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Abstract Background New postoperative atrial fibrillation (POAF) occurs in about 40% after cardiac surgery. Mineralocorticoid receptor antagonists (MRA) are known to reduce chronic atrial fibrillation (AF) development and burden. We examined the impact of preoperative MRA use on POAF and also examine the atrial cell type impacted by MRA treatment during cold cardiac preservation. Methods Retrospective study of 19,042 patients who underwent cardiac surgery at Mayo Clinic in Minnesota, and performed 1:3 propensity matching to obtain 298 patients on preoperative MRA matched to 894 who were not. We also separately matched patients using preoperative diuretics. Single-nuclei RNA sequencing (snRNA-seq) examined MRA’s effects on different atrial cell types in canrenone (water soluble MRA) treated human donor hearts undergoing cold preservation followed by ex-vivo reperfusion and compared gene expression to the atria of patients with AF. Results Propensity matched preoperative MRA group had less new onset POAF (19.8% vs 31.5%, P<0.001). To account for the possibility that preoperative diuretic use and volume reduction may impact POAF, we propensity matched 298 preop diuretic users that included MRA use to another 894 patients who used a non-MRA diuretic preoperatively. Those who used preoperative MRA similarly had a lower incidence of POAF (19.8% vs 33.2%, P<0.001). No survival difference was present between the propensity matched groups that used preoperative diuretics (P=0.079). Preoperative MRA use also reduced the development of paroxysmal and chronic AF at 6 years of follow up. From our snRNA-seq data, we identified a subpopulation of atrial cardiomyocytes (CM2) that had high MR expression where canrenone suppressed the increase in MR target gene expression associated with cold preservation-reperfusion. These MR targets were conversely elevated in patients with chronic AF. Canrenone also suppressed other cardiac preservation associated genes that show elevated expression in atrial macrophages and pericytes from chronic AF atria. Conclusions Our studies show that preoperative MRA use is associated with 40% reduction in POAF as well as lowering long standing AF development by about 41%. Our cold cadiac preservation-reperfusion model showed that canrenone reduced expression of MR target genes associated with chronic AF, particular in cardiomyocytes with important roles in electrical conduction. Clinical Perspective What is New? This study shows that preoperative use of mineralocorticoid receptors antagonists (MRA) is associated with a reduced incidence of new onset perioperative atrial fibrillation after cardiac surgery utilizing cardiopulmonary bypass. We show that preoperative MRA use is associated with a lower incidence of developing more chronic paroxymal or sustained atrial fibrillation. Addition of canrenone, a clinically utilized water soluble MRA, to cardioplegia solution used during cardiac preservation can attenuate atrial inflammatory reponses and reduce signaling through molecular pathways that promote atrial fibrillation. What are the clinical implications? Perioperative use of MRAs may be considered to reduce early postoperative atrial fibrillation as well as lowering the risk of developing more chronic atrial arrhythmias. These findings support pursuing a clinical trial to determine the impact of MRA use on atrial arrhythmias following cardiac surgery in the setting of cardiopulmonary bypass with cold cardiac preservation.

Background Although intravenous thrombolysis (IVT) is safe and effective in populations with general stroke, its impact on cervical artery dissection–related acute ischemic stroke (CeAD‐AIS) remains unclear. This retrospective study used the National Inpatient Sample to compare outcomes in patients with CeAD‐AIS treated with and without IVT. Methods We included adult patients with concurrent CeAD and AIS diagnoses ( International Classification of Diseases, Tenth Revision [ ICD‐10 ], codes) hospitalized from 2016 to 2019. The primary outcome was home discharge; safety outcomes included inpatient death and intracerebral hemorrhage. We performed survey‐weighted multivariable logistic regressions comparing IVT versus no IVT, followed by interaction analyses to examine effect modifications based on age, medical history, stroke severity, carotid artery involvement, and endovascular treatment. Results Between 2016 and 2019, 1360 (12.1%) of 11 285 patients with CeAD‐AIS received IVT. IVT‐treated patients had higher median National Institutes of Health Stroke Scale scores (median [interquartile range], 8 [4–17] versus 3 [1–11]; P <0.001). Adjusted analyses showed IVT was associated with higher odds of home discharge (adjusted odds ratio [OR], 1.40 [95% CI, 1.01–1.92]; P =0.042), but not with inpatient death (adjusted OR, 1.29 [95% CI, 0.76–2.20]; P =0.347) or intracerebral hemorrhage (adjusted OR, 0.69 [95% CI, 0.32–1.48]; P =0.341). Stroke severity ( P for interaction=0.001) and carotid artery involvement ( P for interaction=0.021) significantly modified IVT's effect on home discharge, with IVT being associated with an increased likelihood of home discharge in patients with moderate to severe strokes (National Institutes of Health Stroke Scale score >4) and carotid artery involvement. Conclusions IVT improves the likelihood of home discharge in patients with CeAD‐AIS without increasing the risk of inpatient death or intracerebral hemorrhage.

