Lunde, Julianne J.

1503 Background: CAR T-cell therapy has revolutionized treatment outcomes in hematological malignancies, but has traditionally required inpatient post-infusion monitoring, which is associated with significant cost and time toxicity. Outpatient CAR T infusion and monitoring has been the standard approach at Mayo Clinic site in Rochester, MN, with demonstrated feasibility and safety (Bansal et al., ASCO 2023). We present data comparing healthcare utilization between CAR T recipients who underwent outpatient remote monitoring and those with traditional inpatient monitoring. Methods: Electronic medical records were retrospectively analyzed for 293 patients who received CAR T-cell therapy for a hematological malignancy at any of the 3 Mayo Clinic sites (MN, AZ, FL) between 2020 and 2024 . Healthcare utilization was compared between patients who received outpatient CAR T with remote patient monitoring in Rochester, MN (N = 125) and those who received inpatient CAR T in the Arizona (n = 90) and Florida (n = 78) sites. Per protocol, patients in the inpatient group underwent mandatory inpatient monitoring for 7 days, with extension per provider discretion. Data was analyzed through Chi-Square and Wilcoxon tests. P values < 0.05 were considered statistically significant. Results: There was no significant difference in baseline sex, age, ethnicity, LDH, platelets, or neutrophils among the 293 patients. Diagnoses included lymphoma (n = 175), multiple myeloma (n = 106), and B-ALL (n = 12). The most common CAR T-cell products used were axicabtagene ciloleucel (n = 138) idecabtagene vicleucel (n = 56), and ciltacabtagene autoleucel (n = 50). Median hospital days were lower in the outpatient group vs the inpatient group at 30 days (4.4 vs 13.3, P < 0.001) and 90 days (4.6 vs 13.6, P < 0.001). ICU admission occurred in 1 outpatient patient ( < 1%) vs 18 inpatient patients (11%) in the first 30 days (P < 0.001). In the first 30 days, 22% of patients in the outpatient group did not require hospitalization, while 56%, 15%, and 6% required 1, 2, and 3 hospitalizations, respectively. Similarly, only 11 (8.8%) patients in the outpatient group had ≥1 ED visit in the first 30 days compared with 32 (20%) pts in the inpatient group (P = 0.009). At 30 days, there was no difference in patient portal use, with 58% of patients using the portal at least once and a median of 1 message in both groups. Within the first 30 days, 53% and 2% of patients in the outpatient group required 1 and 2 outpatient visits, respectively, vs 29% and 2% in the inpatient group (P < 0.001). There was no difference in 30-day mortality (1.6% outpatient vs 2.4% in inpatient) between the 2 groups (P = 1.00) Conclusions: Outpatient CAR T-cell therapy monitoring was associated with significantly fewer hospital days without increased ED visits, ICU stays, portal use, or 30-day mortality. This demonstrates lower healthcare utilization for outpatient CAR-T therapy.

