Johnston, Patrick B.

Abstract Background Primary central nervous system lymphoma (PCNSL) is a rare but aggressive non-Hodgkin lymphoma with limited prospective data to guide optimal therapy. This study evaluates real-world treatment patterns and survival outcomes using a large national cohort. Methods We analyzed data from the National Cancer Database (NCDB) for patients diagnosed with PCNSL between 2004 and 2020. Baseline demographics and treatment characteristics were analyzed using descriptive statistics. Survival outcomes were estimated using the Kaplan-Meier method and compared using log-rank tests. Multivariable Cox proportional hazards models were constructed to identify independent predictors of overall survival (OS). Results A total of 14,450 patients with PCNSL were included; 14,439 had first-line treatment data available, and 13,390 had survival data. Median age at diagnosis was 67 years (range 18-90), 49.2% were female, and 6.6% were African American. Chemotherapy alone was the modality of treatment for 81.6% (n=11,787), 12.2% (n=1,769) received chemoradiation, 3.8% (n=545) received chemotherapy and underwent autologous stem cell transplant (ASCT) but no radiation, and 2.4% (n=348) received radiation only. The median follow-up time was 73.5 months (95% CI 71.4-75.6), and the median OS for the group was 17.4 months (95% CI 16.2-18.6). Survival differed significantly by age group (median OS: <65 yrs, 46.1 months [95% CI 41.7 -50.6]; 65-79 yrs, 12.5 months [95% CI 11.2-13.7]; ≥80 yrs, 3.2 months [95% CI 2.9-3.5]; p<0.001), by year of diagnosis (median OS: 2004-2009, 11.0 months [95% CI 9.9-12.1]; 2010-2015, 20.0 months [95% CI 17.4-22.6], 2016-2020, 29.7 months [95% CI 26.0-33.4]; p<0.001), and by frontline treatment strategy (p<0.001). Patients treated with chemotherapy followed by ASCT had the longest median OS (not reached), while those receiving radiation alone had the poorest outcomes with a median OS of 3.9 months (95% CI 3.2-4.7); chemoradiation patients had a median OS of 31.8 months (95% CI 27.5-36.1), and chemotherapy only patients had a median OS of 13.9 months (95% CI 12.7-15.1)(p<0.001). African American patients had an inferior outcome with a median OS of 10.2 months [95% CI 7.2-13.1], compared to “other” races with a median OS of 36.9 months [95% CI 27.6-46.1] (p<0.001), although this is more similar to the median outcome for white patients (17.0 months [95% CI 15.8-18.3]). Treatment at an academic center (25.7 vs 11.0 months) and a high case-volume center (defined as >median number of cases per facility) (18.6 vs 10.5 months), and lower Charlson-Deyo comorbidity scores (CDS) (defined as CDS 0-1) (21.7 vs 6.8 months) were also associated with superior OS (p<0.001). In multivariable analysis, increasing age ( 65-79 y.o HR 1.60 [1.52-1.1.68], ≥80 y.o HR 2.95 [2.75-3.17]), CDS≥2 (HR 1.36 [1.28-1.44]), and African American race (HR 1.12 [1.02-1.24]) were adverse predictors of OS (all p<0.001), while treatment strategy (ASCT [HR 0.17], chemoradiation [HR 0.53], chemotherapy only [HR 0.68] compared to radiation alone), more recent year of diagnosis (2010-2015 [HR 0.81], 2016-2020 [0.70]), and treatment at an academic center [HR 0.81] remained predictors of superior OS (all p<0.001). Conclusion In this large national cohort of patients with PCNSL, treatment with chemotherapy followed by ASCT was associated with the most favorable survival outcomes. Patients treated with chemoradiation or multi-agent chemotherapy also demonstrated improved survival compared to those receiving radiation monotherapy or single-agent chemotherapy alone, respectively. Age, comorbidities, race, and treatment at academic centers were also significant independent predictors of OS. These findings highlight substantial disparities in outcomes and underscore the importance of optimizing treatment strategies, improving access to high-intensity therapies, and supporting timely referral to academic or high case-volume centers, particularly for younger and medically fit patients.

