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e19503 Background: The anti-B-cell maturation antigen (BCMA) antibody-drug conjugate (ADC) belantamab mafodotin is approved in the USA and EU for relapsed/refractory multiple myeloma (RRMM). Understanding treatment options and patient outcomes following ADC failure is clinically important. This study describes post-ADC treatment patterns and clinical outcomes in real-world patients with RRMM. Methods: Adult patients with MM who received an ADC and initiated ≥1 subsequent line of therapy (LOT) were included. The index date was the start of the first post-ADC LOT. Data were obtained from chart reviews at International Myeloma Foundation International Myeloma Working Group (IMF IMWG) academic sites, and US electronic health records from largely community sites (COTA and Guardian Research Network [GRN]). Patient characteristics and index regimens were summarized descriptively. Time to next treatment (TTNT) and overall survival (OS) were estimated with the Kaplan-Meier estimator. Results: The IMF IMWG cohort (n=40) had a mean age of 70.8 years, median of 7 prior LOTs and 82.5% were triple-class refractory (TCR). Overall, 85% received ADC monotherapy (70% belantamab mafodotin) and 15% combination therapy. Pre-ADC and not considering corticosteroids, patients were commonly exposed to lenalidomide (R; 100%), bortezomib (V; 92.5%), daratumumab (D) and pomalidomide (P; 90% each). Over a median follow-up of 26 months after index date, 29 unique index post-ADC regimens were reported, frequently selinexor (27.5%) and bispecific antibodies (15%). CAR T-cell therapy was administered to 5%, with 60% re-treated with a pre-ADC drug class (PI/IMiD/anti-CD38) after ADC. Median (95% CI) TTNT and OS were 10.8 (7.0–20.6) and 19.0 (13.4–25.1) months, respectively. The COTA-GRN cohort (n=39) had a mean age of 67.5 years, median of 8 prior LOTs, and 51.3% were TCR. Overall, 56% received ADC monotherapy (belantamab mafodotin) and 44% combination therapy. Pre-ADC and not considering corticosteroids, patients were commonly exposed to D and R (97.4% each), and carfilzomib, V and P (94.9% each). Over a median follow-up of 9.2 months, 32 unique index post-ADC regimens were reported, frequently selinexor (23.1%) and venetoclax (17.9%) based; 0% received CAR Ts and 54% were re-treated with a pre-ADC drug class (PI/IMiD/anti-CD38) after ADC. Median (95% CI) TTNT and OS were 4.9 (2.8–non-estimable [NE]) and 12.0 (4.9–NE) months, respectively. Conclusions: Findings highlight that most patients with heavily pretreated BCMA-ADC exposed MM were re-treated with similar classes. Academic centers used novel therapies (ie, CAR T, bispecific antibodies) more often and their patients had longer survival than those treated at community sites. However, clinical outcomes remained sub-optimal, emphasizing the unmet need for effective, accessible post-ADC treatments.

e15091 Background: Early identification of patients likely to benefit from immune checkpoint inhibitors (ICIs) remains a major challenge across solid tumors. Circulating tumor DNA (ctDNA) kinetics have emerged as a promising noninvasive biomarker, yet results across studies are heterogeneous. We conducted a systematic review and meta-analysis to evaluate the prognostic and predictive value of early ctDNA reduction in patients receiving ICIs. Methods: A systematic search of PubMed, Embase, Web of Science, and Cochrane Library was conducted from inception through March 2025 following PRISMA guidelines. Studies evaluating early ctDNA dynamics (≤8 weeks after ICI initiation) in adult patients with solid tumors were included. Primary outcomes were progression-free survival (PFS) and overall survival (OS). Secondary outcomes included objective response rate (ORR). Random-effects models were used to pool hazard ratios (HRs) and odds ratios (ORs). Heterogeneity was assessed using I² statistics, and publication bias was evaluated with funnel plots and Egger’s test. Results: A total of 27 studies encompassing 3,842 patients across lung, melanoma, breast, gastrointestinal, and genitourinary malignancies met inclusion criteria. Early ctDNA reduction (defined as ≥50–90% decline or complete clearance, study-specific) was associated with significantly improved PFS (pooled HR 0.45; 95% CI 0.38–0.53; I² = 41%) and OS (pooled HR 0.40; 95% CI 0.32–0.49; I² = 36%). Patients demonstrating early ctDNA reduction had a markedly higher ORR (pooled OR 4.92; 95% CI 3.71–6.53; I² = 29%). Subgroup analyses showed consistent benefit across tumor types and ICI regimens. Early ctDNA dynamics outperformed baseline PD-L1 expression and tumor mutational burden in predicting treatment response. No significant publication bias was detected. Conclusions: Early ctDNA kinetics are a robust, tumor-agnostic biomarker associated with improved survival and treatment response in patients receiving ICIs. These findings support the integration of ctDNA monitoring into early treatment assessment and clinical trial design. Prospective trials are warranted to validate ctDNA-guided immunotherapy strategies.

