Citations

Abstract Purpose To develop and implement an in‑house treatment‑management platform to improve communication, data accessibility, and task tracking across a radiation oncology department. Methods We developed Capsule, a custom software platform that centralizes patient data from the ARIA oncology information system (Varian Medical Systems, Palo Alto, United States), and integrates it with data from Outlook (Microsoft, Redmond, United States), spreadsheets, and manual inputs. Built using C#, SQL, and the .NET framework, it features a graphical interface in XAML with twelve modular tools to support workflows across a large multi‐modality department. A formal validation, feedback, and maintenance cycle was established. Its impact on workflow efficiency was evaluated using average CarePath task duration before and after implementation, supplemented by user interviews and surveys. Results The Department Schedule, Treatment Planning and On‐Treatment Whiteboard, Spreadsheet, and various workload tracking modules emerged as the most frequently used among dosimetrists surveyed.The Whiteboard module consolidates planning metadata for streamlined workflows. Workload and scheduling modules help distribute tasks fairly. The Department Schedule module centralizes daily role and contact information. The Spreadsheet module allows dosimetrists to identify a reference for unique plans and provides secure access to large exportable tabulated patient data and clinical trends. Other modules support proton down‐time replanning and special procedure physics assignment. One year after Capsule's implementation, most tasks in the external beam radiation therapy workflow experienced a reduction in average duration. Discussion Capsule streamlines workflows by integrating multiple tools into a single platform, supporting urgent scenarios, and improving task hand‐off. Its modular design allows customization to local workflows, but implementation must be guided by institutional oversight and formal quality management to ensure data security and compliance. Conclusion Capsule can provide a solution for improved workflow efficiency, communication, and interdisciplinary coordination. By democratizing access to routine and retrospective data, it supports treatment planning, scheduling, and quality improvement. Ongoing updates are essential as clinical practices evolve.

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.

Background Predictive models employing machine learning algorithms are increasingly being used in clinical decision making, and improperly calibrated models can result in systematic harm. We sought to investigate the impact of class imbalance correction, a commonly applied preprocessing step in machine learning model development, on calibration and modelled clinical decision making in a large real-world context. Methods A histogram boosted gradient classifier was trained on a highly imbalanced national dataset of >1.8 million patients undergoing surgery, to predict the risk of 90-day mortality and complications after surgery. Class imbalance correction strategies including random oversampling, synthetic minority oversampling technique, random under-sampling, and cost-sensitive learning were compared to the natural distribution ('natural'). Models were tested and compared with classification metrics, calibration plots, decision curve analysis, and simulated clinical impact analysis. Results The natural model demonstrated high performance (AUROC 0.94, 95% CI 0.94--0.95 for mortality; 0.84, 95% CI 0.84--0.85 for complications) and calibration (log loss 0.05, 95% CI 0.04--0.05 for mortality; 0.23, 95% CI 0.23--0.24 for complications). Class imbalance mitigation (CSL, ROS, RUS, and SMOTE) did not improve AUROC or AUPRC but increased recall and F1 scores at the expense of precision and accuracy. However, these methods severely compromised model calibration, leading to significant over-prediction of risks (up to a 62.8 % increase) as further evidenced by increased log loss across all mitigation techniques. Decision curve analysis and clinical scenario testing confirmed that the natural model provided the highest net benefit. Conclusion Class imbalance correction methods result in significant miscalibration, leading to possible harm whenused for clinical decision making.

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 .

TPS892 Background: Enfortumab Vedotin (EV) plus pembrolizumab (Pembro) is now first-line therapy for advanced urothelial carcinoma (UC), yielding ~30% complete response (CR) rates; nevertheless, most patients (pts) progress within 1 year and median overall survival (OS) remains < 3 years. In muscle invasive bladder cancer, local consolidation after systemic therapy improves outcomes, suggesting that residual, treatment-refractory intravesical disease drives relapse. We hypothesize that cytoreductive cystectomy/nephroureterectomy (CC/U)—with metastasis-directed therapy (MDT) as needed—can consolidate responses to EV/Pembro and extend benefit in regionally advanced or metastatic UC. CAST-AI prospectively evaluates this multimodal strategy and integrates correlative studies of exosomal Nectin-4 and circulating tumor DNA (ctDNA) from blood and urine as predictive/MRD biomarkers. Methods: CAST-AI is a phase II, decentralized single-arm trial enrolling pts with histologically confirmed UC of the bladder or upper urinary tract with ≥N1 and/or M1 disease and ECOG PS 0–2 who are potential surgical candidates (planned n = 75). Treatment: EV 1.25 mg/kg IV D1 & D8 + Pembro 200 mg IV D1 q21d, ≥4 cycles; MDT permitted any time pre-surgery. Response assessments occur q9 weeks (±4) to 18 months, then q12 weeks (±4). Surgical eligibility requires: (A) fitness for surgery; (B) complete or partial response (CR/PR) or, for select low-burden/unmeasurable disease, urologist-adjudicated candidacy; (C) all distant sites addressed; and (D) procedure in pt’s best interest. Post-CC/U maintenance EV/Pembro is encouraged per clinical discretion and guided by definitive surgical pathology results, which provide true pathologic staging often unattainable through imaging after systemic therapy. Primary endpoint: 12-month progression-free survival (PFS). Secondary endpoints: Objective response rate (ORR), CR rate, down-staging at CC/U, PFS, OS, and safety (using CTCAE). Exploratory endpoints: longitudinal exosomal Nectin-4 and ctDNA dynamics as MRD and early relapse indicators; tissue–blood–urine Nectin-4 concordance; pt-reported tolerability (using CIPN20). Key exclusions: > 20% variant histology or disallowed subtypes (e.g., micropapillary, plasmacytoid, sarcomatoid, neuroendocrine); prior chemotherapy for UC; contraindications to surgery/EV/ICI; or active uncontrolled comorbidities/infections. Status: Enrollment is open and ongoing, with 25 of 75 pts enrolled as of September 2025. The trial uses a decentralized model, allowing pts to receive EV/Pembro at their local facility, with central coordination, biospecimen shipping, and surgical evaluation at Mayo Clinic or affiliated sites. ClinicalTrials.gov: NCT06764095. Clinical trial information: NCT06764095 .

