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ABSTRACT Background Acute heart failure (AHF) exhibits marked heterogeneity in diastolic hemodynamics, yet comprehensive echocardiographic assessment of diastolic function (DF) and filling pressure (FP) is often infeasible. We evaluated whether artificial intelligence–enabled electrocardiography (AI-ECG) could provide scalable DF grading and FP estimation in hospitalized AHF patients. Methods We retrospectively studied adults hospitalized for AHF across Mayo Clinic sites (2013–2023) who received ≥1 dose of intravenous loop diuretic and had paired 12-lead ECG and TTE. The previously validated AI-ECG DF model was applied without retraining to generate four DF grades and a continuous FP probability. Clinical outcomes were all-cause mortality and heart failure rehospitalization. Associations with clinical severity markers and echocardiographic indices were examined. Kaplan–Meier survival analysis and adjusted multivariable Cox proportional hazards models were performed. Exploratory analyses examine the kinetics of change in FP probability and impact on mortality. Results Among 11,513 patients (median age 75 years, 39% female), AI-ECG DF grading was feasible in 100%, whereas echocardiographic DF was indeterminate in 44% of clinically eligible patients. In 2,582 patients with determinate echocardiographic DF, AI-ECG FP probability discriminated TTE Grade 2–3 dysfunction with AUC 0.85 (95% CI 0.83 – 0.86). Higher AI-ECG DF grades were associated with higher comorbidity burden, worse NYHA class, elevated NT-proBNP, higher MAGGIC scores, elevated PCWP, and more advanced structural remodeling. After multivariable adjustment, AI-ECG DF remained independently associated with mortality (hazard ratio [HR] 1.25, 95% CI 1.16–1.35 for Grade 2; HR 1.44, 95% CI 1.33–1.56 for Grade 3 versus Normal/Grade 1). Combining AI-ECG DF with MAGGIC scores yielded ordered risk gradients, with highest mortality in patients with both high MAGGIC and Grade 2–3 DF. Among patients with serial ECGs, improvement in FP probability was independently associated with lower mortality (HR 0.85, 95% CI 0.79–0.91), whereas worsening did not show a consistent adverse gradient beyond baseline DF. Conclusions In a large, geographically diverse AHF cohort, AI-ECG DF grading was universally feasible, correlated with established hemodynamic severity markers, and provided independent prognostic information beyond established risk factors, supporting its role as a pragmatic, scalable diastolic biomarker in AHF. CLINICAL PERSPECTIVE What Is New? In 11,513 hospitalized acute heart failure (HF) patients, artificial intelligence-enabled electrocardiography provided diastolic function grading in 100% of patients from a single 12-lead ECG without requiring additional clinical variables, compared with 56% feasibility for guideline-based echocardiography grading. AI-ECG diastolic function grades correlated with established marker of severity (NYHA functional class, NT-proBNP, MAGGIC risk scores, and pulmonary capillary wedge pressure) and remained independently associated with both mortality and HF rehospitalization after multivariable adjustment. Serial AI-ECG measurements identified post-discharge filling pressure trajectories, with improvement independently associated with 15% lower mortality, a first demonstration that longitudinal ECG assessment can track post-discharge hemodynamic recovery. What Are the Clinical Implications? AI-ECG transforms the universally obtained 12-lead ECG into an actionable hemodynamic biomarker that addresses the critical gap when echocardiographic diastolic function assessment is indeterminate or unavailable in acute HF patients. Despite markedly different hemodynamic severity and long-term outcomes across AI-ECG diastolic function grades, hospitalization length of stay did not differ, suggesting advanced diastolic dysfunction represents occult risk not easily recognized during routine acute care and highlighting the need for improved post-discharge risk stratification. The continuous filling pressure probability metric enables longitudinal monitoring of post-discharge hemodynamic status using serial routine ECGs, potentially identifying patients requiring intensified follow-up or specialist referral.