e13660 Background: We previously showed success with collection of structured data elements within the electronic health record using the minimum common oncology data elements (henceforth, mCODE tool) supported by soft-stop close visit validation (CVV) and staff support interventions in a limited cohort. Since the additional interventions are resource-intensive and difficult to apply across an entire department, we therefore implemented a department-wide roll-out supported by the least resource-intensive interventions while monitoring uptake. Methods: The mCODE tool collects five data elements: stage, disease status, performance status, intent of treatment, and intent to change therapy. The Department of Oncology providers received education on the mCODE tool and were asked to implement use at a faculty meeting; soft-stop CVV was enabled at that time. The percentage of data captured for each data element was collected from the notes of providers who did not participate in prior pilots for the 4 months post-implementation. mCODE tool usage was defined as entry of at least one data element except stage (as stage has long been a structured data element in Epic, can be entered independently of the mCODE tool, and many providers were entering stage prior to mCODE tool introduction). Results: 86 MDs and 20 APPs for a total of 106 providers were included, resulting in 14,973 visits and 8,745 unique patients. 73.6% of providers (n =78) utilized the mCODE tool. Of those who utilized the tool, median overall data capture across the four data elements was 24.0%. 22.6% of providers (n =24) achieved > 80% overall data capture and 32.1% (n =34) had over 50% overall data capture despite minimal intervention. 75.6% of MDs (n = 65) utilized the tool with a median data capture of 16.3% compared to 65% of APPs (n = 13) with a median data capture of 90.3%. Rates of data capture for individual data elements were similar. Conclusions: Use of soft-stop CVV appears to drive utilization of the mCODE tool but is insufficient to promote > 80% data capture for most providers without more intervention. Supportive interventions such as individualized assistance with incorporation into existing templates and directed communication from leadership remain necessary to promote use of structured data elements and will be implemented in sequence to understand how we achieve the target data capture ( > 80%) at scale.

