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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Waste Coffee Ground-Derived Porous Carbon for Neurochemical Detection.

We present an optimized synthetic method for repurposing coffee waste to create controllable, uniform porous carbon frameworks for biosensor applications to enhance neurotransmitter detection with fast-scan cyclic voltammetry. Harnessing porous carbon structures from biowastes is a common practice for low-cost energy storage applications; however, repurposing biowastes for biosensing applications has not been explored. Waste coffee ground-derived porous carbon was synthesized by chemical activation to form multivoid, hierarchical porous carbon, and this synthesis was specifically optimized for porous uniformity and electrochemical detection. These materials, when modified on carbon-fiber microelectrodes, exhibited high surface roughness and pore distribution, which contributed to significant improvements in electrochemical reversibility and oxidative current for dopamine (3.5 ± 0.4-fold) and other neurochemicals. Capacitive current increases were small, showing evidence of small increases in electroactive surface area. Local trapping of dopamine within the pores led to improved electrochemical reversibility and frequency-independent behavior. Overall, we demonstrate an optimized biowaste-derived porous carbon synthesis for neurotransmitter detection for the first time and show material utility for viable neurotransmitter detection within a tissue matrix. This work supports the notion that controlled surface nanogeometries play a key role in electrochemical detection.

Prostate Cancer Detection Rate of Transperineal Prostate Biopsy: Cognitive vs Software Fusion, A Multicenter Analysis.

OBJECTIVE: To compare clinically significant prostate cancer detection with TP-TBx utilizing software vs cognitive fusion. It is established that MRI prior to prostate biopsy improves detection of clinically significant cancer (csPCa, Grade Group ≥2). MRI/US fusion targeted biopsy via a transperineal approach (TP-TBx) is increasing in utilization due to the clean percutaneous approach that greatly reduces postbiopsy infection. However, the comparative effectiveness of formal software fusion over cognitive fusion remains under studied. MATERIALS AND METHODS: We performed a retrospective multicenter study from June 2020 to July 2022 including age, race, prostate-specific antigen (PSA), prostate volume, PI-RADS, lesion size(s), number of cores sampled, indication (elevated PSA, prior negative, active surveillance) and anesthesia type. Surgeon preference determined use of cognitive (PrecisionPoint) vs software fusion techniques. Multivariable logistic regression determined factors associated with TP-TBx detection of csPCa. RESULTS: We identified 490 patients (201 cognitive, 289 software fusion) who underwent TP-TBx. Patient age, PSA, number of targets, and PI-RADS were similar (all P > .05). Software fusion TP-TBx had 4 [95% confidence interval (CI) 3-5] more (estimated median difference) systematic cores sampled. csPCa was detected in 44% of all patients. In adjusted analysis, cognitive vs software fusion was similar in detection of csPCa (odds ratio 1.46, 95% CI 0.82-2.58). CONCLUSION: Cognitive vs software fusion TP-TBx has similar csPCa detection, despite fewer systematic cores taken with cognitive fusion. The expense, additional time requirement, and similar outcomes of software fusion platforms confers higher value to cognitive TP-Bx.

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.

A microfluidic chip for sustained oxygen gradient formation in the intestine ex vivo.