e13890 Background: Many oncology practices have reported continued use of telemedicine since onset of the COVID-19 pandemic. However, the future sustainability of telemedicine within oncology practices remains unclear, particularly because federal policies that enabled adoption in response to the public health emergency (PHE) have not been made permanent. Understanding similarities and differences in telemedicine utilization at high-volume oncology centers is crucial for shaping evidence-based policy that enables equitable access to oncology care across varying geographies. Methods: This is a cross-sectional, year-over-year, retrospective cohort analysis of trends in telemedicine utilization across all medical oncology clinical appointments conducted among adult patients (age >18) from January 2019 to December 2023 at Stanford Medicine Cancer Center (SM) – comprising multiple campuses in the California Bay Area – and the Mayo Clinic Comprehensive Cancer Center (MC) – a multiregional cancer practice with tertiary referral campuses in Minnesota, Florida, and Arizona, as well as community-based clinics throughout the Upper Midwest. Results: Both institutions exhibited a similar trend in telemedicine adoption over time. This was characterized by an initial surge in utilization following the PHE declaration in March 2020, followed by sustained utilization rates from 2021 to 2023. However, telemedicine use as a proportion of the overall practice differed significantly between institutions. At SM, the rate of telemedicine visits as a proportion of overall clinical practice was 60.3% (49,136/ 81,502) in 2021, 59.9% (52,247/ 87,215) in 2022, and 57.2% (55,007/ 96,163) in 2023. At MC, the proportion of telemedicine utilization was 12.8% in 2021 (23,873/186,086), 14.7% in 2022 (28,985/196,777), and 14.0% in 2023 (30,208/215,941). Deployment in the setting of new versus return visits also differed between institutions. In 2023, telemedicine accounted for 53.7% (6,440/11,998) of new and 57.7% (48,567/84,165) of return visits at SM, compared to 15.5% (3,359/21,728) and 13.8% (26,849/194,213) at MC. Additionally, while video visits were the predominant modality used to conduct telemedicine visits at both institutions from 2021 onward, in 2023 phone visits still made up 17.9% (5,394/30,208) of all telemedicine visits at MC, compared to just 5.4% (2,990/55,007) at SM. Conclusions: Stanford Medicine and Mayo Clinic exhibited a pattern of initial growth of telemedicine adoption in 2020, followed by sustained utilization from 2021-2023. We observed unique differences in the overall proportion, visit type deployment, and modality of telemedicine utilization between institutions. However, this study confirms telemedicine visits have remained a fixture of medical oncology care for many patients at these institutions since the COVID-19 pandemic.

AbstractTo address the current and long‐term unmet health needs of the growing population of non‐Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18–99). Participants came from 49 US states and included 538 Black/African‐Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population‐based SEER data (2015–2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population‐based SEER rates for indolent B‐cell (follicular and marginal zone) and T‐cell lymphomas, but were 10%–15% higher than SEER rates for aggressive B‐cell subtypes (diffuse large B‐cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.

Introduction While chimeric antigen receptor (CAR)-T cell therapy has transformed the management of hematologic malignancies, it requires frequent monitoring for acute toxicities, almost universally achieved through mandatory hospitalizations, therefore utilizing a significant amount of healthcare resources. At Mayo Clinic in Rochester, MN, our standard practice is administering CAR-T cell therapy in the outpatient setting through a multi-disciplinary hospital-based outpatient (HBO) unit and remote patient monitoring (RPM) program. Our CAR-T RPM program consists of in-home, electronic health record-integrated technology to monitor vital signs and neurologic symptoms for 30 days post CAR-T infusion. Here we report the healthcare utilization outcomes of CAR-T patients managed in the outpatient setting enrolled in the RPM program. Methods Patients undergoing FDA-approved CAR-T cell treatment in the outpatient setting and participating in the CAR-T RPM program at Mayo Clinic Rochester were included in this IRB-approved study. Patient characteristics, healthcare utilization metrics, inpatient interventions, and patient satisfaction data regarding the RPM program were reviewed. Length of stay (LOS) includes any hospitalizations for which the admission date falls within the RPM monitoring period (CAR-T cell infusion to day +30), even if the hospitalization continued past day +30. Results A total of 123 patients participated in the CAR-T RPM program and underwent treatment in the outpatient setting. Median age at CAR-T infusion was 63 years (range 22 - 83), and most patients were male (n=78, 63%). Non-Hodgkin lymphoma was the most common diagnosis (n=74, 