Key Points In a cohort of children, 79% of families with kidney cysts had a monogenic diagnosis. Resolved cases were more likely to have a family history of kidney cysts and unresolved cases more often had unilateral cysts. Broad genetic testing revealed genetic diversity and informed prognosis and clinical management in childhood kidney cysts. Background Pediatric kidney cysts may indicate an underlying genetic disorder, yet the full spectrum of causes remains incompletely defined. With advances in genetic testing enabling broader evaluation, this study assessed the diagnostic utility of comprehensive genetic testing in a broad pediatric cohort with kidney cysts and characterized the underlying etiological diversity. Methods This observational cohort study included patients younger than 18 years enrolled between January 2020 and June 2024 at a single tertiary center. Genetic testing used targeted multigene or custom curated exome/genome sequencing panels, with segregation analysis when available. Eligible participants had at least two cysts without family history, one cyst with positive family history, or enlarged echogenic kidneys on prenatal ultrasound; those with congenital anomalies of the kidney and urinary tract associated with cysts were excluded. Clinical presentation was categorized as symptomatic, incidental, prenatal, or family screening. Primary outcomes were diagnostic yield and distribution of pathogenic variants. Results Among 109 patients (median age 7.6 years, 53% female), genetic testing identified a definitive diagnosis in 81 of 100 tested patients (81%) from 72 families (79%; 14 disorders). PKD1 variants were most common (45%), while PKD2 accounted for 7%. Other causes included HNF1B or 17q12 deletions (13%), minor autosomal dominant polycystic kidney disease genes (11%; GANAB, NEK8, IFT140 ), monoallelic PKHD1 (3%), and biallelic PKHD1 (8%), while syndromic ciliopathy genes accounted for 5%. A positive family history of cystic kidney disease was more common among patients with a genetic diagnosis (54% versus 11%; P = 0.008). Patients without an identified genetic diagnosis more often had unilateral cysts (26% versus 4%; P = 0.53). Diagnosis by clinical symptoms was the most genetically diverse category. Conclusions Comprehensive genetic testing in pediatric kidney cysts achieved high diagnostic yield in a selected cohort and identified diverse causes beyond major autosomal dominant polycystic kidney disease/autosomal recessive polycystic kidney disease genes, supporting early evaluation to improve diagnostic accuracy, inform prognosis, and guide management, even in the absence of family history.

Abstract Introduction Left atrial-to-coronary sinus (LA-to-CS) shunting through the APTURE transcatheter shunt system aims to unload the LA while preserving the interatrial septum. This article aims to examine the 3-year health status, functional capacity, and clinical outcomes of the ALT-FLOW Early Feasibility Study (EFS). Methods Device safety, patency, and echocardiographic parameters, but also symptoms, health status, and exercise capacity were assessed in patients with left ventricular ejection fraction (LVEF) > 40% (n & 95). Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score predicted 3-year all-cause mortality was compared with observed mortality assessed by Kaplan–Meier analysis using adjudicated events. Predicted and observed HF hospitalization (HFH)-free survival rates were also compared. Results At 3 years, the safety profile remained stable with no new safety signals, and all implanted shunts remained patent. 76.3% of patients improved by at least one NYHA class, and mean KCCQ Overall Summary Scores increased by 25 points from baseline (P < .0001). The 6-min walk distance improved by an average of 39 m (P & .002). These benefits were consistent regardless of baseline pulmonary vascular resistance (PVR). Right heart echocardiographic parameters after 3 years were stable, though a reduction in TAPSE was observed, primarily in the high PVR subgroup. The observed 3-year survival was significantly higher than the MAGGIC-predicted survival (84.4% vs 70.2, respectively; P & .009), as well as the HFH-free survival (68.0% vs 24.0%, respectively; P < 0001). Conclusion In patients with HF and LVEF >40%, the APTURE LA-to-CS shunting confirmed an acceptable safety profile with stable right heart parameters and sustained improvements in symptoms, quality of life, and functional capacity at 3 years. Observed survival and HFH were superior to MAGGIC predictions.