261 Background: Clinicians use next-generation sequencing (NGS) to tailor targeted treatments for PCa patients. However, the results are often available in unstructured formats and are saturated with technical jargon, making them inaccessible for patients. Therefore, we aimed to assess the efficacy of LLMs to accurately extract genomic characteristics from unstructured reports and generate patient-friendly summaries for ease of variant interpretation in PCa patients. Methods: This retrospective study included patients with PCa who underwent NGS from 2023-2024. The GPT4 model was utilized using structured zero-shot prompts to extract genomic characteristics from unstructured reports in a non-decomposed manner. Prompt development was conducted iteratively using a 2% random sample of the dataset. Genomic characteristics ascertained by LLM were assessed against held out vendor-curated test dataset for evaluation. Performance was assessed using weighted evaluation metrics (precision, recall, and F1-score). Additionally, the extracted variables were organized using rule-based criterion and presented as a separate prompt to GPT4 to generate summaries for interpretation at the level of each biologically relevant variant. Mean Flesch-Kincaid scores and Vocd-D statistic with standard deviations were computed to assess readability and lexical diversity of LLM-generated variant interpretation summaries. Results: A total of 331 patients (370 NGS reports) were included in the study. Evaluation on the held-out test dataset (Table) showed that the weighted average precision ranged from 80% for extracting tumor mutational burden to 100% for extracting the CtDNA fraction from unstructured reports. The weighted average recall ranged from 85% for extracting CtDNA tumor fraction to 99% for ascertaining variant/alteration. The weighted average F1-scores varied from 0.83 for extracting tumor mutational burden to 1.0 for extracting specimen site from NGS reports. The mean Flesch-Kincaid score was 8.29 ± 1 indicating average/standard readability ease. The mean Vocd-D statistic was 7.55 ± 1 indicating focused summaries, however, with limited lexical diversity. Conclusions: This study suggests that large language models can effectively extract genomic characteristics from unstructured reports and can potentially improve genomic literacy among prostate cancer patients by providing easy-to-interpret variant summaries. However, targeted prompting may be required to increase lexical diversity for improved engagement. Performance across different genomic characteristics. Category Precision Recall F1-Score Altered gene 0.86 0.97 0.89 Variant/alteration type 0.98 0.99 0.98 Variant allele fraction 0.96 0.96 0.96 Test name/type 1 0.99 1 Specimen site 1 0.99 1 Tumor mutational burden 0.8 0.93 0.83 CtDNA tumor fraction 1 0.85 0.92 MSI status 0.99 0.97 0.98

454 Background: Limited data exist on outcomes in mRCC patients with major venous involvement (MVI). Assessment of impact of a given variable on prognosis in cancer patients is challenging given competing causes of death (PMID: 25417239). This analysis aims to estimate cancer prognosis in mRCC patients with MVI, considering death from competing causes. Methods: Data from the Surveillance Epidemiology and End Results (SEER) database (2010-2020) were analyzed for survival and mortality in mRCC patients with MVI. 5-year (y) overall survival (OS) and 5-y probability of cancer death were calculated using the actuarial method in SEER*Stat 8.4.4, reported as percentages with 95% confidence intervals (CI). Results were based on the site of MVI (renal vein, inferior vena cava [IVC]) and stratified by age (<65, >65 years), gender (male, female), and race/ethnicity (Non-Hispanic [NH] White, NH Black, NH Asian/Pacific Islander [API], Hispanic). Results: A total of 89047 mRCC patients were included