60%), followed by multiple myeloma (n=47, 38%), ALL (n=1, 1%) and other (n=1, 1%). During the PRM monitoring period, 19 (16%) patients were managed entirely in the outpatient setting. The remaining 104 (84%) patients required at least one hospitalization, with most patients (n=70, 57%) hospitalized only once [26 (21%) patients were hospitalized twice, and 7 (6%) patients were hospitalized 3 times, and 1 (1%) patient hospitalized 4 times during the monitoring period]. When considering the first hospitalization post CAR-T infusion, the median LOS was 6 days (range 2 - 47). When considering all hospitalizations post CAR-T, the median LOS was 8 days (range 2 - 47). Only 7 (6%) patients required an ICU stay, with a mean ICU stay of 0.2 days (standard deviation 0.9). Cytokine release syndrome (CRS) was noted in 92 (75%) of patients at a median of 3 days (range 0 - 18) post CAR-T infusion. All patients with CRS received tocilizumab, at a median of 4 days post CAR-T infusion. Steroids for CRS were administered in 63 (68%) of these patients. Neurotoxicity was reported in 45 (37%) patients at a median of 7 days (range 1 - 19) post CAR-T infusion. During the RPM monitoring period, patients were seen in our HBO unit with a median of 18 outpatient visits (range 4 - 30). Patient survey data, obtained at the end of the RPM monitoring period, were available from 37 patients. The majority of patients felt that the RPM program helped them feel comfortable managing their health at home, were able to reach a team member, and receive an appropriate response promptly. The majority of patients felt comfortable using the RPM equipment and interacting with providers virtually. Overall, 83% of patients were satisfied with the RPM program and 6% were neither satisfied nor dissatisfied. When asked about the reason for disappointment, technical difficulties/issues with the devices were the themes mentioned by the few patients (11%) who were unsatisfied with the RPM program. Conclusion: Despite the complexities and frequent monitoring associated with CAR-T cell therapy, outpatient CAR-T cell treatment is a feasible model of care. As the standard practice at our institution, the CAR-T RPM program was part of the management of nearly all patients undergoing an FDA-approved CAR-T product in the outpatient setting. RPM in the acute setting post CAR-T infusion is a well-received practice initiative by the majority of patients, including a high level of comfort utilizing the RPM equipment and virtual interaction with the RPM providers.

Electronic health record (EHR) systems collate patient data, and the integration and standardization of documents through Health Information Exchange (HIE) play a pivotal role in refining patient management. Although the clinical implications of AI in EHR systems have been extensively analyzed, its application in HIE as a crucial source of patient data is less explored. Addressing this gap, our systematic review delves into utilizing AI models in HIE, gauging their predictive prowess and potential limitations. Employing databases such as Scopus, CINAHL, Google Scholar, PubMed/Medline, and Web of Science and adhering to the PRISMA guidelines, we unearthed 1021 publications. Of these, 11 were shortlisted for the final analysis. A noticeable preference for machine learning models in prognosticating clinical results, notably in oncology and cardiac failures, was evident. The metrics displayed AUC values ranging between 61% and 99.91%. Sensitivity metrics spanned from 12% to 96.50%, specificity from 76.30% to 98.80%, positive predictive values varied from 83.70% to 94.10%, and negative predictive values between 94.10% and 99.10%. Despite variations in specific metrics, AI models drawing on HIE data unfailingly showcased commendable predictive proficiency in clinical verdicts, emphasizing the transformative potential of melding AI with HIE. However, variations in sensitivity highlight underlying challenges. As healthcare’s path becomes more enmeshed with AI, a well-rounded, enlightened approach is pivotal to guarantee the delivery of trustworthy and effective AI-augmented healthcare solutions.

Abstract Background: To address the current and long-term unmet health needs of the growing population of patients diagnosed with non-Hodgkin lymphoma (NHL) and NHL survivors, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/) with recruitment at eight centers (Cornell University, Emory University, Mayo Clinic, MD Anderson, University of Iowa, University of Miami, University of Rochester, and Washington University). Here we report on the first two years of enrollment. Methods: All patients ≥18 years with NHL (exclusive of chronic lymphocytic leukemia) newly diagnosed within 183 days of enrollment are eligible. LEO reviews all pathology diagnoses; annotates and harmonizes all cases with clinical, epidemiologic, pathology and treatment data; builds a NHL tumor bank that includes an H&E slide, a formalin-fixed, paraffin-embedded tissue sample and extracted tumor DNA and RNA; collects peripheral blood and banks DNA, serum, plasma and buffy coat in a central biorepository; and