associated with nonlocalized disease identified on PSMA PET/CT both pretreatment and post-RP. There were several transcriptomic differences between localized and nonlocalized diseases in both settings.

Development of a Novel Patient-Reported Outcome Measure to Assess Symptoms and Impacts of Androgen Deprivation Therapy for Advanced Prostate Cancer.

INTRODUCTION: This qualitative research study was conducted to develop a novel, comprehensive, patient-reported outcome measure (PRO), the "Symptoms and Impacts of Androgen Deprivation Therapy (ADT) for Prostate Cancer" (SIADT-PC), assessing hormonal therapy-related symptoms and their impacts on men with advanced prostate cancer. METHODS: Concept elicitation (CE) interviews were conducted among adult men with prostate cancer to evaluate their experiences with ADT. Based on key symptom and impact concepts mentioned, an initial PRO measure was developed. The draft measure was further assessed in cognitive debriefing (CD) interviews with men with prostate cancer, in which participants reviewed items, response options, and recall periods. Initial item-based psychometric analyses were conducted using interview data. The draft questionnaire was revised on the basis of participant feedback, quantitative psychometric results, and consultation with clinical experts. RESULTS: A total of 21 participants were interviewed (CE concept elicitation, n = 12; CD cognitive debriefing, n = 17; n = 8 completed both). Mean participant age (SD) was 59.7 (8.7) years and 76.2% were white. The de novo SIADT-PC measure consists of 27 items: 11 symptoms (e.g., fatigue, hot flashes, and erectile dysfunction), 2 long-term symptoms (e.g., weight gain), 10 impacts (e.g., impacts on physical activities and relationships), and 4 related to mode of administration (i.e., injection-site reactions). Items were assessed with a 5-point verbal rating scale, with answer choices that capture frequency or severity. CONCLUSIONS: Once fully validated, this de novo measure may be used in clinical studies and clinical practice to assess hormone therapy-related symptoms and impacts, enabling physicians to identify timely and appropriate interventions.

Detection of clinically significant prostate cancer following initial omission of biopsy in multiparametric MRI era.

BACKGROUND: Multiparametric prostate MRI (mpMRI) is being increasingly adopted for work-up of prostate cancer. For patients selected to omit biopsy, we identified factors associated with repeat MRI, eventual prostate biopsy, and subsequent detection of clinically significant prostate cancer (csPCa, Grade Group ≥2). METHODS: We identified biopsy-naïve men presenting with PSA 2-20 ng/mL (March 2018-June 2021) undergoing initial mpMRI with PIRADS 1-3 lesions who were not selected for biopsy with ≥6 months follow-up. We examined factors associated with repeat mpMRI, progression to biopsy, and subsequent detection of csPCa with univariable and multivariable logistic regression. RESULTS: Of 1494 men, 31% (463/1494) did not pursue biopsy. PSA density (PSAD) ≤ 0.1, prostate health index (PHI) < 55, and PIRADS 1-2 were associated with omission of prostate biopsy. csPCa diagnosis-free survival was 97.6% (326/334) with median follow up of 23.1 months (IQR 15.1-34.6 months). Black race, PSA, PHI, PSA density, and PSA and PHI velocity were significant predictors of undergoing repeat mpMRI (15.6%, 52/334) and subsequent biopsy (8.4%, 28/334). 8 men were subsequently diagnosed with csPCa (N = 7 on prostate biopsy; N = 1 incidentally on holmium enucleation of prostate). All patients diagnosed with csPCa had PIRADS 4-5 on repeat mpMRI. CONCLUSIONS: The subsequent detection rate of csPCa among patients not initially biopsied after mpMRI was low at 2.4%. Decisions to omit biopsy after initial reassuring PHI, PSAD, and mpMRI appear safe with subsequent reassuring serum biomarkers and for cause mpMRI during follow-up.

Development of a Longitudinal Prostate Cancer Transcriptomic and Clinical Data Linkage.