9535 Background: MUM carries a poor prognosis with few effective treatments, especially for HLA-A*02:01-negative pts. While a subset of MUM pts responds to immune checkpoint inhibitors, the comparative efficacy of IPI+PD1 versus PD1 monotherapy is unclear. This study compares objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety between these regimens in MUM. Methods: MUM pts treated with PD1 or IPI+PD1 at 15 major melanoma centres (from Australia, Europe, United States and Israel) were included. Demographics, patient and disease characteristics, and clinical outcomes were examined. Univariate and multivariate (MVA) analyses were performed to identify clinical predictors of response and survival. Results: Of 412 MUM pts treated, 150 (36%) had PD1 and 262 (64%) received PD1+IPI. Compared to the PD1 group, PD1+IPI-treated pts were younger (64 vs. 70 years; p<0.001), had higher rate of elevated LDH (44% vs. 31%; p=0.037), and more frequently had prior treatment with tebentafusp (6.5% vs. 1.3%; p=0.031). Median follow-up from commencement of PD1+/-IPI was 4.9 years (95% CI 4.7 – 6.1). ORR was higher in IPI+PD1 group (18%) vs. PD1 (9%) (p=0.008), particularly in males (p=0.009), patients with liver metastases (p=0.018) and with lung metastases (p=0.011), with elevated LDH (p=0.047) and with no prior treatment with tebentafusp (p=0.007). PFS and OS at 1 and 2 years were numerically higher with IPI+PD1 (1- and 2-year PFS: 23% and 15%; 1- and 2-year OS: 63% and 39%) vs. PD1 (1- and 2-year PFS: 17% and 11%; 1- and 2-year OS: 54% and 36%), but these differences were not statistically significant (p>0.05). On MVA, adjusting for predefined variables (age, gender, ECOG PS, LDH, presence/absence of liver/lung metastases, prior treatment with tebentafusp), IPI+PD1 was associated with higher ORR (OR 2.71, 1.30 – 6.05; p=0.01) but not with PFS or OS compared to PD1. Presence of liver metastases (ORR [OR 0.28; 95% CI 0.13 - 0.64], PFS [HR 1.61; 95% CI 1.11 - 2.34], OS [HR 2.02; 95% CI 1.32 - 3.10]), ECOG PS≥2 (PFS [HR 1.82; 95% CI 1.07 - 3.10], OS [HR 2.24; 95% CI 1.25-4.01]), elevated LDH (PFS [HR 1.66; 95% CI 1.30 - 2.11], OS [HR 2.39; 95% CI 1.84-3.10]) and prior tebentafusp treatment (OS [HR 2.36; 95% CI 1.21-4.59]) were also independent predictors of response and/or survival. A higher percentage of pts experienced grade ≥3 immune-related adverse events (irAEs) in the IPI+PD1 group compared to the PD1 group (34% vs 13%, p<0.0001). Most pts ceased treatment due to progression (234, 57%), and more pts stopped due to toxicity in the IPI+PD1 vs. PD1 group (25% vs. 9%, p<0.0001). Conclusions: In pts with MUM, IPI+PD1 demonstrated a higher ORR but did not improve survival compared with PD1 alone. IPI+PD1 was more toxic, leading to early treatment discontinuation in one-quarter of pts. These findings may help guide treatment selection in MUM.

9030 Background: AI use is ubiquitous among HOT and healthcare workers, but with variable base knowledge and comfort level. Its indiscriminate use may be problematic. To address this educational gap, we developed a WS for HOT to assess their use of AI and educate them on how to employ it in MedEd and patient-centered CP based on LSP. Methods: A faculty member developed a WS on how to use AI in MedEd and CP based on LSP of analogy, contrasting cases, elaboration, generation, and question driven learning. The WS was for HOT, but faculty could join. It had 3 sections: introduction to basic concepts of AI; principles of the Health Insurance Portability and Accountability Act and protected health information; AI in MedEd; and AI in CP. Sections had real use case examples of AI, for participants to interact, ask questions, and share their personal use cases. HOT were invited to compare and generate examples during the WS, based on their educational and clinical experience and needs. Participants’ AI use and self-perceived and objective knowledge about it were assessed in a pre activity survey, a post WS survey, and a post 8 week survey to evaluate long term learning. Results: A 2 hour WS with 9 HOT and 2 faculty was completed successfully. 10 participants completed the pre WS survey, and 11 completed the post WS and the post 8 week surveys. 