Abstract Secondary central nervous system lymphoma (SCNSL) is defined as the diagnosis of CNS lymphoma diagnosed concurrently with systemic lymphoma or after prior treatment. Due to the poor prognosis associated with SCNSL, the lack of randomized trial data, and the need for international consensus guidelines, there is a high unmet need for effective therapy options for SCNSL. Here we present safety and efficacy data on 2 SCNSL patients treated with the combination of emavusertib and ibrutinib. Both patients had directly progressed on their prior BTKi treatment. One patient achieved an unconfirmed complete response (CRu) and remained on treatment for over 4 mos, while the other patient maintained stable disease (SD) with a 38% reduction in disease burden from baseline and was on treatment for more than 8 mos. The patient with a durable SD, who received 5 prior lines of therapy along with an ASCT, presented with 3 related AEs Grade ≥ 3 that were reversible and manageable. These included elevated ALT, AST, and bilirubin levels that resolved. The patient received emavusertib 300 mg BID and ibrutinib 560 mg QD. The CRu patient received 6 prior lines of therapy and experienced CK elevation, fatigue, hypoglycemia, sepsis, urinary retention, neutropenia, and constipation that resolved with either a dose reduction and/or supportive care. The initial dose for this patient was 150 mg emavusertib BID and ibrutinib 560 mg QD. Subsequently, the dose of emavusertib was decreased to 150 mg BID due to Grade 4 neutropenia, then increased to 200 mg AM and 150 mg PM once resolved. This patient achieved CRu within 60 days on treatment. The 2 patients presented here are supportive data for using the combination of emavusertib and ibrutinib in SCNSL.

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.

We report 3-year follow-up results from TRANSFORM comparing lisocabtagene maraleucel (liso-cel) versus standard of care (SOC) for second-line primary refractory/early relapsed (≤12 months) large B-cell lymphoma (LBCL). Adults eligible for autologous stem cell transplantation (N = 184) were randomly assigned 1:1 to liso-cel (100 × 10 6 chimeric antigen receptor–positive T cells) or SOC. Results are reported descriptively. With a median follow-up of 33.9 months, median (95% CI) event-free survival was 29.5 months (9.5 to not reached [NR]) for liso-cel versus 2.4 months (2.2 to 4.9) for SOC (hazard ratio [HR], 0.375; 95% CI, 0.259 to 0.542). Median progression-free survival was NR (12.6-NR) for liso-cel versus 6.2 months (4.3-8.6) for SOC (HR, 0.422; 95% CI, 0.279 to 0.639) with 36-month rates of 51% versus 26.5%. Median overall survival (OS) was NR for both arms (HR, 0.757; 95% CI, 0.481 to 1.191), with 66% of patients crossing over to receive liso-cel; 36-month OS rate was 63% for liso-cel versus 52% for SOC. OS HR (0.566 [95% CI, 0.359 to 0.895]) favored liso-cel when accounting for the treatment effect of crossover. Safety results were consistent with previous reports. At 3-year follow-up, liso-cel confirmed superior, more durable efficacy versus SOC with a favorable safety profile and no new safety signals. These data support liso-cel as an effective second-line treatment with curative potential for relapsed/refractory LBCL.

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.

7032 Background: The impact of immune cell counts pre LD and during immune reconstitution on CAR T therapy outcomes is poorly understood. We investigated the association between CD4, CD8 and NK cell counts and CAR T therapy outcomes in patients with LBCL. Methods: Retrospective study of R/R LBCL patients who received CAR T cells between 2016-24 at Mayo Clinic, Rochester, were included in this analysis. Peripheral blood CD4, CD8 and NK counts were measured pre LD and at M1 post CAR T infusion. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff for pre LD and M1 immune cells to predict patients who were alive and in remission at 6 months (M6) post CAR T infusion. Patients who progressed or were lost to follow up prior to day 30 were excluded from M1 ROC analysis. Results: Of 140 patients, 81 were alive and in remission at M6 (Group A), while 59 had relapse or death (Group B). Axicabtagene ciloleucel was the CAR T product given in 81% of patients (114/140). Median pre LD CD4 counts were significantly lower in Group B compared to group A (143 vs 280 cells/µL, p = 0.001). No significant difference was observed in median pre LD CD8 counts (205 vs 221 cells/µL, p = 0.8). ROC analysis identified an optimal pre LD CD4 count of 124.5 cells/µL for M6 alive+remission. Lower pre LD CD4 counts (<124.5) predicted worse progression free survival (PFS) in univariate (HR = 3.02, 95% confidence interval [CI]: 1.73–5.27, p< 0.01) and multivariable analysis (MVA) adjusted for IPI and the number of prior lines (aHR = 2.54, 95% CI: 1.39–4.62, p< 0.01).Lower pre LD CD4 counts also predicted inferior overall survival (OS) in MVA (aHR = 2.27, 95% CI: 1.08–4.77, p = 0.03). (Table 1) On day 30 landmark analysis, ROC identified M1 optimal CD4 count of ≥ 99.5 cells/µL to be associated with a trend toward superior PFS (P=0.09), but not OS (p=0.90) in MVA. Median pre LD NK cell counts were significantly lower in Group B (73 vs 98 cells/µL, p = 0.04). ROC analysis identified an optimal pre LD NK count of 151 cells/µL for M6 alive + remission. Lower pre LD NK counts (<151) predicted worse PFS, both on univariate (HR = 4.17, 95% CI: 1.29–13.47, p = 0.02) and MVA (aHR = 4.64, p< 0.01). The lower pre LD NK cell count group had worse OS in MVA (aHR = 5.69, 95% CI: 1.16–28.1, p = 0.01). (Table 1) On D30 landmark analysis, M1 NK cell count of ≥ 128.5 cells/µL was associated with a trend toward superior PFS (P=0.08), but not OS (p=0.30) in MVA. Conclusions: Pre LD CD4 and NK cell counts are significantly associated with PFS and OS post CAR T therapy in patients with R/R LBCL. Pre-treatment immune subset levels may identify patients at higher risk of relapse or death after CAR-T therapy. Groups Median PFS 2 Year PFS Median OS 2 Year OS CD4 ≥124.5 cells/µL (N=75) NR 58% 3.31 years 67% CD4 <124.5 cells/µL (N=30) 2.2 months 22% 1.59 years 45% NK ≥151 cells/µL (N=17) NR 77% NR 84% NK <151 cells/µL (N=82) 10.6 months 44% 3.31 years 62%