The oxygen gradient across the intestine influences intestinal physiology and the microbial environment of the microbiome. The microbiome releases metabolites that communicate with enterochromaffin cells, neuronal cells, and resident immune cells to facilitate the bidirectional communication across the gut-brain axis. Measuring communication between various cell types within the intestine could provide essential information about key regulators of gut and brain health; however, the microbial environment of the intestine is heavily dependent on the physiological oxygen gradient that exists across the intestinal wall. Likewise, there exist a need for methods which enable real-time monitoring of intestinal signaling ex vivo yet this remains challenging due to the inability to adequately culture intestinal tissue ex vivo while also exposing the appropriate locations of the intestine for probe insertion and monitoring. Here, we designed and fabricated a 3D printed microfluidic device to maintain the oxygen gradient across precision cut murine intestinal slices with the capability to couple to external neurochemical recording techniques. The gradient is maintained from outlets below while allowing access to the slice from above for detection with fast scan cyclic voltammetry (FSCV) and carbon-fiber microelectrodes. A series of 11 outlet ports were designed to lay underneath the slice which were connected to channels to deliver oxygenated vs. deoxygenated media. Outlet ports were designed in an oval shape where deoxygenated media was delivered to the center of the slice and oxygenated media is delivered to the outer portion of the slice to mimic the location of oxygen across the intestine. An oxygen sensitive fluorescent dye, tris(2,2'-bipyridyl)dichlororuthenium(II), was used to characterize the tunability of the gradient. Viability of the tissue was confirmed by both fluorescence microscopy and FSCV. Additionally, we measured simultaneous serotonin and melatonin signaling with FSCV in the intestine for the first time. Overall, this chip provides a significant advance in our ability to culture intestinal slices ex vivo with the added benefit of direct access for measurements and imaging.

Transperineal Versus Transrectal Magnetic Resonance Imaging-targeted and Systematic Prostate Biopsy to Prevent Infectious Complications: The PREVENT Randomized Trial.

BACKGROUND AND OBJECTIVE: The transrectal biopsy approach is traditionally used to detect prostate cancer. An alternative transperineal approach is historically performed under general anesthesia, but recent advances enable transperineal biopsy to be performed under local anesthesia. We sought to compare infectious complications of transperineal biopsy without antibiotic prophylaxis versus transrectal biopsy with targeted prophylaxis. METHODS: We assigned biopsy-naïve participants to undergo transperineal biopsy without antibiotic prophylaxis versus transrectal biopsy with targeted prophylaxis (rectal culture screening for fluoroquinolone-resistant bacteria and antibiotic targeting to culture and sensitivity results) through a multicenter, randomized trial. The primary outcome was post-biopsy infection captured by a prospective medical review and patient report on a 7-d survey. The secondary outcomes included cancer detection, noninfectious complications, and a numerical rating scale (0-10) for biopsy-related pain and discomfort during and 7-d after biopsy. KEY FINDINGS AND LIMITATIONS: A total of 658 participants were randomized, with zero transperineal versus four (1.4%) transrectal biopsy infections (difference -1.4%; 95% confidence interval [CI] -3.2%, 0.3%; p = 0.059). The rates of other complications were very low and similar. Importantly, detection of clinically significant cancer was similar (53% transperineal vs 50% transrectal, adjusted difference 2.0%; 95% CI -6.0, 10). Participants in the transperineal arm experienced worse periprocedural pain (0.6 adjusted difference [0-10 scale], 95% CI 0.2, 0.9), but the effect was small and resolved by 7-d. CONCLUSIONS AND CLINICAL IMPLICATIONS: Office-based transperineal biopsy is tolerable, does not compromise cancer detection, and did not result in infectious complications. Transrectal biopsy with targeted prophylaxis achieved similar infection rates, but requires rectal cultures and careful attention to antibiotic selection and administration. Consideration of these factors and antibiotic stewardship should guide clinical decision-making. PATIENT SUMMARY: In this multicenter randomized trial, we compare prostate biopsy infectious complications for the transperineal versus transrectal approach. The absence of infectious complications with transperineal biopsy without the use of preventative antibiotics is noteworthy, but not significantly different from transrectal biopsy with targeted antibiotic prophylaxis.

Tissue Contamination Challenges the Credibility of Machine Learning Models in Real World Digital Pathology.