46 Background: Primary results from the randomized, multicenter, open-label, phase 3 TRITON3 (NCT02975934) study demonstrated that rucaparib significantly improved radiographic progression-free survival (rPFS) vs physician’s choice of DTX or an ARPI. ECOG PS is used as a predictor of prostate cancer survival. In this post hoc analysis, we report results from the BRCA1/2 subgroup of pts stratified by ECOG PS. Methods: Pts with disease progression after 1 prior second-generation ARPI in any setting were randomized 2:1 to rucaparib 600 mg BID or physician’s choice of DTX or ARPI (abiraterone acetate or enzalutamide). Primary endpoint was rPFS by independent radiology review (IRR). Objective response rate (ORR) for pts with measurable disease and overall survival (OS) were key secondary endpoints. Crossover from physician’s choice to rucaparib was allowed after radiographic progression was confirmed by IRR. Data cutoff was August 25, 2022. Results: Of 302 pts in the BRCA1/2 population, 147 had an ECOG status of 0 (97 rucaparib; 50 physician’s choice) and 155 had ECOG 1 (104 rucaparib; 51 physician’s choice). Baseline characteristics and demographics were generally similar between arms for pts in the ECOG 0 and ECOG 1 groups. Median rPFS favored rucaparib vs physician’s choice for pts with ECOG 0 (11.4 vs 8.2 months; HR, 0.48 [95% CI, 0.30-0.76]) and ECOG 1 (10.9 vs 6.1 months; HR, 0.48 [95% CI, 0.31-0.74]) (Table). Additionally, rPFS favored rucaparib for ECOG 0 and ECOG 1 including those whose prespecified physician’s choice was ARPI or docetaxel (Table). The confirmed ORR (95% CI) of rucaparib vs physician’s choice for ECOG 0 was 54% (37%–69%) vs 16% (3%–40%); the ORR for ECOG 1 was 37% (22%–53%) vs 18% (5%–40%), respectively. Median OS was similar between arms for rucaparib or physician’s choice; median OS was 23.7 vs 21.7 months (HR, 0.91 [95% CI, 0.61–1.37]) for ECOG 0 and 21.8 vs 20.4 months (HR, 0.85 [95% CI, 0.58–1.24]) for ECOG 1. Conclusions: Rucaparib improved rPFS and ORR in pts with BRCA-mutated prostate cancer with an ECOG PS of 0 or 1. OS was similar for these groups in both arms. These data support rucaparib as a treatment option for pts with BRCA-mutated mCRPC, whether ECOG 0 or 1. Clinical trial information: NCT02975934 . Median rPFS in patients in the ECOG 0 and ECOG 1 groups. Rucaparib, n Physician’s choice, n rPFS Rucaparib, median months rPFS Physician’s choice, median months HR (95% CI) rPFS, ECOG 0 97 50 11.4 8.2 0.48 (0.30–0.76) rPFS, ECOG 1 104 51 10.9 6.1 0.48 (0.31–0.74) rPFS, physician’s choice ARPI, ECOG 0 51 24 11.2 5.6 0.42 (0.22–0.78) rPFS, physician’s choice docetaxel, ECOG 0 46 26 11.5 8.8 0.49 (0.24–0.98) rPFS, physician’s choice ARPI, ECOG 1 52 17 11.2 4.5 0.33 (0.16–0.68) rPFS, physician’s choice docetaxel, ECOG 1 52 34 10.7 7.1 0.59 (0.34–1.01)

162 Background: Clinical trial conduct in advanced prostate cancer has changed dramatically with the continued development of new imaging approaches, molecular phenotypes and genetic subtypes, prognosis assessments, and effective therapies across a range of disease states. This created a need to redefine terminology and best practices for clinical trials. Methods: We convened PCWG4, an international expert committee of multidisciplinary working groups, between 2016 and 2025 to update and expand PCWG2-3 recommendations based on emerging evidence and clinical trial data in an innovative biomarker and imaging context to provide guidance for clinical trial design, eligibility, and endpoint assessments. Results: PCWG4 redefines terminology around disease states and prior therapies in a patient-centric context, considering imaging modalities, with a particular focus on PET-defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, imaging and non-imaging-based responses. We define delay/prevent endpoints including responses by pathology, ctDNA, circulating tumor cells, and PSA declines, and specify intervals for re-assessments including imaging, biomarker assessments, and patient reported outcomes. We propose new imaging-specific rPFS criteria including guidance with serial PSMA PET/CT imaging (Table). We provide recommendations in a biomarker-based context for the indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. Conclusions: PCWG4 expands guidance on patient and tumor profiling, as well as therapy development, to include both androgen deprivation therapy sensitive and resistant settings, reflecting today’s more heterogeneous and diverse patient population to optimize outcomes. PCWG4-defined radiographic progression by imaging modality for patients with metastatic disease. Pretreatment Scan On-treatment Scan #1(≥week 8) On-treatment Scan #2 All Subsequent Scans Bone scintigraphy Comparator Comparator for subsequent scansPOD never called here POD:PCWG3 criteria (2+2 additional new lesions) POD:≤5 new lesions: PCWG3 criteria 2 new lesions confirmed≥6 new lesions CT/MRI Any measurable disease Comparator PCWG3/RECIST PCWG3/RECIST PCWG3/RECIST PSMA PET Bones, and lymph nodes and lung metastases (non-RECIST qualifying by + on PET only) Comparator POD:≤5 new lesions: 2 new lesions confirmed on a subsequent scan≥6 new lesions Same as prior Same as prior Liver and non-pulmonary viscera Comparator POD:Any single new lesion that represents disease Same as prior Same as prior