prospectively follows patients regularly to ascertain disease progression/relapse, retreatment, transformation, second cancers, survival, updated exposures, and patient-reported outcomes. We examined the demographics, clinical characteristics, and NHL subtypes for patients enrolled in the first two years (2015-2017) in LEO Cohort and compared these characteristics to population-based registry data from the United States Surveillance, Epidemiology, and End Results (SEER) Program for 2011-2015. We also examined baseline body mass index (BMI), comorbidities and quality of life (QOL) measured with the Functional Assessment of Cancer Therapy - General (FACT-G) scores (0-100 scale) overall and by NHL subtype that were collected in LEO but not available in SEER or any other large, prospective US NHL cohort. Results: From 2015-2017, LEO enrolled 3244 NHL patients across 47 states (Figure) with a median age at diagnosis of 62 years (range, 18-94 years) and 55.9% male. Based on self-identified race/ethnicity, 85% of the participants were White, 7.4% were Black/African American, 2.6% were Asian, and 3.5% other or more than one race; 9.9% were Hispanic (regardless of race). The most common subtypes were diffuse large B-cell (DLBCL, 33.9%), follicular (FL, 22.2%), mantle cell (MCL, 9.3%), marginal zone (MZL, 8.3%), T-cell (TCL, 10.9%), and all other NHL subtypes (other NHL, 15.3%). These distributions were all within 5% of SEER data, except that 6.8% of participant in LEO were in the age 80+ years group compared to 18.5% in SEER (Table). The overall prevalence of self-reported comorbidities at enrollment was 13.5% for heart disease (range, 12.1% for FL to 16.6% for MCL), 8.8% for diabetes (range, 7.1% for FL to 9.8% for DLBCL), 4.6% for osteoporosis (range, 3.0% for MCL to 6.3% for MZL), and 5.9% for autoimmune disease (range, 2.0% for MCL to 12.6% for MZL). The median BMI was 27.9 kg/m2 (range, 26.7 kg/m2 for TCL to 28.3 kg/m2 for MZL). A total of 2151 participants completed the FACT-G with a median score of 78.7 (range, 75.9 for TCL to 83.3 for MZL). Complete IPI data were available on 2296 participants: 40.4% IPI 0-1, 32.7% IPI 2, 18.3% IPI 3, 8.7% IPI 4-5. Overall, 73.7% of participants were initially treated with systemic therapy (range, 40.0% for MZL and 91.8% for DLBCL); 14.5% were initially managed with observation (range, 1.4% DLBCL and 31.8% for FL); and 2.0% were initially manage with radiotherapy (range, 0.2% for MCL and 3.8% for DLBCL). Outcomes are being prospectively collected. Conclusions: LEO is a large and diverse cohort of newly diagnosed NHL patients and the first two years of enrollment reflects the broader United States NHL population. Enrollment is ongoing. This unique resource will enable examination of the interactions among a broad array of clinical and molecular factors and their impact on multiple outcomes, to improve prognostication, identify new approaches to improve outcomes and survivorship, and facilitate clinical trials using this infrastructure. Disclosures Flowers: Acerta: Research Funding; Pharmacyclics/ Janssen: Consultancy; OptumRx: Consultancy; Janssen Pharmaceutical: Research Funding; V Foundation: Research Funding; Burroughs Wellcome Fund: Research Funding; Spectrum: Consultancy; Eastern Cooperative Oncology Group: Research Funding; Abbvie: Consultancy, Research Funding; Bayer: Consultancy; Millennium/Takeda: Research Funding; Abbvie: Research Funding; Celgene: Research Funding; Gilead: Consultancy; BeiGene: Research Funding; Karyopharm: Consultancy; Denovo Biopharma: Consultancy; Genentech/Roche: Consultancy; Gilead: Research Funding; Genentech/Roche: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Pharmacyclics: Research Funding. Nastoupil:TG Therappeutics: Research Funding; Merck: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Research Funding; Spectrum: Honoraria; Gilead: Honoraria; Genentech: Honoraria, Research Funding; Karus: Research Funding; Novartis: Honoraria; Juno: Honoraria. Kahl:Acerta: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Juno: Consultancy; CTI: Consultancy; ADC Therapeutics: Consultancy; Gilead: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Abbvie: Consultancy. Casulo:Celgene: Research Funding; Gilead: Honoraria. Friedberg:Bayer: Honoraria. Lossos:Affimed: Research Funding. Martin:Seattle Genetics: Consultancy; Kite: Consultancy; Janssen: Consultancy; Gilead: Consultancy; Bayer: Consultancy; AstraZeneca: Consultancy. Leonard:Bayer: Consultancy; Celgene: Consultancy; Biotest: Consultancy; United Therapeutics: Consultancy; BMS: Consultancy; MEI Pharma: Consultancy; Juno: Consultancy; Sutro: Consultancy; Karyopharm: Consultancy; ADC Therapeutics: Consultancy; Pfizer: Consultancy; AstraZeneca: Consultancy; Gilead: Consultancy; Genentech/Roche: Consultancy; Novartis: Consultancy. Bernal-Mizrachi:Kodikaz Therapeutic Solutions: Consultancy, Equity Ownership; Takeda Pharmaceutical Company: Research Funding. Maurer:Morphosys: Research Funding; Nanostring: Research Funding; Celgene: Research Funding. Cerhan:Nanostring: Research Funding; Jannsen: Other: Scientific Advisory Board; Celgene: Research Funding.