Importance: Although tissue-based gene expression testing has become widely used for prostate cancer risk stratification, its prognostic performance in the setting of clinical care is not well understood. Objective: To develop a linkage between a prostate genomic classifier (GC) and clinical data across payers and sites of care in the US. Design, Setting, and Participants: In this cohort study, clinical and transcriptomic data from clinical use of a prostate GC between 2016 and 2022 were linked with data aggregated from insurance claims, pharmacy records, and electronic health record (EHR) data. Participants were anonymously linked between datasets by deterministic methods through a deidentification engine using encrypted tokens. Algorithms were developed and refined for identifying prostate cancer diagnoses, treatment timing, and clinical outcomes using diagnosis codes, Common Procedural Terminology codes, pharmacy codes, Systematized Medical Nomenclature for Medicine clinical terms, and unstructured text in the EHR. Data analysis was performed from January 2023 to January 2024. Exposure: Diagnosis of prostate cancer. Main Outcomes and Measures: The primary outcomes were biochemical recurrence and development of prostate cancer metastases after diagnosis or radical prostatectomy (RP). The sensitivity of the linkage and identification algorithms for clinical and administrative data were calculated relative to clinical and pathological information obtained during the GC testing process as the reference standard. Results: A total of 92 976 of 95 578 (97.2%) participants who underwent prostate GC testing were successfully linked to administrative and clinical data, including 53 871 who underwent biopsy testing and 39 105 who underwent RP testing. The median (IQR) age at GC testing was 66.4 (61.0-71.0) years. The sensitivity of the EHR linkage data for prostate cancer diagnoses was 85.0% (95% CI, 84.7%-85.2%), including 80.8% (95% CI, 80.4%-81.1%) for biopsy-tested participants and 90.8% (95% CI, 90.5%-91.0%) for RP-tested participants. Year of treatment was concordant in 97.9% (95% CI, 97.7%-98.1%) of those undergoing GC testing at RP, and 86.0% (95% CI, 85.6%-86.4%) among participants undergoing biopsy testing. The sensitivity of the linkage was 48.6% (95% CI, 48.1%-49.1%) for identifying RP and 50.1% (95% CI, 49.7%-50.5%) for identifying prostate biopsy. Conclusions and Relevance: This study established a national-scale linkage of transcriptomic and longitudinal clinical data yielding high accuracy for identifying key clinical junctures, including diagnosis, treatment, and early cancer outcome. This resource can be leveraged to enhance understandings of disease biology, patterns of care, and treatment effectiveness.

Contemporary Diagnosis of Very Low-risk Prostate Cancer in a Multihospital Health Care System.

The National Comprehensive Cancer Network (NCCN) very low risk (VLR) category for prostate cancer (PCa) represents clinically insignificant disease, and detection of VLR PCa contributes to overdiagnosis. Greater use of magnetic resonance imaging (MRI) and biomarkers before patient selection for prostate biopsy (PBx) reduces unnecessary biopsies and may reduce the diagnosis of clinically insignificant PCa. We tested a hypothesis that the proportion of VLR diagnoses has decreased with greater use of MRI-informed PBx using data from our 11-hospital system. From 2018 to 2023, 351/3197 (11%) men diagnosed with PCa met the NCCN VLR criteria. The proportion of VLR diagnoses did not change from 2018 to 2023 (p = 0.8) despite an increase in the use of MRI-informed PBx (from 49% to 82%; p < 0.001). Of patients who underwent combined systematic and targeted PBx and were diagnosed with VLR disease, cancer was found in systematic PBx regions in 79% of cases and in targeted PBx regions in 31% of cases. When performing both systematic and targeted PBx, prebiopsy MRI-based risk calculators could limit VLR diagnosis by 41% using a risk threshold of >5% for Gleason grade group ≥3 PCa to recommend biopsy; the reduction would be 77% if performing targeted PBx only. These findings suggest that VLR disease continues to account for a significant minority of PCa diagnoses and could be limited by targeted PBx and risk stratification calculators. PATIENT SUMMARY: We looked at recent trends for the diagnosis of very low-risk (VLR) prostate cancer. We found that VLR cancer still seems to be frequently diagnosed despite the use of MRI (magnetic resonance imaging) scans before biopsy. The use of risk calculators to identify men who could avoid biopsy and/or biopsy only for lesions that are visible on MRI could reduce the overdiagnosis of VLR prostate cancer.

Surface-Roughened Graphene Oxide Microfibers Enhance Electrochemical Reversibility.