TPS898 Background: Enfortumab vedotin with pembrolizumab (EV/Pembro) is now first-line therapy for locally advanced or metastatic urothelial carcinoma (la/mUC) following the EV-302/KEYNOTE-A39 trial, which demonstrated a 67.7% response rate and prolonged survival. However, ~35% of cancers exhibited primary resistance and most responders relapse within one year, with post-EV/Pembro therapies achieving < 15% response and median survival < 3 years. We previously showed that therapeutic plasma exchange (TPE) removed soluble PD-L1 and other immune checkpoint inhibitor (ICI) blocking soluble factors from the blood and that this overcame ICI resistance. Combining TPE with EV/Pembro rechallenge may overcome acquired resistance and restore antitumor immunity. Methods: RECIPE-B1 [NCT07087860] is an open-label, randomized phase II trial enrolling 50 patients (1:1) with EV/Pembro-refractory la/mUC and ECOG 0–2. Arm A receives TPE on days 1–3 followed by EV 1.25 mg/kg IV plus pembrolizumab 200 mg IV on day 3 of each 21-day cycle for the first three cycles, then continues EV/Pembro alone from cycle 4. Arm B receives investigator’s-choice next-line standard of care (SOC) per NCCN guidelines. Tumor assessments occur at the end of cycle 4 (±28 days) and every 12 weeks thereafter; safety is monitored each cycle (CTCAE v5.0). The primary endpoint is objective response rate (ORR) by RECIST 1.1, comparing TPE + EV/pembro versus SOC. Secondary endpoints include progression-free survival, overall survival, duration of response, quality of life (EORTC QLQ-CIPN20), and safety. Correlative studies evaluate circulating and urinary tumor DNA and exosomal biomarkers (including exosomal Nectin-4) as predictors of response and resistance. The trial is open at Mayo Clinic; as of September 2025, 2 of 50 patients have been enrolled, with planned accrual of ~2 patients/month and central coordination at Mayo Clinic and affiliates. Clinical trial information: NCT07087860 .

498 Background: Radiotherapy-based metastasis-directed therapy (MDT) has emerged as a viable treatment paradigm for oligometastatic clear cell renal cell carcinoma (ccRCC). However, the optimal integration of MDT with frontline immune checkpoint inhibition (ICI) is unclear, especially in light of the M1 NED subgroup analysis of KEYNOTE-564 suggestive of a larger benefit from adjuvant pembrolizumab. Here, we sought to compare the effects of MDT with or without pembrolizumab on clinical and translational outcomes among patients with oligometastatic ccRCC enrolled on two prospective phase II trials. Methods: We undertook an exploratory cohort study of two prospective, single-arm, investigator-initiated phase II trials. The RAPPORT trial (NCT02855203) assigned 30 patients to radiotherapy-based MDT followed by pembrolizumab 200 mg Q3W for eight cycles (MDT+ICI cohort). The MD Anderson trial (NCT03575611) assigned 121 patients to serial MDT (which was almost exclusively radiotherapy-based) without systemic therapy (MDT cohort). For both trials, eligibility criteria consisted of 1 to 5 ccRCC metastatic lesions amenable to MDT. For the present analysis, the primary endpoint was progression-free survival (PFS), prospectively defined by RECIST v1.1 and analyzed using Cox regression. Peripheral blood flow cytometry obtained at baseline, end of MDT in both cohorts (after 1 cycle of ICI in the MDT+ICI cohort), and after completion of all treatment in both cohorts (3 months in the MDT alone cohort and 12 months in the MDT+ICI cohort) was compared using adjusted linear mixed effect models. Results: A total of 150 patients were included for analysis (MDT+ICI: 30; MDT: 120). Median follow-up time was 34 months (MDT+ICI: 28; MDT: 36). At enrollment, the MDT+ICI cohort had a larger number of metastases (median 3 vs 1). Adjusted for prognostic factors, median PFS was 28 months after MDT+ICI and 17 months after MDT (HR, 0.57; 95% CI: 0.31 to 0.998; P = 0.049). Induction of activated systemic CD8 + T cells (ICOS + ) was observed in both cohorts following MDT; however, this increase was greater in the MDT+ICI cohort. Moreover, there was evidence of decreased systemic CD8 + T cell immunosuppression (CD73 + ) following treatment cessation in the MDT+ICI group. Conclusions: To our knowledge, this is the largest prospective analysis of MDT for ccRCC in the ICI era. The addition of maintenance ICI to MDT may improve clinical outcomes in patients with oligometastatic ccRCC. Greater immunomodulatory signals were observed with MDT+ICI, providing a mechanistic link to the clinical benefits. The ASTROs trial (NCT06004336) randomizing patients with oligometastatic ccRCC to MDT with or without pembrolizumab has been initiated to test the hypotheses generated by the present study. Clinical trial information: NCT02855203 and NCT03575611 .