100% of them used generative AI tools before the WS, while 10% had prior training in AI. 90% used AI in personal life and MedEd, 70% used it in CP, and 30% in academic research. Table 1 shows participants’ self-assessed knowledge of AI, comfort level in using AI for MedEd and CP, self-assessed preparedness to implement AI in MedEd and CP, and objective knowledge. 8 weeks post WS, 91% of participants reported increased AI use in CP, leading anywhere from slight to significant decreases in time spent on documentation tasks for 91% of them. In MedEd, 73% reported increased AI use, and 82% described slight to significant improvement in the quality of time dedicated to it. 82% described the WS as extremely relevant to their daily responsibilities, and 91% reported confidence navigating ethical and privacy risks of AI in HemOnc. All participants were interested in having a similar WS in the future. Conclusions: An LSP based WS about AI increased the self-perceived and objective knowledge of HOT about using this tool in MedEd and CP. It also increased HOT comfort level, preparedness, and efficiency using AI. With the ubiquitous use of AI by HOT, ongoing education about it focused on supporting high-quality patient care should be a part of fellowship curriculum. Pre WS % Post WS % Post 8 week % Moderately/Very knowledgeable about AI 50 91 100 Comfortable using AI in MedEd 60 82 82 Prepared to implement AI in MedEd 30 91 73 Comfortable using AI in CP 40 73 82 Prepared to implement AI in CP 0 91 73 Correct answers on objective assessment 53 68 71

12007 Background: YAs with cancer, defined as those diagnosed prior to the age of 40, may experience greater symptom burden compared to those diagnosed at older ages. We evaluated the impact of an ePROM-triggered, CC-based, supportive care intervention on symptom burden in YAs with cancer. Methods: The Enhanced, Electronic Health Record-facilitated Cancer Symptom Control (E2C2) trial was a cluster-randomized, pragmatic trial (NCT03892967) that enrolled oncology patients seen at Mayo Clinic Rochester and within the Mayo Clinic Health System (sites in Minnesota and Wisconsin) between March 2019 and January 2023. Patients routinely reported the severity of six SPPADE symptoms (Sleep deficit, Pain, Physical function impairment, Anxiety, Depression, and Energy deficit/fatigue) on 11-point numerical rating scales. Symptom severity was classified as none to mild (0-3), moderate (4-6), or severe (7-10). Those with moderate or severe symptoms were offered symptom management education, while those with severe symptoms were also offered the option to work virtually with a symptom care manager. In this post hoc analysis, we examined the effects of the intervention on change in symptom scores among YAs and time to improvement to a mild/moderate level in those with at least one severe symptom. Results: Among 40,659 patients who responded to at least one survey, 2,598 were YAs and 38,061 were adults ≥ 40 years. Among YAs, 10.7%, 24.3%, and 65.1% were 18-24 years, 25-31 years, and 32-39 years, respectively. A greater proportion of YA patients were female (61.5% vs 57.0%), of a non-white race (12.4% vs 5.3%), living in an urban setting (65.7% vs 55.1%), single (36.4% vs 9.6%), on non-government insurance (78.1% vs 36.6%), employed (72.6% vs 37.4%), and had a Bachelor’s degree or greater (37.8% vs 28.3%, p < 0.001 for all). Fewer YA patients had metastatic disease compared to older patients (24.2% vs 35.2%, p < 0.001). Compared to a pre-intervention baseline, the mean change in symptom score for YA patients following the intervention demonstrated improvements in anxiety (-0.195) and depression (-0.168, p < 0.0001 for both), while physical function impairment worsened over the intervention period (0.101, p = 0.014). Compared to adults ≥ 40 years, YAs experienced greater intervention effects for management of depression ( p < 0.001), fatigue ( p = 0.01), pain ( p < 0.0001), and physical function impairment ( p < 0.0001). Among YAs with a severe symptom during the intervention period, median time to improvement to a mild/moderate level was longer for anxiety compared to those ≥ 40 years (3.5 vs 2.7 months, p = 0.009). Conclusions: Routine ePROM surveillance, coupled with CC-based symptom management, led to improvements in anxiety and depression among YAs with cancer, although, time to improvement was longer for anxiety compared to adults ≥ 40 years.