Here, we provide an optimized method for fabricating surface-roughened graphene oxide disk microelectrodes (GFMEs) with enhanced defect density to generate a more suitable electrode surface for dopamine detection with fast-scan cyclic voltammetry (FSCV). FSCV detection, which is often influenced by adsorption-based surface interactions, is commonly impacted by the chemical and geometric structure of the electrode's surface, and graphene oxide is a tunable carbon-based nanomaterial capable of enhancing these two key characteristics. Synthesized GFMEs possess exquisite electronic and mechanical properties. We have optimized an applied inert argon (Ar) plasma treatment to increase defect density, with minimal changes in chemical functionality, for enhanced surface crevices to momentarily trap dopamine during detection. Optimal Ar plasma treatment (100 sccm, 60 s, 100 W) generates crevice depths of 33.4 ± 2.3 nm with high edge plane character enhancing dopamine interfacial interactions. Increases in GFME surface roughness improve electron transfer rates and limit diffusional rates out of the crevices to create nearly reversible dopamine electrochemical redox interactions. The utility of surface-roughened disk GFMEs provides comparable detection sensitivities to traditional cylindrical carbon fiber microelectrodes while improving temporal resolution ten-fold with amplified oxidation current due to dopamine cyclization. Overall, surface-roughened GFMEs enable improved adsorption interactions, momentary trapping, and current amplification, expanding the utility of GO microelectrodes for FSCV detection.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer.

Importance: Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater). Objective: To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers. Design, Setting, and Participants: RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023. Exposure: Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy. Main Outcomes and Measures: Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily. Results: Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater. Conclusions and Relevance: In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Transcriptome-Based Prognostic and Predictive Biomarker Analysis of ENACT: A Randomized Controlled Trial of Enzalutamide in Men Undergoing Active Surveillance.

PURPOSE: Few studies have explored the potential for pharmacological interventions to delay disease progression in patients undergoing active surveillance (AS). This preplanned transcriptomic analysis of patient samples from the ENACT trial aims to identify biomarkers in patients on AS who are at increased risk for disease progression or who may derive the greatest benefit from enzalutamide treatment. PATIENTS AND METHODS: In the phase II ENACT (ClinicalTrials.gov identifier: NCT02799745) trial, patients on AS were randomly assigned 1:1 to 160 mg orally once daily enzalutamide monotherapy or continued AS for 1 year. Transcriptional analyses were conducted on biopsies collected at trial screening, year 1, and year 2. Three gene expression signatures were evaluated in samples collected at screening and in available samples from patients on AS at any time during surveillance (expanded cohort): Decipher genomic classifier, androgen receptor activity (AR-A) score, and Prediction Analysis of Microarray 50 (PAM50) cell subtype signature. RESULTS: The Decipher genomic classifier score was prognostic; higher scores were associated with disease progression in the expanded cohort and AS arm of the expanded cohort. Patients with higher Decipher scores had greater positive treatment effect from enzalutamide as measured by time to secondary rise in prostate-specific antigen >25% above baseline. In patients treated with enzalutamide, higher AR-A scores and PAM50 luminal subtypes were associated with a greater likelihood of negative biopsy incidence at year 2. CONCLUSION: This analysis suggests that the Decipher genomic classifier may be prognostic for disease progression in AS patients with low- to intermediate-risk prostate cancer. Higher Decipher and AR-A scores, as well as PAM50 luminal subtypes, may also serve as biomarkers for treatment response.

Ultrasensitive PSA: rethinking post-surgical management for node positive prostate cancer.