405 Background: Clinical trials are critical to advancing prostate cancer treatment, yet patient enrollment remains a major bottleneck. Despite strong interest in AI for trial matching, real-world use remains limited due to reasons such as complex infrastructure requirements. To address this, we developed a lightweight, scalable AI framework leveraging the Google Healthcare Search API—requiring minimal technical expertise—to automate trial eligibility screening. Methods: We used a pre-trained GPT-5 large language model (LLM) to decompose the eligibility criteria of 13 prostate cancer clinical trials into 269 YES/NO questions, such that for an eligible patient of a given trial, the chart review would yield YES for inclusion and NO for exclusion questions. From 348 patients enrolled in one of the trials, we built a dataset linking each eligibility question to each patient, resulting in 4,947 patient–question pairs (2,034 inclusion pairs with YES labels and 2,913 exclusion pairs with NO labels). The task was framed as binary classification. During evaluation, for each patient–question pair, the LLM extracted search phrases from the question to retrieve relevant EHR information via the Google Healthcare Search API, then used the question and retrieved information to predict YES or NO responses. Performance was measured using accuracy, precision, recall, specificity, and F1 score. Results: Across 4,947 question–patient pairs, our framework achieved 0.81 accuracy, 0.85 precision, 0.65 recall, 0.92 specificity and a F1 score of 0.74. Results for different phases of trials is reported in Table 1, which demonstrates the approach’s robustness across trial phases. Predictions for exclusion criteria were highly precise, while inclusion criteria were more challenging. Most errors were observed in criteria involving complex nested logical conditions, interpretable clinical definitions and data not explicitly measurable or recorded in the EHR (e.g., planned treatments or clinician-assessed scores). Conclusions: This work demonstrates a practical AI framework to support clinical trial matching. The system can identify complex disease states (biochemical recurrence vs radiographic metastasis), castration status (sensitive, resistant) and genomics. Future work should focus on developing human-in-the-loop supervision and improving question decomposition to reduce errors in complex eligibility criteria. Screening performance of the proposed framework across different phases of trials. Trial Phase #Patient-Question Pairs #YES/NO labels Accuracy Precision Recall Specificity F1 score I, II, I/II 4,227 Yes: 1,735 No: 2,492 0.80 0.84 0.66 0.92 0.74 III 720 Yes: 299 No: 421 0.82 0.90 0.63 0.95 0.74 All 4,947 Yes: 2,034 No: 2,913 0.81 0.85 0.65 0.92 0.74 #YES/NO labels: The number of patient-question pairs that are labeled YES/NO among total patient-question pairs of the same row.

PURPOSE The continuous development of new imaging approaches, molecular phenotyping, genetic subtypes, prognosis assessments, and effective therapies across a range of disease states has created a need to redefine terminology and best practices for clinical trial conduct in patients with advanced prostate cancer. Methods We convened an international expert committee of diverse working groups, the Prostate Cancer Working Group 4 (PCWG4), between 2016 and 2025. Our objective was to formulate updated criteria based on emerging evidence and clinical trial data in a biomarker context to provide guidance for clinical trial design, eligibility, and end point assessments for patients with advanced prostate cancer. RESULTS PCWG4 redefines terminology around the disease state and previous therapies in a patient-centric context and terminology focused on androgen pathway modulation. We consider imaging, with a particular focus on positron emission tomography (PET)–defined disease. New recommendations are provided for disease state terminology, defining eligibility criteria, response and delay/prevent end points, intervals for reassessments including imaging, and patient-reported outcome determination. We provide recommendations in a biomarker-based context of use for the intended indication, reflective of patient benefit for specific interventions. We emphasize the need for development of validated PET imaging and molecular and phenotypic criteria as well as trial designs to appropriately risk stratify patients, predict and assess benefit, and measure post-treatment outcomes reliably in a trial framework. CONCLUSION PCWG4 updates recommendations on patient and tumor characterization, therapy development, and imaging criteria and extends guidance into earlier androgen pathway modulator–naïve/sensitive disease states to reflect an evolving, heterogeneous, and diverse patient population to optimize treatment benefits for all patients.