Jain, Prateek

Abstract Background Diagnosis and risk stratification in rare hematologic malignancies such as myeloproliferative neoplasms (MPNs) – polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) – require expert review of longitudinal, heterogeneous clinical records. This process is cognitively demanding, inconsistently applied, and difficult to scale beyond tertiary centers. No automated phenotyping workflow currently exists for hematologic malignancies. Methods A HIPAA-compliant large language model (LLM) framework for phenotyping MPN was developed to integrate (i) rule-based retrieval of bone marrow biopsy reports, clinical notes, and structured laboratory results from the electronic health record (EHR); (ii) zero-shot extraction of diagnostic and prognostic variables from unstructured text using GPT-4 Turbo; (iii) a clinician-informed source-prioritization algorithm to reconcile conflicting multi-source data; (iv) WHO/ICC-criteria–based diagnostic classification; and (v) NCCN-based risk stratification using the conventional risk model for PV, IPSET-thrombosis for ET, and DIPSS, DIPSS-plus, and MIPSS70/MIPSS70+ v2 for MF. Patients were identified via MPN-related ICD-9/10 codes; cases met 2017 WHO criteria or had a hematologist-documented diagnosis, and controls did not. The cohort was split into a prompt-development set (n = 60) and a held-out test set (n = 450; 75 cases and 75 controls per disease). Ground truth was established by independent dual-clinician chart review with consensus adjudication. LLM performance was evaluated against the ground truth: variable-level extraction using accuracy, F1 score, and Cohen’s kappa; patient-level diagnostic classification using sensitivity, specificity, and Cohen’s kappa; and prognostic risk stratification (among confirmed cases) using accuracy, weighted F1 score, and quadratic-weighted Cohen’s kappa. Wilson 95% confidence intervals (CIs) were used for proportions and bootstrap 95% CIs with 500 resamples for F1 scores. Results The held-out test set included 450 patients (PV: 150; ET: 150; MF: 150) with pathology reports and structured laboratory results, and 172 patients (PV: 52; ET: 55; MF: 65) with clinical notes. From pathology reports, overall variable extraction accuracy and F1 score were 99% (95% CI, 98–100) and 1.00 (0.99–1.00) for PV, 100% (99–100) and 0.99 (0.96–1.00) for ET, and 100% (99–100) and 0.99 (0.97–1.00) for MF. From clinical notes, overall accuracy and F1 score were 96% (91–100) and 0.94 (0.85–1.00) for PV, 100% (100–100) and 1.00 (1.00–1.00) for ET, and 100% (99–100) and 0.98 (0.95–1.00) for MF. Diagnostic sensitivity was 100% (95% CI, 95.1–100.0) for PV, ET, and MF; specificity was 98.7% (92.8–99.8) for PV and 100% (95.1–100.0) for both ET and MF, with Cohen’s kappa of 0.99 for PV and 1.00 for ET and MF. Risk stratification accuracy was 100% with weighted F1 score of 1.00 and quadratic-weighted Cohen’s kappa of 1.00 across all three diseases. A pre-specified source-ablation analysis showed that pathology reports alone were sufficient for diagnosis (sensitivity 98.7% for PV, 100% for ET, 96.0% for MF; specificity 100% across all three subtypes) but inadequate for prognostication (accuracy 69.3% for PV, 93.3% for ET, 77.3% for MF). Adding clinical notes to pathology reports recovered full prognostic accuracy of 100% across all three diseases. Conclusions This first-in-class automated framework achieved expert-level performance for MPN diagnosis and risk stratification from real-world EHR data, establishing a foundation for scalable, standardized phenotyping in rare hematologic malignancies. Prospective, multi-site validation is warranted before clinical deployment.