Introduction: Clinicians may offer patients with positive lymph nodes (pN1) and undetectable PSA following surgery for prostate cancer either observation or adjuvant therapy based on AUA, EAU, and NCCN guidelines considering standard PSA detection thresholds of <0.1ng/ml. Here we sought to investigate the outcomes of pN1 patients in the era of ultrasensitive PSA testing. Methods: We queried the Northwestern Electronic Data Warehouse for patients with prostate cancer who were pN1 at radical prostatectomy and followed with ultrasensitive PSA. Patients receiving neoadjuvant treatment were excluded. We compared clinical characteristics including age, race, pre-operative PSA, Gleason grade, tumor stage, surgical margins, and nodal specimens to identify factors associated with achievement and maintenance of an undetectable PSA (defined as <0.01 ng/mL). Statistics were performed using t-test, Mann-Whitney U test, chi-squared analysis, and logistic regression with significance defined as p<0.05. Results: From 2018-2023, 188 patients were included. Subsequently, 39 (20.7%) had a PSA decline to undetectable levels (<0.01 ng/mL) post-operatively at a median time of 63 days. Seven percent of these men (3/39) were treated with adjuvant RT + ADT with undetectable PSA levels. 13/39 (33.3%) had eventual rises in PSA to ≥0.01 ng/mL for which they underwent salvage RT with ADT. Overall, 23/39 (59%) patients achieved and maintained undetectable PSA levels without subsequent therapy at median follow-up of 24.2 mo. Compared to patients with PSA persistence after surgery or elevations to detectable levels (≥0.01 ng/mL), patients who achieved and maintained undetectable levels had lower Gleason grades (p=0.03), lower tumor stage (p<0.001), fewer positive margins (p=0.02), and fewer involved lymph nodes (p=0.02). On multivariable analysis, only primary tumor (pT) stage was associated with achieving and maintaining an undetectable PSA; pT3b disease was associated with a 6.6-fold increased chance of developing a detectable PSA (p=0.03). Conclusion: Ultrasensitive PSA can aid initiation of early salvage therapy for lymph node positive patients after radical prostatectomy while avoiding overtreatment in a significant subset. 20% of patients achieved an undetectable PSA and over half of this subset remained undetectable after 2 years.

Comparison of Magnetic Resonance Imaging-Based Risk Calculators to Predict Prostate Cancer Risk.

Importance: Magnetic resonance imaging (MRI)-based risk calculators can replace or augment traditional prostate cancer (PCa) risk prediction tools. However, few data are available comparing performance of different MRI-based risk calculators in external cohorts across different countries or screening paradigms. Objective: To externally validate and compare MRI-based PCa risk calculators (Prospective Loyola University Multiparametric MRI [PLUM], UCLA [University of California, Los Angeles]-Cornell, Van Leeuwen, and Rotterdam Prostate Cancer Risk Calculator-MRI [RPCRC-MRI]) in cohorts from Europe and North America. Design, Setting, and Participants: This multi-institutional, external validation diagnostic study of 3 unique cohorts was performed from January 1, 2015, to December 31, 2022. Two cohorts from Europe and North America used MRI before biopsy, while a third cohort used an advanced serum biomarker, the Prostate Health Index (PHI), before MRI or biopsy. Participants included adult men without a PCa diagnosis receiving MRI before prostate biopsy. Interventions: Prostate MRI followed by prostate biopsy. Main Outcomes and Measures: The primary outcome was diagnosis of clinically significant PCa (grade group ≥2). Receiver operating characteristics for area under the curve (AUC) estimates, calibration plots, and decision curve analysis were evaluated. Results: A total of 2181 patients across the 3 cohorts were included, with a median age of 65 (IQR, 58-70) years and a median prostate-specific antigen level of 5.92 (IQR, 4.32-8.94) ng/mL. All models had good diagnostic discrimination in the European cohort, with AUCs of 0.90 for the PLUM (95% CI, 0.86-0.93), UCLA-Cornell (95% CI, 0.86-0.93), Van Leeuwen (95% CI, 0.87-0.93), and RPCRC-MRI (95% CI, 0.86-0.93) models. All models had good discrimination in the North American cohort, with an AUC of 0.85 (95% CI, 0.80-0.89) for PLUM and AUCs of 0.83 for the UCLA-Cornell (95% CI, 0.80-0.88), Van Leeuwen (95% CI, 0.79-0.88), and RPCRC-MRI (95% CI, 0.78-0.87) models, with somewhat better calibration for the RPCRC-MRI and PLUM models. In the PHI cohort, all models were prone to underestimate clinically significant PCa risk, with best calibration and discrimination for the UCLA-Cornell (AUC, 0.83 [95% CI, 0.81-0.85]) model, followed by the PLUM model (AUC, 0.82 [95% CI, 0.80-0.84]). The Van Leeuwen model was poorly calibrated in all 3 cohorts. On decision curve analysis, all models provided similar net benefit in the European cohort, with higher benefit for the PLUM and RPCRC-MRI models at a threshold greater than 22% in the North American cohort. The UCLA-Cornell model demonstrated highest net benefit in the PHI cohort. Conclusions and Relevance: In this external validation study of patients receiving MRI and prostate biopsy, the results support the use of the PLUM or RPCRC-MRI models in MRI-based screening pathways regardless of European or North American setting. However, tools specific to screening pathways incorporating advanced biomarkers as reflex tests are needed due to underprediction.

