Citations

207 Background: CAR-T & bispecific antibodies (BsAb) for large B-cell lymphoma offer deep responses, but have unique toxicities requiring close monitoring. Different practice settings have varied strategies for managing these toxicities, leading to increased costs, healthcare resource use, & reduced quality of life. With no direct comparison, rationale for therapy selection may vary. This study explores provider choices, sequencing strategies & access barriers. Methods: A survey of US-based Hematologists was conducted on practice demographics, therapy availability, preferences, & barriers in LBCL. Responses were analyzed across clinical scenarios. Results: Responses were received from 45 physicians. Availability of CAR-T & BsAb varied with 75% prescribing both, & only BsAb being available at 9% of providers’ centers. There was a strong preference for CAR-T over BsAb—higher among academic vs. nonacademic providers (96% vs. 78%; p = 0.03) & at CAR-T vs. non-CAR-T centers (100% vs. 72%; p = 0.001). Even at BsAb-only centers, preference leaned toward CAR-T, though notably lower compared to CAR-T centers. Among centers without either, 86% preferred CAR-T. Practice volume had no impact. Reasons for favoring CAR-T included perceived better outcomes (55%), shorter treatment (26%), center choice (19%), more experience (48%), & curative potential (21%). BsAb selection was driven by CAR-T unavailability & logistical barriers (distance to specialized center, insurance delays, referral complexity, manufacturing time, & hospitalization needs). Axi-cel was preferred by 69% ( p = 0.0001) vs. other CAR-T for third-line or later due to experience with use, response rates, center choice, & logistical ease. Liso-cel (26%) & Tisa-cel (2%) were chosen for perceived favorable toxicity over Axi-cel. Axi-cel was also preferred second-line vs. Liso-cel (73% vs. 24%; p < 0.0001) for similar reasons. Among BsAb, Epcoritamab was favored by 56% for administration ease (subcutaneous), experience, & center preference; Glofitamab by 42% for shorter duration, experience, & center preference. There was no difference by academic vs nonacademic practice & volume for both CAR-T & BsAb. In patients with prior non-CAR-T anti-CD19 therapy, providers chose CD19 CAR-T over CD20 BsAb (80% vs. 18%; p < 0.0001). For relapse after second-line CAR-T, 78% providers preferred BsAb as the next line over other options ( p < 0.0001) due to more favorable response rates, toxicity profile, & experience with use. Providers prioritized response rates, survival, & toxicity profile in their treatment decisions. Logistics, duration, frequency, & cost were less important. There were no differences based on practice setting & CAR-T experience. Conclusions: Despite higher preference for CAR-T due to perceived superior outcomes, access barriers exist. Efforts to streamline referral pathways, logistics, & expand availability are crucial to improve outcomes.

1652 Background: Tarlatamab is a bispecific T-cell engager targeting DLL3 that has shown promise as a therapy in small cell lung cancer. Administering tarlatamab requires careful consideration of immune-related adverse events (AE), including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Prescribing information recommends patients to be monitored for 22-24 hours in an appropriate healthcare setting for cycle 1 (C1), days 1 and 8. At Mayo Clinic in Rochester MN (MCR), tarlatamab is initially administered in a hospital-based outpatient (HBO) setting utilizing an innovative remote patient monitoring system (RPM). In this study, we describe our RPM process and patient outcomes thus far. Methods: We retrospectively reviewed records of patients treated with tarlatamab from August through December 2024. All patients received tarlatamab in the HBO setting and were enrolled into RPM for C1, days 1–10. Patients attended daily HBO visits on days 1–3 and 8–10 of C1 and were required to stay within 30 minutes of the hospital with a 24-hour caregiver for 48 hours following infusion days in C1-2. Data on patient characteristics, frequency of RPM alerts, escalations, rate of CRS & ICANS, and need for hospitalizations were reported using descriptive metrics. Results: As part of RPM, patients are provided with a kit containing preconnected Bluetooth-enabled devices to measure vital signs (VS), including blood pressure (BP), heart rate (HR), temperature (T), and pulse oximetry (SpO2). The kit also includes a cellular-enabled tablet for electronic ICANS questionnaires, which upload directly into our electronic medical record system. Patients are required to log VS four times daily, monitored in real-time by a centralized virtual RPM nursing (RN) team. Embedded decision trees trigger alerts, prompting the RN team to contact patients and follow care pathways for escalations as needed. Among the 16 patients treated, the median age was 68 years, and the median ECOG PS was 1. During the 10-day RPM period, a total of 2,233 VS entries were recorded. Of these, 88% (14/16) of patients had alerts triggered, with a median of 2 alerts per patient. Alerts were mostly for out-of-range systolic BP (56%), HR (56%), and T (25%), with none for SpO2. The RN team escalated alerts in 50% (8/16) of the patients. Overall, 38% (6/16) of patients were managed entirely in the HBO setting. Among the 63% hospitalized, 56% had CRS limited to grade (G) 2, and 31% had ICANS limited to G3. Two patients were hospitalized for other indications. The mean length of stay was 2.6 days, with no ICU admissions. Conclusions: Our experience shows that frequent monitoring required with tarlatamab can be safely and effectively executed in an outpatient setting with the utilization of an RPM system. It can potentially minimize the burden of hospitalizations for patients and the healthcare system.