in our analysis of whom 10785 (12%) had major venous involvement (MVI). Overall, patients who experienced MVI had worse prognosis as compared to those who did not have MVI (5-y OS: 53.2% vs 84.4% and 5-y cancer death: 38.6% vs 8.2% respectively). Among cohort with MVI, prognosis was poor with IVC involvement as compared to involvement of renal vein (5-y OS: 36% vs 57%; 5-y cancer death: 56% vs 35% respectively). Patients who had the worst prognosis with MVI included older adults (>65 y) (5-y OS: 47.8%; 5-y cancer death: 40.8%) and NH Black (5-y OS: 41.5%; 5-y cancer death: 49.8%) (Table). Conclusions: Prognosis in mRCC with MVI, especially with IVC involvement, was poor, particularly for older adults (>65 y) and NH Black patients. Further research is needed for better prognostication and risk stratification to improve outcomes for high-risk patients. Subgroup No MVI MVI N 5-year OS (%), 95% CI 5-year Cancer death (%), 95% CI N 5-year OS (%), 95% CI 5-year Cancer death (%), 95% CI Overall population 78,262 84.4 (84.1-84.7) 8.2 (8.0-8.4) 10,785 53.2 (52.0-54.3) 38.6 (37.5-39.7) Age <65 y 49,217 89.0 (88.6-89.2) 6.5 (6.3-6.8) 5,897 57.5 (56.0-59.0) 36.8 (35.4-38.3) >65 y 29,045 77.0 (76.1-77.2) 10.9 (10.5-11.4) 4,888 47.8 (46.0-49.5) 40.8 (39.2-42.4) Gender Male 49,221 83.0 (82.7-83.5) 8.9 (8.6-9.2) 7,503 53.2 (51.8-54.6) 38.3 (37.0-39.6) Female 29,041 86.5 (86.0-86.9) 7.0 (6.7-7.4) 3,282 53.0 (51.0-55.0) 39.4 (37.4-41.3) Race/ethnicity NH White 49,520 84.0 (83.7-84.4) 8.3 (8.0-8.5) 7,182 53.5 (52.1-54.8) 38.0 (36.7-39.3) NH Black 8,878 82.0 (81.0-82.9) 8.1 (7.5-8.8) 685 41.5 (37.1-45.9) 49.8 (45.4-54.1) NH API 4,747 86.0 (85.1-87.4) 8.5 (7.6-9.4) 713 52.9 (48.2-57.3) 39.9 (35.5-44.1) Hispanic (All Races) 13,826 86.5 (85.8-87.2) 7.9 (7.4-8.4) 2,014 56.2 (53.4-58.8) 36.7 (34.1-39.2) N: number of cases; OS: overall survival; CI: confidence interval; NH: Non-Hispanic; API: Asian/Pacific Islander; MVI: major venous involvement.

270 Background: Inconsistent reporting of subgroup data across clinical trials makes interpretation and application of the evidence from trials challenging. We conducted a living systematic review to summarize evidence for American Society of Clinical Oncology (ASCO) guidelines for management of metastatic castration resistant prostate cancer (mCRPC). Here, we provide an overview of reporting patterns of subgroup data across mCRPC trials. Methods: MEDLINE and EMBASE were systematically searched from each database's inception through September 20 th , 2024, to identify phase II/III/IV randomized clinical trials assessing the efficacy and safety of treatment options in mCRPC. For outcomes of overall survival (OS) and progression free survival (PFS), data from the subgroup analyses was collected and compared across trials to assess heterogeneity in the reporting of subgroups. Results: This analysis included 141 trials (phase II: 83; phase III: 56; phase IV: 2). OS was reported by 113 (80%) trials; 32 (28%) reported OS by any subgroups with 95 unique subgroup categories. PFS was reported by 110 (78%) trials; 23 (21%) reported PFS by any subgroups with 63 unique subgroup categories. Even among consistently reported subgroups, such as age, ECOG performance status, race, geographical area, and Gleason score, considerable heterogeneity in different subgroup levels/thresholds was observed across trials. Top ten most commonly reported subgroups are summarized (Table). Conclusions: Lack of consistent reporting for subgroup analysis in mCRPC trials preclude meaningful conclusions about clinically relevant subgroup and synthesizing evidence for clinical guidelines. A standardized framework for consistent reporting of subgroup data across trials can help inform clinical practice and clinical practice guidelines. OS PFS Number of trials 113 110 Reporting subgroup analysis – N (%) 32 (28) 23 (21) Commonly reported subgroups – (N) Age (26)ECOG-PS (26)LDH (21)PSA (18)Geographic area (15)Alkaline phosphatase (14)Visceral disease (14)Gleason score (9)Race (9)Brief pain inventory level (8) Age (21) ECOG-PS (19)PSA (18)LDH (14)Geographic area (13)Visceral disease (11)Gleason score (10)Alkaline phosphatase (9)Bone metastasis (9)Disease location (9) Age – (N) <65 (14); ≥65 (9); ≤68 (1); ≥69 (1); <70 (5); ≥70 (5); ≤74 (4); 65-75 (5); ≤ 71 (1); >71 (1); ≥75 (11); >Median (1); <Median (1) <65 (12); 65-74 (6); ≥65 (6); <70 (5); ≥70 (5); <75 (4); ≥75 (10); 76-80 (1); >80 (1) ECOG-PS – (N) 0 (15); 0-1 (11), 1 (11); 1-2 (5); 2 (12) 0 (15); 0-1 (5), 1 (12); 1-2 (2); 2 (6) Race – (N) White (9)Non-white (6)African American/black (2)Asian (2) White (8)Non-white (5)African American/black (2)Asian (4) Geographic Area – (N) Europe (8)North America (14)United States (1)Australia (1)Asia (2) Europe (11)North America (13)United States (1)Australia (1)Asia (2)North and South America (2) Gleason Score – (N) 2-6 (1); 7 (1); 8 (1); <8 (8); ≥ 8 (8); 9-10 (1) <8 (10); ≥ 8 (10)

520 Background: The annual incidence of renal cancer is 0.02% among the general United States population. End stage renal disease (ESRD) and exposure to dialysis are thought to be the primary drivers of increased risk of renal cancer in renal transplant patients rather than immunosuppression. This has been evidenced by how the incidence of RCC in heart transplant recipients is no different than the normal population. In this study, we aim to characterize RCC incidence among kidney transplant patients (usually exposed to ESRD/dialysis) versus other solid organ transplant patients (usually unexposed to ESRD/dialysis). Methods: We used CPT codes to search for patients who had received a solid organ transplant (kidney, liver, heart, lung, pancreas) at all Mayo Clinic sites from 1/1/2018 to 1/1/2024. Within this cohort, we identified those who had been diagnosed with kidney cancer after initiating dialysis or receiving a transplant, and retrospectively extracted data related to demographics, cancer diagnosis, and transplant details. Results: We identified 10873 patients who had received a solid organ transplant (Table 1). Of these, 178 (1.76%) were diagnosed with kidney cancer after either starting dialysis or receiving a transplant. These 178 patients were of median age 56 years at time of cancer diagnosis (STD 12), 71% male, 70% white, 20% black, 4.5% Asian, 2.8% American Native. Of 5792 patients who had received a kidney transplant (with or without another solid organ transplant), 172 (2.97%) were diagnosed with kidney cancer after having started dialysis or receiving a kidney transplant. Of these 172, 156 (91%) were exposed to dialysis (107 primarily hemodialysis and 48 peritoneal). Of 4392 patients who had received a solid organ transplant other than kidney (liver, heart, lung, and/or pancreas), 6 (0.14%) were diagnosed with kidney cancer after having received a kidney transplant. Of these 6, none underwent dialysis. Conclusions: Patients with kidney transplants are at increased risk of kidney cancer compared to patients with non-kidney solid organ transplants (2.97% vs 0.14%). This supports prior evidence showing ESRD plays a significant role in the pathogenesis of kidney cancer. Patients who received solid organ transplants at Mayo Clinic from 2018-2024 and were subsequently diagnosed with kidney cancer. n % With RCC after TXP 178 1.7587% Cancer Diagnosis after Kidney HD/TXP 172 2.9696% Cancer Diagnosis after Other TXP 6 0.1386% Patients who received solid organ transplants at Mayo Clinic from 2018-2024 n % Unique Patients 10121 100% Kidney Transplant 5792 57.23% Alone 5088 50.27% &Liver 332 3.28% &Heart 119 1.18% &Lung 8 0.08% &Pancreas 245 2.42% Non-kidney Transplant (Liver, Heart, Lung, or Pancreas) 4329 42.77% TXP: Transplant, HD: Hemodialysis.