A multidisciplinary approach to address unmet needs in the management of patients with non-metastatic castration-resistant prostate cancer.

BACKGROUND: With the availability of second-generation androgen receptor inhibitors (SGARIs), the treatment landscape has changed dramatically for patients with nonmetastatic castration-resistant prostate cancer (nmCRPC). In clinical trials, the SGARIs (apalutamide, enzalutamide, darolutamide) increased metastasis-free survival (MFS), overall survival (OS), and patient quality of life compared to placebo. These drugs were subsequently integrated into nmCRPC clinical practice guidelines. With advances in radiographic imaging, disease assessment, and patient monitoring, nmCRPC strategies are evolving to address limitations related to tracking disease progression using prostate-specific antigen (PSA) kinetics. METHODS: A panel of 10 multidisciplinary experts in prostate cancer conducted reviews and discussions of unmet needs in the management and monitoring of patients with nmCRPC in order to develop consensus recommendations. RESULTS: Across the SGARI literature, patient MFS and OS are generally comparable for all treatments, but important distinctions exist regarding short- and long-term drug safety profiles and drug-drug interactions. With respect to disease monitoring, a substantial proportion of patients using SGARIs may experience disease progression without rising PSA levels, suggesting a need for enhanced radiographic imaging in addition to PSA monitoring. Recent data also indicate that novel prostate-specific membrane antigen positron emission tomography radiotracers provide enhanced accuracy for disease detection, as compared to conventional imaging. CONCLUSIONS: Clinical decision-making in nmCRPC has become more complex, with new opportunities to apply precision medicine to patient care. Multidisciplinary teams can ensure that patients with nmCRPC receive optimal and individualized disease management.

Implementation of PSMA PET/CT and alignment of ordering to SNMMI appropriate use criteria in a large network system.

INTRODUCTION: The Society of Nuclear Medicine and Molecular Imaging (SNMMI) provides appropriate use criteria (AUC) for prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT) which include guidance on imaging in newly diagnosed prostate cancer and in patients with biochemically recurrent (BCR) disease. This study aims to examine trends in PSMA implementation and the prevalence and outcomes of scans ordered in scenarios deemed rarely appropriate or not meeting SNMMI AUC. METHODS: We retrospectively identified patients who were diagnosed with presumptive National Comprehensive Cancer Network unfavorable intermediate, high, or very high risk prostate cancer, patients who underwent staging for BCR, and all patients staged with PSMA between July 2021 and March 2023. Positivity was validated by adherence to a predetermined reference standard. RESULTS: The frequency of PSMA use increased in initial staging from 24% to 80% and work-up of BCR from 91% to 99% over our study period. In addition, 5% (17/340) of PSMA scans ordered for initial staging did not meet AUC and 3% (15/557) of posttreatment scans were deemed rarely appropriate. Initial staging orders not meeting SNMMI AUC resulted in no positivity (0/17), while rarely appropriate posttreatment scans were falsely positive in 75% (3/4) of cases. Urologists (53%, 17/32) comprised the largest ordering specialty in rarely appropriate use. CONCLUSION: The frequency of PSMA use rose across the study period. A significant minority of patients received PSMA PET/CT in rarely appropriate scenarios yielding no positivity in initial staging and significant false positivity post-therapy. Further education of providers and electronic medical record-based interventions could help limit the rarely appropriate use of PET imaging.

Evaluating relugolix for the treatment of prostate cancer in real-world settings of care: the OPTYX study protocol.