e13622 Background: Chimeric antigen receptor T-cell (CAR-T) therapy has revolutionized treatment of hematologic malignancies; however, severe toxicities like cytokine release syndrome (CRS) remain a limitation to broader utilization. Using a large dataset of patients treated with CAR-T, we developed a machine learning (ML) model leveraging multi-model patient characteristics to predict the risk of CRS onset with clinically meaningful lead times. Methods: A prospectively maintained dataset of CAR-T patients treated at Mayo Clinic was used. Baseline disease/patients characteristics, labs, ECG, echocardiogram, and vital signs (including data from remote patient monitoring program) were collected. A 24-hour rolling window was used to generate daily averages, maximum, minimum, and deltas for each parameter. ECG and echocardiogram data were forward-imputed; vital signs and labs were not imputed. Each day-post-infusion served as a potential event (CRS onset vs. no CRS). A gradient boosting classifier was trained and tested on a subset of patients (n = 351) using 1,000 bootstrap iterations, evaluating 24-, 48-, and 72-hour lead times. Shapley-based feature importance guided simplification to an 11-feature model, externally validated on an independent cohort (n = 51). Models’ performance assessed using the area under the receiver operating characteristic curve (AUC). Results: A total of 402 patients treated with CAR-T were examined. Median age was 64 years and 36% were female. Primary diagnosis was B-cell lymphoma (n = 240) or multiple myeloma (n = 162). A total of 226,332 vital sign measurements and 372,871 lab values, as well as ECG and echocardiogram data, were collected for 30 days post-infusion. Overall, 79.8% of patients experienced CRS within 30 days. The full ML model demonstrated AUCs of 0.90 (95% CI 0.86–0.93), 0.83 (95% CI 0.77–0.88), and 0.82 (95% CI 0.77–0.87) for 24-, 48-, and 72-hour predictions of CRS, respectively. Including “day of CRS onset post CAR-T” as a feature improved the 72-hour AUC to 0.87 (95% CI 0.83–0.90). A model restricted to vital signs alone showed AUCs of 0.88, 0.75, and 0.71 for 24-, 48-, and 72-hour horizons. An 11-feature model—focusing on temperature, blood pressure, fibrinogen, CRP, serum sodium level, QRS interval, and lymphocyte counts—maintained high accuracy at 24 hours (AUC 0.90, 95% CI 0.86–0.93) and was validated externally using an independent dataset with an AUC of 0.92. Conclusions: Our ML model provides a reliable approach for predicting if/when CRS will occur, with up to three days of lead time before clinical manifestation, offering an opportunity for proactive management. The robust performance of a parsimonious 11-feature model supports practical adoption across clinical settings and real-time risk stratification to enhance patient safety. Prospective validation and integration into clinical workflows will be critical to translating these findings into practice.