745 Background: The combination of EV-P therapy has recently been approved as first-line (1L) therapy for patients with LA/mUC based on the results of the EV-302 trial. Herein, we report the updated results from a cohort of patients with LA/mUC who received EV-P in real world clinical setting. Methods: This retrospective study included patients with LA/mUC (07/2022-08/2024) at the Mayo Clinic who completed at least one cycle of EV-P. The best overall response (BOR) was evaluated using radiographic imaging and was adjudicated as complete response (CR), partial response (PR), stable disease (SD), mixed response (MR), or progressive disease (PD). The median progression-free survival (PFS), defined as the time from treatment initiation to disease progression or death, was estimated using the Kaplan-Meier method. Patients who had not experienced disease progression by their last follow-up were censored for the PFS analysis. Results: A total of 120 patients were included; 79 (65.8%) were males, 41 (34.1%) females, 109 (91%) White, and 119 (99%) were non-Hispanic/Latino. The median age was 72 years (IQR: 65-77). Of these, only 22 (18.3%) had locally advanced disease while the remaining had mUC; 62 (51.6%) had lower tract urothelial carcinoma (LUTC), 36 (30%) had upper tract urothelial carcinoma (UTUC). The median follow-up time was 7.1 months (IQR: 4.93-9.26). In terms of BOR, 56 patients (46.6%) experienced PR, 34 (28.3%) CR, 12 (10%) PD, 7 (5.8%) MR, and 8 (6.6%) experienced SD. 3 (2.5%) patients were not evaluable. The BOR across subgroups, LA and mUC, including LUTC and UTUC, is summarized in the table. Among the responders, the median number of treatment cycles to first response was 3 (IQR: 2.25–4). Within the follow-up, 28 patients (23.3%) experienced eventual radiographic disease progression; death was observed in 25 patients (20.8%). The median PFS was 12.7 months (95% CI: 9.8-NE), and OS was 25.1 months (16.3-NE). Conclusions: In real world setting, the combination of EV-P in LA/mUC demonstrated clinical efficacy compatible with the findings from the EV-302 trial. Our results showed comparable efficacy with EV-P in both UTUC and LUTC, highlighting it's broad therapeutic potential. However, clinical data at longer follow-up is required to fully evaluate overall survival and the durability of response. mUC LA Overall LUTC UTUC Total patients 98 62 36 22 BOR CR 23 (23.4%) 13 (20.9%) 10 (28.5%) 11 (50%) PR 49 (52.6%) 31 (50%) 18 (50%) 7 (31.8%) SD 6 (6.4%) 2 (3.2%) 4 (11.4%) 2 (9.0%) PD 10 (10.7%) 9 (15.5%) 1 (2.8%) 2 (9.0%) MR 7 (7.5%) 5 (8.6%) 2 (5.7%) 0 (0%)

134 Background: Prostate cancer patients with visceral metastases at diagnosis are often treated using one-size-fits-all approach. For example, CHAARTED criteria treats any visceral metastasis as high volume. Therefore, we aimed to assess overall survival (OS) by site of visceral involvement in patients with metastatic PCa. Methods: Surveillance, Epidemiology, and End Results (SEER) database (2010-2021) was queried to obtain case listing data on metastatic PCa patients from 17 registries. The patients were categorized into three groups based on visceral metastasis at diagnosis: lung metastasis, liver metastasis, and others. Kaplan-Meier survival analysis was performed to estimate median OS with 95% confidence interval (CI). Log-rank test was conducted to assess if survival was significantly different among the groups. Cox proportional hazard regression analysis was performed to assess the magnitude of difference among the groups. P-value <0.05 established statistical significance. Results: This analysis included 21,007 metastatic PCa patients (lung: n=319; liver: n=123; brain: 107; bone: 20538). Metastatic PCa population with lung metastasis exhibited a median OS of 60 months (95% CI: 48-72) compared to 24 months (95% CI: 12-36) in population with liver metastases and to 36 months (95% CI: 