Abstract Background: Triple-negative breast cancer (TNBC) is an aggressive yet immunogenic subtype of breast cancer (BC) and the only one with FDA-approved immune checkpoint inhibitor (ICI) - pembrolizumab. Currently, PD-L1 (22C3) is the companion biomarker for predicting pembrolizumab benefit, but its utility is limited by spatial/temporal heterogeneity, assay variability, and modest correlation with treatment response. Chemokines such as CXCL9, CXCL10, and CCL5 recruit CD8+ T cells into the tumor microenvironment and have been associated with improved response to ICI, but their predictive value alongside PD-L1 remains unclear. Here, we examined the relationship between these chemokines, PD-L1, and pembrolizumab efficacy in TNBC. Methods: We analyzed 3662 TNBC tumors profiled by NGS (592, NextSeq; WES/WTS, NovaSeq; Caris Life Sciences). Immune cells were estimated using WTS deconvolution (Quantiseq). PD-L1 positivity was defined as &gt;10% CPS (PharmDx 22C3). CXCL9/CXCL10/CCL5-high (H) and -low (L) TNBC were classified by RNA expression above or below 50th percentile. Real-world median overall survival (mOS) was derived from insurance claims and calculated from start of pembrolizumab to last contact using Kaplan-Meier. Statistical significance was assessed by chi-square and Mann-Whitney U with multiple comparison adjustments (q&lt;0.05). Results: TNBC expressed higher levels of CXCL9, CXCL10, and CCL5 (N = 3662, median TPM: 5.3, 14.8, and 15.1) compared to HER2+ (N = 1344; 4.8, 10.1, 10.6) and HR+HER2- BC (N = 6097; 2.7, 6.6, 9.4), all q&lt;0.05. Moderate correlations were observed between PD-L1 CPS and each chemokine (r = 0.41, p&lt;.01). PD-L1-positive tumors had better mOS (24.3 months (m) vs 18.6 m, HR 0.75, 95% CI 0.6-0.92, p=0.007) compared to PD-L1-negative TNBC post-pembrolizumab. Among PD-L1-negative tumors, those with CXCL9-H had better mOS (26.9 m vs 15.8 m for CXCL9-L, HR 0.61, 95% CI 0.45-0.82, p=0.001) post-pembrolizumab. Among PD-L1-positive tumors, CXCL10-H and CCL5-H was associated with improved mOS (CXCL10-H: 25.7 m vs. 20.7 m for CXC10-L, p = 0.03; CCL5-H: 26.7 vs. 18.5 m for CCL5-L, p = 0.03) post-pembrolizumab. PD-L1 negative CXCL9-H, PD-L1 positive CXCL10-H and PD-L1 positive CCL5-H groups showed higher infiltration of CD8+ T cell, B cells, M1/M2 macrophages, Tregs. They also exhibited higher T cell inflamed score, IFNy score and MAPK activation score vs. CXCL9-L, CXCL10-L and CCL5-L groups (Table). Conclusions: In TNBC, a chemokine signature comprising CXCL9, CXCL10 and CCL5 refines PD-L1 based prediction of pembrolizumab benefit. Specifically, high CXCL10 or CCL5 expression in PD-L1-positive tumors, and high CXCL9 expression in PD-L1-negative tumors, were associated with improved survival post pembrolizumab and immune-rich microenvironment. These findings support the use of chemokine profiling to complement PD-L1 and enhance patient selection for ICI therapy in TNBC. Citation Format: S. Gandhi, S. Deshmukh, S. Wu, J. Xiu, G. Sledge Jr., D. Trapani, J. Leone, S. Chumsri, M. Lustberg, C. Hong, S. Yao, K. Takabe, M. Ernstoff, M. Opyrchal, P. Chalasani, C. Paulos, G. Lesinski, A. Madabhushi, S. Badve, K. Kalinsky, P. Kalinski. Chemokine signatures improve PD-L1-based prediction of pembrolizumab response in triple-negative breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-08-14.

Neuromodulation is becoming a common treatment strategy for patients with drug-resistant epilepsy who are not candidates for resective surgery. Responsive neurostimulation can effectively reduce seizure burden, however it remains unclear which neural signals are most important for triggered stimulation. Furthermore, the high-dimensional parameter space remains systematically underexamined. As more patients become candidates for neurostimulation, clinical teams will need to decide on the optimal site and stimulation program for therapeutic neuromodulation. In this review, we highlight how recent insight into the biological rhythms of epilepsy may pair with personalization protocols in the emerging field of neuropsychiatric neuromodulation. Finally, we discuss future directions for epilepsy neuromodulation, specifically how machine learning can offer clinical teams actionable feedback on neuromodulation efficacy.