Abstract Aims We aimed to compare procedural, echocardiographic, and clinical outcomes within the first year after transcatheter aortic valve implantation (TAVI) among inhospital and subacute patients to elective patients in the COMPARE-TAVI 1 cohort. Methods and results Among 1030 patients treated with TAVI, 927 (90%) had an elective procedure, 63 (6.1%) had a subacute procedure, and 40 (3.9%) had an inhospital procedure. Procedural characteristics and outcomes were comparable. Among elective, subacute, and inhospital patients, mortality at 30 days was 15 (1.6%), 0 (0%), and 0 (0%) and at 1 year 54 (5.8%), 4 (6.3%), and 2 (5.0%). Stroke at 30 days was 28 (3.0%), 0 (0%), and 3 (7.5%) and at 1 year 42 (4.5%), 5 (7.9%), and 3 (7.5%). New pacemaker at 30 days was 119 (14%), 12 (21%), and 6 (17%) and at 1 year 130 (16%), 14 (25%), and 7 (19%). Elective, subacute, and inhospital patients with LVEF ≤40%, improved their LVEF from 33% (28–37), 33% (27–37), and 28% (22–33) before TAVI to 46% (35–60), 43% (33–52), and 42% (33–55) at 30-days, and 54% (45–62), 53% (43–61), and 49% (39–63) at 1-year. Differences between the groups were not statistically significant. Conclusion After transfemoral TAVI with balloon-expandable valves in COMPARE-TAVI 1, procedural, echocardiographic, and clinical outcomes were comparable among elective, subacute, and inhospital patients within the first year.

Abstract Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

Abstract Background T cell activation and polarization drive atherosclerosis. Among the mediators underlying T cell polarization, the epigenetic enzyme EZH2 catalyses the repressive mark H3K27me3. In humans, EZH2 is upregulated in T cells in advanced atherosclerosis, whereas its deficiency in T cells in mice limits plaque formation via an anti-inflammatory response. Emerging evidence indicates that EZH2 can also regulate lncRNAs and miRNAs by depositing H3K27me3 at their loci, repressing transcription. Purpose We hypothesize that EZH2 governs lncRNAs and miRNAs expression in T cells in the context of atherogenesis. Methods CD4+ T cells were isolated from spleens of atherosclerosis-prone T cell-specific Ezh2 (Ezh2cd4)-KO mice and WT littermates. Small RNA-seq (SMARTer® smRNA-Seq) and transcriptomic profiling (Prime-seq) were performed. Differential expression was assessed using edgeR. Selected miRNAs were validated by RT-qPCR. Putative miRNA targets were retrieved from miRTarBase (v. 8) and TargetScan, and gene ontology enrichment was performed using Metascape. Results In CD4+ T cells from Ezh2cd4-KO mice, 41 out of 2,950 mature miRNAs were differentially expressed (log2FC &gt; |0.8|, FDR &lt; 0.05), with 27 upregulated and 14 downregulated. Top upregulated miRNAs included miR-125a-5p, miR-130a-3p, miR-744-5p, miR-181a-5p, miR-181b-5p, miR-374b-5p, miR-99b, miR-3085, and miR-7049-3p. RT-qPCR confirmed that expression of miR-125a-5p, miR-181a-5p, miR-181b-5p, and miR-99b-5p were upregulated in Ezh2-deficient murine CD4+ T cells. GO enrichment analysis of downregulated genes revealed enrichment of IL-4, IL-9, IL-10, and TGF-β pathways, suggesting their relevance in T-cell function and differentiation. In human Jurkat T cells, pharmacological EZH2 inhibition using GSK126 or tazemetostat resulted only in the upregulation of miR-125a-5p and miR-99b-5p, confirming the conservation of the mechanisms in humans. Integration of our Prime-seq transcriptomics and smallRNAseq datasets with human and mouse predicted and experimentally validated targets of miR-125a-5p and miR-99b-5p identified six conserved target genes: STAT1, FAM169B, NDRG3, PSMB9, TRIB1, and RAB3IP. Conclusions Our findings indicate that Ezh2 represses miRNA expression in T cells during atherogenesis, thereby possibly promoting differentiation toward pro-atherogenic subsets while restraining anti-atherogenic transcriptional programs. Further research is needed to elucidate the underlying mechanisms. Ezh2-regulated miRNAs may represent promising targets to direct T cell plasticity to combat atherosclerosis.