Abstract Abstract 1563 Intro: Optimal treatment for non-follicular low grade B-cell lymphoma (NFLGL) is not well defined. Clinical trial design for these subtypes would be enhanced by further understanding of early presentation and management. A large prospective observational study was used to identify presenting clinical features, describe patterns of care and compare the prognostic utility of International Prognostic Index (IPI) and the Follicular Lymphoma International Prognostic Index (FLIPI). Methods: The University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) is a prospective, longitudinal observational study designed to collect information on patterns of care and outcomes for patients with newly diagnosed lymphoma. Patients seen at the Mayo Clinic, Rochester MN and the University of Iowa within 9 months of their initial diagnosis of lymphoma are offered enrollment. Baseline patient reported data, clinical data and initial management are collected using a standard protocol and a central pathology review is performed. After enrollment, patients are actively followed for events (disease progression, retreatment, and death) and disease related comorbidities. This analysis includes 198 patients diagnosed with extranodal marginal zone (EMZL), 22 with nodal marginal zone (NMZL), 47 with splenic marginal zone (SMZL), 48 with lymphoplasmacytic lymphoma (LPL), as well as 67 patients with unclassifiable low-grade B-cell lymphoma (B-NOS). Results: 382 newly diagnosed NFLGBL patients were enrolled in the MER from 2002–2009. The median age at enrollment was 63 years (range 22–95). 52% were male. The most common types of initial therapy after diagnosis were observation (41 %), alkylator- based chemotherapy +/− rituximab (R) (17%), radiation therapy alone (15%) and R monotherapy (13%). At median follow-up of 60 months (range 1–121), 51 patients were deceased and 155 had an event. The clinical characteristics that comprise the IPI and FLIPI were similar across the subtypes. Approximately half of the cases presented at low risk (55% IPI; 48% FLIPI). A majority had a normal LDH (81%), limited nodal involvement (91% had ≤ 4 groups), normal hemoglobin (71% ≥12 g/dL), good performance status (95% 0–1), and advanced stage (57% stages III-IV). There were notable differences among the NFLGBL subtypes. Patients with SMZL and LPL presented with high risk FLIPI of 3–5 (49% and 46% respectively) and high to high-intermediate IPI of 3–5 (21% and 13%). Abnormal LDH and anemia (< 12 g/dL) were more frequent in patients with SMZL (40%; 56%) and LPL (25%; 62%). EMZL presented with lower stages (70% stage I-II) and NMZL presented with increased nodal involvement (38% >4 sites). SMZL had the highest rates of surgical resection (21%) and EMZL was more frequently treated with radiation therapy (25%). LPL (30%) and NMZL (32%) more commonly received alkylator based chemotherapy +/− R. While both IPI and FLIPI differentiated outcome in these patients, FLIPI had higher c-statistics than IPI for both EFS (0.583 vs 0.568) and OS (0.685 vs 0.661), respectively. Conclusions: This large prospective collection of data on NFLGBL patients presenting to academic medical centers provides a modern picture of presentation and management patterns useful to investigators designing clinical trials. FLIPI may have more prognostic utility than IPI in this group of patients. Disclosures: Ansell: Seattle Genetics, Inc.: Research Funding.