4589 Background: Recent years have seen a shift in aUC management following approval of enfortumab vedotin–pembrolizumab (EV-P) and gemcitabine/cisplatin plus nivolumab (GC-NIVO) as first-line therapies. Despite improved clinical outcomes, their relative economic value remains uncertain. Herein, we conducted a cost-effectiveness analysis of current 1L regimens in aUC from a U.S. payer perspective using 2026 pricing. Methods: A partitioned survival model with three health states (progression-free [PF], progressed disease [PD], and death) was developed over a 10-year horizon from a U.S. payer perspective. Analyses focused on cisplatin-eligible patients. Survival data were reconstructed from published Kaplan–Meier curves and extrapolated using parametric survival models. Treatment dosing, schedules, and duration were modeled according to trial protocols. Patients receiving gemcitabine/cisplatin without progression were modeled to receive avelumab maintenance (GC→AVEL). Subsequent-line therapy costs were applied at incident progression, and grade ≥3 adverse event costs and disutilities were applied as one-time events. Drug acquisition costs (2026 USD) were based on average sales prices from the Centers for Medicare & Medicaid Services. Costs and quality-adjusted life years (QALYs) were discounted at 3% annually. Incremental cost-effectiveness ratios (ICERs) and net monetary benefit (NMB) were evaluated at willingness-to-pay (WTP) thresholds of $100,000, $150,000, and $200,000 per QALY. Parameter uncertainty was characterized using probabilistic sensitivity analysis. Results: In the base-case analysis, total discounted costs and QALYs were $90,269 and 1.62 for GC→AVEL, $131,836 and 2.09 for GC-NIVO, and $1,451,885 and 2.77 for EV-P. Compared with GC→AVEL, GC-NIVO gained 0.46 QALYs at an incremental cost of $41,567, resulting in an ICER of $89,501 per QALY and positive NMB across all evaluated WTP thresholds. Compared with GC→AVEL, EV-P gained 1.15 QALYs at an incremental cost of $1.36 million (ICER $1.19 million per QALY). Compared with GC-NIVO, EV-P gained 0.68 QALYs at an incremental cost of $1.32 million (ICER $1.93 million per QALY), exceeding all evaluated WTP thresholds. In a scenario analysis limiting EV-P to 10 treatment cycles, total costs decreased to $287,360, with ICERs of $172,000/QALY versus GC→AVEL and $225,000/QALY versus GC-NIVO, remaining above the $150,000/QALY threshold. Conclusions: Using updated 2026 pricing, GC-NIVO is likely to be the most cost-effective first-line regimen for cisplatin-eligible patients with aUC. EV-P offers the greatest clinical benefit but is not cost-effective at current prices. A major limitation of this study is cross-trial variability in study populations and design, limiting the validity of head-to-head economic comparisons.

703 Background: The association of circulating tumor DNA (ctDNA) reduction with treatment response has been investigated across multiple malignancies. This study aims to assess the impact of ctDNA response on survival outcomes in patients receiving enfortumab-pembrolizumab (EV-P). Methods: We identified 32 patients with advanced urothelial carcinoma who received EV-P and had ≥2 ctDNA assessments with ≥1 detectable level. Deep molecular response was defined as >2-log reduction from highest ctDNA detection. Radiographic progression was determined from radiology reports documenting progression by RECIST criteria. Kaplan Meier analyses were performed to compute Hazard Ratios (HR) with 95% confidence intervals (CI) for radiographic progression free survival (rPFS), defined as time from treatment start to radiographic progression or death and overall survival (OS) defined as time from treatment start to death were computed. Log-rank tests were performed to compare PFS and OS in patients with deep molecular response to those without response. A p-value <0.05 indicated a statistically significant association with response. Results: Thirty-two patients were included (median age 71 years; range 39–90). Median follow-up was 10.6 months. At cutoff (10/1/2025), 26 patients were alive and 6 had died. Seventeen (53%) achieved a ≥2-log ctDNA reduction (responders), while 15 (47%) did not (non-responders). Progression-free survival was significantly longer in responders (log-rank P < 0.001); median PFS was 5.9 months (95% CI 2.4–NR) in non-responders and not reached in responders (HR 0.09, 95% CI 0.02–0.44; P = 0.0026). Median overall survival was 12.7 months (95% CI 10.0–NR) in non-responders versus not reached in responders (log-rank P = 0.011; HR 0.11, 95% CI 0.01–0.88; P = 0.037). At cutoff, 94% of responders and 67% of non-responders were alive. Conclusions: Achieving a >2-log decrease in ctDNA during EV + Pembrolizumab therapy was significantly associated with improved progression free and overall survival. These findings support ctDNA kinetics as a potential early biomarker of response warranting prospective validation. Clinical outcomes by >2-log ctDNA reduction status. Endpoint > 2-log drop (n = 17 ≤ 2-log drop (n = 15) Log-rank p Median (mo) ≤ 2-log > 2-log HR (95% CI) P C-index PFS 2 events (12%) 10 events (67%) 0.0002 5.9 (2.4–NA) NR 0.09 (0.02–0.44) 0.0026 0.77 OS 1 event (6%) 6 events (40%) 0.011 12.7 (10.0–NA) NR 0.11 (0.01–0.88) 0.037 0.73