Machine learning (ML) models are poised to transform surgical pathology practice. The most successful use attention mechanisms to examine whole slides, identify which areas of tissue are diagnostic, and use them to guide diagnosis. Tissue contaminants, such as floaters, represent unexpected tissue. Although human pathologists are extensively trained to consider and detect tissue contaminants, we examined their impact on ML models. We trained 4 whole-slide models. Three operate in placenta for the following functions: (1) detection of decidual arteriopathy, (2) estimation of gestational age, and (3) classification of macroscopic placental lesions. We also developed a model to detect prostate cancer in needle biopsies. We designed experiments wherein patches of contaminant tissue are randomly sampled from known slides and digitally added to patient slides and measured model performance. We measured the proportion of attention given to contaminants and examined the impact of contaminants in the t-distributed stochastic neighbor embedding feature space. Every model showed performance degradation in response to one or more tissue contaminants. Decidual arteriopathy detection--balanced accuracy decreased from 0.74 to 0.69 ± 0.01 with addition of 1 patch of prostate tissue for every 100 patches of placenta (1% contaminant). Bladder, added at 10% contaminant, raised the mean absolute error in estimating gestational age from 1.626 weeks to 2.371 ± 0.003 weeks. Blood, incorporated into placental sections, induced false-negative diagnoses of intervillous thrombi. Addition of bladder to prostate cancer needle biopsies induced false positives, a selection of high-attention patches, representing 0.033 mm2, and resulted in a 97% false-positive rate when added to needle biopsies. Contaminant patches received attention at or above the rate of the average patch of patient tissue. Tissue contaminants induce errors in modern ML models. The high level of attention given to contaminants indicates a failure to encode biological phenomena. Practitioners should move to quantify and ameliorate this problem.

Comparison of Multiple Segmentation Methods for Volumetric Delineation of Primary Prostate Cancer with Prostate-Specific Membrane Antigen-Targeted 18F-DCFPyL PET/CT.

This study aimed to assess the accuracy of intraprostatic tumor volume measurements on prostate-specific membrane antigen-targeted 18F-DCFPyL PET/CT made with various segmentation methods. An accurate understanding of tumor volumes versus segmentation techniques is critical for therapy planning, such as radiation dose volume determination and response assessment. Methods: Twenty-five men with clinically localized, high-risk prostate cancer were imaged with 18F-DCFPyL PET/CT before radical prostatectomy. The tumor volumes and tumor-to-prostate ratios (TPRs) of dominant intraprostatic foci of uptake were determined using semiautomatic segmentation (applying SUVmax percentage [SUV%] thresholds of SUV30%-SUV70%), adaptive segmentation (using adaptive segmentation percentage [A%] thresholds of A30%-A70%), and manual contouring. The histopathologic tumor volume (TV-Histo) served as the reference standard. The significance of differences between TV-Histo and PET-based tumor volume were assessed using the paired-sample Wilcoxon signed-rank test. The Spearman correlation coefficient was used to establish the strength of the association between TV-Histo and PET-derived tumor volume. Results: Median TV-Histo was 2.03 cm3 (interquartile ratio [IQR], 1.16-3.36 cm3), and median TPR was 10.16%. The adaptive method with an A40% threshold most closely determined the tumor volume, with a median difference of +0.19 (IQR, -0.71 to +2.01) and a median relative difference of +7.6%. The paired-sample Wilcoxon test showed no significant difference in PET-derived tumor volume and TV-Histo using A40%, A50%, SUV40%, and SUV50% threshold segmentation algorithms (P > 0.05). For both threshold-based segmentation methods, use of higher thresholds (e.g., SUV60% or SUV70% and A50%-A70%) resulted in underestimation of tumor volumes, and use of lower thresholds (e.g., SUV30% or SUV40% and A30%) resulted in overestimation of tumor volumes relative to TV-Histo and TPR. Manual segmentation overestimated the tumor volume, with a median difference of +2.49 (IQR, 0.42-4.11) and a median relative difference of +130%. Conclusion: Segmentation of intraprostatic tumor volume and TPR with an adaptive segmentation approach most closely approximates TV-Histo. This information might be used to guide the primary treatment of men with clinically localized, high-risk prostate cancer.