36-36) in population with other metastases. The difference in OS among the groups was statistically significant (p < 0.001). Compared to population with lung metastasis, those with liver (HR: 1.91; 95% CI: 1.41-2.57) but not those with other metastases (1.16; 0.97-1.39) had significantly worse OS adjusting for Gleason score, PSA and race (Table). Conclusions: In metastatic PCa, patients with lung-only metastasis have significantly better overall survival and should be considered differently in prognostication to liver metastases. Consideration of site of visceral metastasis is critical for treatment intensification decisions. Limitations of this analysis include lack of accounting for confounding relationships at individual patient level. Variable Hazard Ratio (95% CI) Metastases (Lung) REFERENCE Metastases (Liver) 1.91 (1.41-2.57) Metastases (Other) 1.16 (0.97-1.39) Gleason score≥8 REFERENCE Gleason score <8 0.68 (0.64 -0.72) PSA - ng/dL 1.01 (1.00 – 1.01) Race (White) REFERENCE Race (Black) 0.99 (0.94 – 1.05) Race (Asian or Pacific Islander) 0.70 (0.64 – 0.76)

132 Background: Distant metastasis at the time of prostate cancer (PCa) diagnosis is associated with increased morbidity and mortality. This study aimed to assess the impact of sociodemographic characteristics on distant metastasis at the time of PCa diagnosis. Methods: The Surveillance Epidemiology and End Results (SEER) database (2000-2021), including PCa patients from 17 registries, was queried. Patients with late-stage diagnosis (LSD) were defined as those who were initially diagnosed with stage IV disease, indicating distant metastasis. Sociodemographic predictors included race, ethnicity, age, marital status, residential status, and median household income. Multicollinearity was assessed using variance inflation factors (VIF). Univariable logistic regression was performed to identify significant predictors of LSD, which were further analyzed in multivariable logistic regression using a maximum likelihood estimation approach. Odds ratios with 95% confidence intervals (CI) were computed with a p-value of <0.05 indicating a statistically significant association. Results: Of the 1,089,736 PCa patients diagnosed, 64,983 (6%) had an LSD. The majority were white (80%), non-Hispanic/Latino (HL) (91%), aged ≥65 years (60%), married (75%), residents in metropolitan areas (88%), and had an annual house income of ≥$70,000 (70%). Multivariable logistic regression identified Black (OR: 1.24; 95%CI: 1.22-1.27), Asian or Pacific Islander (1.35; 1.30-1.40), and American Indian/Alaska Native (1.70; 1.53-1.89) to have higher odds of LSD compared to White patients (Table). In addition, HL ethnicity compared to non-HL (OR: 1.45; 95% CI: 1.42-1.49), age ≥65 compared to <65 (1.68; 1.65-1.71), unmarried status compared to married (1.88; 1.85-1.91), residency in non-metropolitan areas compared to metropolitan (1.10; 1.07-1.12), and household income <$70,000 compared to ≥$70,000 (1.03; 1.01-1.05) had a significant association with LSD. Conclusions: Older, non-White (Black, Asian/Pacific Islander, American Indian/Alaska Native), Hispanic/Latino, unmarried men, residents of non-metropolitan areas, or those with lower annual household incomes have higher odds of late-stage diagnosis. Interventions targeting early detection in these at-risk groups may improve prostate cancer outcomes in the US. Variable Odds Ratio (95% CI) p-value Race (Black vs White) 1.24 (1.22-1.27) <0.01 Race (Asian or Pacific Islander vs White) 1.35 (1.31-1.40) <0.01 Race (American Indian/Alaska Native vs White) 1.70 (1.53-1.89) <0.01 Ethnicity (Hispanic/Latino vs non-/Hispanic/Latino) 1.45 (1.42-1.49) <0.01 Age (≥65 vs <65) 1.68 (1.65-1.71) <0.01 Marital status (unmarried vs married) 1.88 (1.85-1.91) <0.01 Residence status (non-metropolitan vs metropolitan) 1.10 (1.07-1.12) <0.01 Household income (<$70,000 vs ≥$70,000) 1.03 (1.01-1.05) <0.01