e13893 Background: For individuals with CNS tumors who have experience difficulties with in-person (IP) evaluations due to disease-related neurologic disability or the costs associated with travel, telehealth (TH) offers a convenient and timely alternative for accessing specialized neuro-oncology care. We report our institution’s experience with telehealth utilization in neuro-oncology. Methods: We conducted a retrospective review of patients who had at least one neuro-oncology telehealth visit between August 2021 and May 2024 at Mayo Clinic in Rochester, Minnesota. Reasons for visits, outcomes of appointments, acute care utilization following visits was reviewed. Results: A total of 660 patients who had at least one TH visit between August 2021 and May 2024 were included in the analysis. Median age was 56 (range 20-98), 49% were female, and 92% were white. Most patients resided in the US Midwest (84%), followed by the South (8%), West (5%), Northeast (1%), and US Territories (< 1%). Less than two percent were international patients. The most common primary visit diagnosis was glioblastoma (GBM, 26%), followed by astrocytoma, IDH-mutant (17%), meningioma (17%), oligodendroglioma, IDH-mutant, 1p/19q codeleted (7%). Of 6657 visits reviewed, 2745 (41%) were conducted via TH. Telehealth visits served various purposes, including consultation for newly diagnosed tumors or abnormal MRIs (n = 26), second opinion for an established tumor diagnosis (n = 119), discussion about clinical trial participation (n = 108), tumor-related treatment discussions (n = 719), chemotherapy education (n = 161), new symptom assessment (n = 117), symptom management (n = 366), and tumor surveillance (n = 1694). Outcomes from telehealth visits included enrollment in clinical trials (n = 28), proceeding with tumor-directed surgery (n = 46), initiation of radiation therapy (n = 88), starting or changing systemic therapy (n = 377), continuing existing systemic therapy (n = 932), transition to supportive care (n = 45), tumor diagnostic workup (n = 28), continuation of tumor surveillance (n = 1254). Acute care utilization, defined as an emergency department visit or hospitalization within one month of an appointment, was the same following telehealth visits compared to in-person visits (6.9% for IP vs 5% for TH, p = 0.507). Conclusions: Our findings demonstrate that telehealth can effectively support all aspects of neuro-oncology care, ranging from initial diagnosis discussions to systemic therapy management and transitions to supportive care. Telehealth offers a convenient and accessible method of care delivery option for patients faced with neurologic illness. Additionally, THs do not lead to increased acute care utilization compared to IP evaluations.

9024 Background: Comprehensive hematology education during fellowship is essential for delivering high-quality healthcare. Variability in individual learning experiences can lead to trainee dissatisfaction and suboptimal clinical acumen. Fellowship programs must strive for a well-rounded and equitable educational experience for all fellows to prepare them for real-world practice in the increasingly dynamic field of hematology. Methods: Hematology fellows (n=30) at Mayo Clinic (Rochester) were invited to complete a survey about the inpatient Fellow Hematology Curriculum (FHC) during 2021-2022. Responses were recorded in a five-point Likert scale and free-text. Using the initial results, we implemented a structured inpatient hematology curriculum starting in 2022 and conducted a post-implementation survey in Spring 2024 to assess its success and sustainability. Results: The initial survey was completed by twenty fellows, with a response rate of 66%. All respondents agreed that the FHC could be improved. Only 45% agreed that structured education is adequately paired with clinical duties. In the open-ended responses, a structured curriculum covering a set list of topics was the most common recommendation given to improve the FHC. This prompted a longitudinal QI initiative to implement standardized rotation-specific lectures created by fellows and distributed to faculty and fellows prior to the associated 4-week rotations. Twelve fellows (40%) completed the post-implementation survey. Summary of key responses are shown in table 1. Although there remained high variability among consultants regarding their engagement in education, significant improvements were noted. Agreement that the curriculum has well-defined objectives for each rotation increased from 25% to 58%. Additionally, 83% of fellows agreed that structured education was effectively paired with clinical duties, up from 45%. Open-ended responses highlighted variability in consultants' utilization of the curriculum but reflected overall satisfaction. Conclusions: The need for a well-structured FHC was identified as a gap in equitable hematology education. This was addressed through a fellow led longitudinal QI project generating easily accessible educational material relevant to weekly themes on inpatient hematology services. The introduction of a structured and clinically relevant curriculum was well-received. Summary of survey responses. Pre-implementation Post-implementation Statement Agreed or strongly agreed (%) Agreed of strongly agreed (%) I know what topics and to what extent I’m expected to learn 25 67 The FHC has well-defined objectives for each rotation 25 55 There is high variability among consultants with engagement in education 95 75 Structured education is paired with clinical duties 45 83 I can easily locate lectures given by hematology consultants 5 42