OPTYX is a multi-center, prospective, observational study designed to further understand the actual experience of patients with advanced prostate cancer treated with relugolix (ORGOVYX®), an oral androgen deprivation therapy (ADT), by collecting clinical and patient-reported outcomes from routine care settings. The study aims to enroll 1000 consented patients with advanced prostate cancer from community, academic and government operated clinical practices across the USA. At planned timepoints, real-world data analysis on treatment patterns, adherence and safety as well as health outcomes and health-related quality-of-life (HRQOL) after treatment discontinuation will be published in scientific peer-reviewed journals and presented at relevant conferences. This study will provide real-world data for practitioners and researchers in their understanding of the safety and effectiveness of relugolix. Clinical Trial Registration: NCT05467176 (ClinicalTrials.gov).

What is this summary about? This is a protocol summary for a research study named OPTYX. Who can participate in this research? Men 18 or older with advanced prostate cancer initiating treatment with relugolix, an oral androgen deprivation therapy (ADT), at the time of enrollment or within the 1 month before enrollment (remaining on treatment at enrollment) and are willing and able to complete patient assessments during the study. What institutions are performing this research? Community practices, academic institutions and Veterans Health Administration facilities across the USA. What are the research assessments to obtain the results? Data will be collected from the routine medical visits twice yearly including patient demographics, medical history (co-morbidities and cardiac risk factors), prostate cancer history and treatments and test results (routine lab testosterone, PSA levels and imaging). Relugolix response and all serious adverse events (SAEs) and any nonserious adverse events (AE) leading to relugolix treatment discontinuation will be assessed. Patients will be asked to respond to evaluations about their health-related quality of life and adherence to relugolix treatment. How long would the study last? Up to 5 years from enrollment date and/or up to 2 years after relugolix discontinuation. Follow-up will end with consent withdrawal, loss to follow-up, death, or study termination, whichever comes first. What do the results of the study mean? Real-world understanding of the experience and clinical outcomes in patients with advanced prostate cancer in routine clinical care and their clinical trajectory following cessation of relugolix therapy.

External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial.

BACKGROUND: Accurate risk stratification is critical to guide management decisions in localized prostate cancer (PCa). Previously, we had developed and validated a multimodal artificial intelligence (MMAI) model generated from digital histopathology and clinical features. Here, we externally validate this model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial. OBJECTIVE: To externally validate the MMAI model on men with high-risk or locally advanced PCa treated and followed as part of a phase 3 randomized control trial. DESIGN, SETTING, AND PARTICIPANTS: Our validation cohort included 318 localized high-risk PCa patients from NRG/RTOG 9902 with available histopathology (337 [85%] of the 397 patients enrolled into the trial had available slides, of which 19 [5.6%] failed due to poor image quality). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Two previously locked prognostic MMAI models were validated for their intended endpoint: distant metastasis (DM) and PCa-specific mortality (PCSM). Individual clinical factors and the number of National Comprehensive Cancer Network (NCCN) high-risk features served as comparators. Subdistribution hazard ratio (sHR) was reported per standard deviation increase of the score with corresponding 95% confidence interval (CI) using Fine-Gray or Cox proportional hazards models. RESULTS AND LIMITATIONS: The DM and PCSM MMAI algorithms were significantly and independently associated with the risk of DM (sHR [95% CI] = 2.33 [1.60-3.38], p < 0.001) and PCSM, respectively (sHR [95% CI] = 3.54 [2.38-5.28], p < 0.001) when compared against other prognostic clinical factors and NCCN high-risk features. The lower 75% of patients by DM MMAI had estimated 5- and 10-yr DM rates of 4% and 7%, and the highest quartile had average 5- and 10-yr DM rates of 19% and 32%, respectively (p < 0.001). Similar results were observed for the PCSM MMAI algorithm. CONCLUSIONS: We externally validated the prognostic ability of MMAI models previously developed among men with localized high-risk disease. MMAI prognostic models further risk stratify beyond the clinical and pathological variables for DM and PCSM in a population of men already at a high risk for disease progression. This study provides evidence for consistent validation of our deep learning MMAI models to improve prognostication and enable more informed decision-making for patient care. PATIENT SUMMARY: This paper presents a novel approach using images from pathology slides along with clinical variables to validate artificial intelligence (computer-generated) prognostic models. When implemented, clinicians can offer a more personalized and tailored prognostic discussion for men with localized prostate cancer.