Tahir, Haris Bin

e16502 Background: Accurate postoperative risk stratification in localized clear-cell renal cell carcinoma (ccRCC) informs prognosis, surveillance intensity, and eligibility for adjuvant systemic therapy. Although validated prognostic models (Leibovich 2018, SSIGN, and UISS) exist, they are inconsistently applied in routine practice due to workflow and documentation barriers. Using AI assisted tools within the electronic medical record (EMR) may enable rapid, standardized risk assessment and improve clinical use. Methods: We retrospectively analyzed 92 patients with localized ccRCC undergoing radical nephrectomy and postoperative oncology evaluation (December 2021–September 2025) across three Mayo Clinic sites. Pathology reports and oncology notes were extracted via structured SQL queries. Clinical and pathologic variables were parsed using a zero-shot GPT-4o pipeline. Gold-standard prognostic risk classification and adjuvant therapy eligibility were established by an expert oncology clinician using validated prognostic calculators and KEYNOTE-564 eligibility criteria. AI-generated outputs and novice manual abstraction by two first-year fellows were compared against expert assessment using accuracy, precision, recall, and F1 score. Leibovich and SSIGN were evaluated as three-class models (low/intermediate/high), and UISS as binary risk stratification (high vs non-high). Results: Among 92 patients with localized ccRCC (median age 64 years [range 41–78]), AI-generated outputs demonstrated near-perfect agreement with expert assessment for KEYNOTE-564 adjuvant immunotherapy eligibility (accuracy 97%, precision 100%, recall 97%, F1 score 98%). For three-class prognostic stratification, AI achieved perfect agreement for Leibovich disease-free survival risk (accuracy, precision, recall, and F1 all 100%), outperforming novice abstraction. For SSIGN, AI demonstrated strong multi-class performance (accuracy 91%, precision 91%, recall 93%, F1 score 92%), compared with novice abstraction (accuracy 92%, F1 score 90%). For binary UISS risk stratification, AI achieved 81% accuracy, precision 74%, recall 100%, and F1 score 85% showing a tendency towards false positives. Conclusions: This study demonstrates AI can use existing prognostic and systemic therapy eligibility to accurately risk stratify and identify patients eligible for adjuvant systemic immunotherapy post nephrectomy. For our next steps, we plan to develop a multimodal AI platform integrating pathologic, radiologic, and clinical data to improve prognostication for outcomes and predictive capabilities for patients who would benefit from adjuvant systemic therapy for more personalized medicine.

145 Background: Multiple trials have demonstrated addition of androgen-receptor pathway inhibitors (ARPIs) improve survival in patients with metastatic prostate cancer but there is a need to quantify cardiovascular toxicity. Understanding the nature and extent of ARPI-associated cardiovascular adverse events across disease states and toxicity grades is critical to inform treatment decisions and long-term patient safety. Methods: MEDLINE, and EMBASE were systematically searched from database inception through August 30, 2025, for phase III randomized controlled trials evaluating abiraterone, enzalutamide, apalutamide, darolutamide, orteronel in metastatic prostate cancer. Trials were included if they reported CVS toxicity. Meta-analysis using a random-effects model was performed to assess the difference of all-cause and treatment-emergent cardiovascular adverse events between ARPI+ADT and ADT alone. Summary effects were expressed as relative risk (RR) with associated 95% confidence intervals. Results: A total of 21 trials (45 references) with 25,576 patients (mCSPC: 12,537, mCRPC: 13,039) were included in this meta-analysis. Compared to ADT alone, ARPI+ADT significantly increased the risk of all cause, all grade hypertension in both mCSPC (RR 1.60, 1.22–2.10) and mCRPC (RR 1.61, 1.20–2.16) as well as grade ≥ 3 hypertension (RR 1.71, 1.17–2.48) in mCRPC setting. There was an increased risk of all-cause, all grade acute coronary syndrome (RR 2.21, 1.09–4.49) and AV nodal disease (RR 2.53, 1.18–5.43) with ARPI+ADT compared to ADT alone in mCSPC setting. There was increased risk of all cause, all grade, any cardiac events (RR 1.30, 1.10–1.54) as well as grade ≥ 3 any cardiac events (RR 1.70, 1.20–2.42) in mCRPC setting. Risk of all cause, all grade hot flashes (RR 1.47, 1.16–1.85) was also significantly increased with ARPI+ADT when compared to ADT alone. In terms of treatment-emergent adverse effects, a significant increase was observed only for pulmonary embolism with ARPI+ADT when compared to ADT alone (RR 1.66, 1.06–2.60) in mCRPC setting. Conclusions: Current evidence indicates potentially increased risk of hypertension, venous thromboembolic, and ischemic cardiac events with ARPI therapy in metastatic prostate cancer. Proactive CV risk assessment, particularly in patients with preexisting comorbidities or prolonged ARPI exposure, may optimize outcomes and minimize treatment interruptions. All cause adverse events. Adverse Event Disease State All Grade Grade ≥3 Any Cardiac Event mCSPC 0.81 (0.37–1.76) 0.88 (0.16–4.64) mCRPC 1.30 (1.10–1.54) 1.70 (1.20–2.42) Hypertension mCSPC 1.60 (1.22–2.10) 1.43 (0.82–2.52) mCRPC 1.61 (1.20–2.16) 1.71 (1.17–2.48) ACS mCSPC 2.21 (1.09–4.49) 1.77 (0.86–3.61) mCRPC – – Hot Flashes mCSPC – – mCRPC 1.47 (1.16–1.85) 1.46 (0.21–9.97)

Abstract Background Valvular heart disease (VHD) and atrial fibrillation (AF) frequently coexist, presenting complex clinical challenges despite advances in diagnostics and therapeutics. Together, they contribute substantially to cardiovascular mortality. However, epidemiological patterns vary across demographics and regions Methods Mortality data from 1999–2023 were obtained from the CDC WONDER database. Deaths attributed to VHD (ICD-10: I30-I52) with co-diagnosed AF (ICD-10: I48) among adults ≥ 45 were included. Age-adjusted mortality rates (AAMRs) per 1,000,000 population were calculated. Autoregressive integrated moving average (ARIMA) models were used to project mortality trends through 2035. Results From 1999 to 2023, there were 172,511 VHD and Afib-related deaths in adults ≥ 45. AAMRs increased until 2021, followed by a slight decline to 8.86. The overall AAPC for VHD with AF was 4.01%. AAMR increase was consistent across all age groups, highest seen in 65 + individuals. Males had consistently higher AAMRs than females. AAPC for males was 4.44% and for females 3.52%. Non- Hispanic White had the highest AAMR (10.56 in 2021), followed by Hispanics (4.19). Regionally, the West had the highest AAMR (11.27), followed by Mid-West (9.94). Non-metropolitan areas had higher AAMR 8.96 compared to metropolitan areas (AAMR: 7.59). Most VHD related deaths were reported in inpatient settings (n = 396,451) and 12% involved co-diagnosed AF. Conclusion Mortality associated with VHD and AF in the U.S population aged ≥ 45 has shown a concerning increase. Predictive models indicate this trend may persist, highlighting the need for early detection, equitable healthcare access and public health interventions tailored to high-risk populations.