9021 Background: Home call is an expected trainee responsibility in many hematology-oncology (HO) training programs although the specific duties and frequency vary. Home call is associated with sleep deprivation and burnout . The Accreditation Council for Graduate Medical Education (ACGME) outlines that home call should not prevent adequate rest or personal time and that the clinical time spent must be counted toward duty hours. However, little is known about the educational value or impact of home call. We sought to analyze the volume, perceived value, and effects of oncology home call on HO fellows. Methods: We completed a review of the pager log of the outpatient/after hours oncology pager (OP) at a single 2059 bed tertiary medical center from 1/1/23-12/31/24. The HO fellow carries the OP afterhours and on weekends except for 7am-12pm on Saturday/Sunday. The pager receives all consult calls from the emergency department and inpatient teams requesting verbal communication (in addition to the electronic order), critical results, and outpatient patient calls on matters related to oncology (hematology not included). Patient calls are not triaged and are routed through the hospital operator directly to the OP. Overnight home call is maximum 3 times per week without a post call day. An optional survey was distributed to fellows in May 2024 to assess fellows’ experiences with the OP using a 5-point Likert scale and free response. Results: There were 80,672 and 87,605 oncology patient visits in 2023 and 2024 respectively at the analyzed institution. The OP received a total of 7,239 pages over the analyzed period. Fellows received a mean of 5.8 pages per weeknight call shift and 8.8 pages per weekend call shift. The survey response rate was 19/33 (42%) HO fellows. Respondents were 58% male and included first (42%), second (26%), and third year (32%) fellows. 89% of respondents reported that most pages overnight were from outpatients and 0 respondents felt that answering patient calls required a physician. Most fellows (79%) did not report educational value from holding the OP and 63% of fellows felt that holding the OP negatively impacted their performance at work the next day. For nights that received more than 3 calls, 95% fellows reported feeling not well rested. In addition, a majority of negative impact on their wellness including anxiety and inability to exercise or socialize when holding the OP. Conclusions: The results from our single-institution study indicate that home call could represent a major opportunity to improve the wellness of trainees without negatively impacting their education. More research is needed to understand what the primary contributors are for the negative experiences and perceptions while developing sustainable systems and approaches for efficiently handling oncology pager traffic.

7075 Background: Hepatosplenic T-cell lymphoma (HSTCL) is a rare, aggressive peripheral T-cell lymphoma arising primarily from γδ T-cells. It carries a poor prognosis and resists conventional chemotherapy. Most reports on HSTCL are case-based. This study comprehensively analyzes a large cohort, evaluating treatment strategies and survival outcomes. Methods: This retrospective study included patients (pts) with pathologically confirmed HSTCL diagnosed between 2000-2024, consecutively seen at Mayo Clinic MN. Clinical, pathological, genomic, and treatment-related data were extracted when available. Descriptive statistics were used to summarize baseline characteristics. Time-to-event analyses, including Kaplan-Meier estimates, median overall survival (OS), and survival time estimates were conducted from the date of diagnosis. Results: A total of 20 patients with newly diagnosed HSTCL were included, with a median age of 57 years (range: 35-71). The cohort was predominantly male (70%) and non-Hispanic (93%). Molecular data was available for five patients, revealing abnormalities in STAT5B, MLL3 deletion, TP53, EZH2, TERT, and NF1 E291D . The median follow-up was 27.6 months (m) with a median OS of 17.6 m (95% CI: 11.2 - NA). First-line treatment was anthracycline-based in 68% of pts and non-anthracycline-based in 32%, with higher response rates in the latter group (50% vs.83%). Although non-anthracycline regimens showed a trend toward improved 3-year OS (100% vs. 29%) the difference was not statistically significant (p = 0.16). Achieving a complete response to first-line therapy was also associated with a trend towards a better 3-year OS compared to refractory disease (80% vs. 50%, p = 0.17). Most pts (79%) underwent hematopoietic stem cell transplant (HSCT), primarily allogeneic, with only one receiving autologous HSCT. First-line therapy before HSCT was evenly distributed between anthracycline (55%) and non-anthracycline (45%) regimens. HSCT recipients had significantly higher 3-year OS than non-recipients (83% vs. 33%, p = 0.017). Notably, the patient with a TP53 mutation has remained in remission for over a year post-allogeneic HSCT. Conclusions: HSTCL predominantly affects younger pts, with nearly half dying within a year. Allogeneic HSCT, rarely used in other NHL subtypes, improved survival. Non-anthracycline regimens and achieving CR trended toward better outcomes. Our study, leveraging a sizable cohort, highlights the need for targeted research and novel therapies to improve HSTCL management. Summary of survival outcomes in HSTCL. Characteristics Median OS (y) 3-Year OS (95% CI) 1.48 [0.93- NA] 46% [0.26 - 0.81] Transplant Transplant NA [NA - NA] 83% [0.58 - 1.00] No Transplant 1.02 [0.93 - NA] 33% [0.07 - 1.00] Treatment Anthracycline Based 1.02 [0.36 - NA] 29% [0.11 - 0.73] Non-Anthracycline Based 4.61 [NA- NA] 100% [1.00 - 1.00]