e19008 Background: Cytokine release syndrome (CRS) is typically reversible in CAR-T therapy, while hyperinflammatory syndromes like macrophage activation-like syndrome (MAS-L) and high-grade immune effector cell-associated hemophagocytic syndrome (IEC-HS) are associated with significant morbidity and mortality. Early interventions are critical for improving outcomes. We aim to analyze clinical cytokine assays and cellular phenotypes early in hyperinflammatory syndromes to identify profiles for severe cases to inform management decisions. Methods: This study included 113 CAR-T patients (pt) (September 2019-March 2024) with cytokine profiles (CP) performed at the second tocilizumab dose or with suspected hyperinflammatory states (CP1), followed by assessments at 24 hours (CP24) and 48 hours (CP48). 52 pts consented to blood (PB) and bone marrow (BM) cell immune phenotyping at pre-treatment (pre-LD) and day 1 for PB. Results: Among the 113 pts, CRS pts (N=74), when compared to MAS-L(N=19) & IEC-HS (N=20) at CP1, had lower levels of TNF (median in pg/mL; 31, 62.9, 47.7) , IL-18 (794, 1353, 2011), and MCP-1 (689, 2722, 2485.5). While MAS-L and IEC-HS had similar CP1 profiles, CP24 and CP48 differed between them: TNF & MCP-1 levels decreased in MAS-L but remained elevated or increased in IEC-HS. IL-18 was stable in MAS-L but increased steadily daily in IEC-HS. Infections were more frequent in IEC-HS (CRS: 43%; MAS-L: 58%; IEC-HS: 85%; p=0.002). Notably, patients who died with persistent E. faecium bacteremia had higher IL-18 in CP48. In the 52 pts with cell phenotypes available by flow, 33 had CRS, 18 MAS-L and 8 IEC-HS. The correlation between cell phenotypes and cytokine levels showed that elevated TNF at CP1 correlated with increased non-classical monocytes in pre-LD BM and higher NK and NK-T cells in pre-LD PB. Similarly, elevated IL-18 CP48 levels correlated with increased CD8 T-cells, NK-T cells, and intermediate monocytes in pre-LD PB, as well as increased NK cells at both pre-LD and day 1 (Table). Conclusions: We report distinct cytokine profiles in IEC-HS early in the inflammatory course post-CAR-T therapy. These elevated cytokines correlate with specific immune cell subsets, including BM-resident monocytes, intermediate monocytes with heightened cytokine trafficking and inflammatory capacity. This study demonstrates the feasibility for identifying potential biomarkers for early risk stratification and targeted interventions. Cytokine Sample source Immune cells R P value TNF CP1 BM pre-LD Non-classical monocytes (CD14loCD16+) 0.38 0.025 PB pre-LD Monocytes (All) 0.47 0.022 NK cells (CD56+CD16+) 0.34 0.024 NK-T cells (CD3+CD56+CD16-) 0.29 0.04 IL-18 CP48 PB pre-LD CD8+ T-cells 0.59 0.0093 NK-T cells (CD3+CD56+CD16-) 0.53 0.023 Intermediate monocytes (CD14+CD16+) 0.58 0.012 PB pre-LD NK cells (CD56+CD16+) 0.56 0.49 0.015 0.024