Johnston, Patrick B.

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.

We report correlative circulating tumor DNA (ctDNA) analyses from TRANSFORM (ClinicalTrials.gov identifier: NCT03575351 ) evaluating lisocabtagene maraleucel (liso-cel) versus standard of care (salvage immunochemotherapy, high-dose chemotherapy, autologous stem cell transplantation [ASCT]) in second-line large B-cell lymphoma (LBCL). ctDNA association with efficacy was investigated at predefined time points (random assignment, day 43, day 64, and day 126 [3 months after liso-cel, approximately 2 months after ASCT]) for 136 patients using ultrasensitive PhasED-Seq. ctDNA clearance (measurable residual disease [MRD] neg ) predicted longer event-free survival (EFS) at all time points in both arms, with significantly more liso-cel–treated patients achieving MRD neg . Liso-cel demonstrated superior outcomes versus ASCT, including longer EFS, progression-free survival (PFS), and duration of response among patients in complete response (CR) and MRD neg . ctDNA re-emergence in patients with CR after ASCT confirmed its potential in predicting relapse. MRD neg remained significantly associated with EFS after adjusting for positron emission tomography (PET) response, while interaction testing revealed a significant interaction between PET status and treatment arm for EFS. Liso-cel achieved deeper, more durable molecular clearance by ctDNA, consistent with superior EFS and PFS versus ASCT for second-line LBCL treatment. ctDNA-MRD provided prognostic value beyond PET, supporting its role as a complementary biomarker for treatment response and relapse prediction.

Summary Chimeric antigen receptor T cells directed against CD‐19 are highly effective therapies for various subtypes of B‐cell non‐Hodgkin lymphoma (NHL). We have studied the impact of patient‐specific lymphocyte growth kinetics after lymphoid depletion chemotherapy on both long‐term outcomes and toxicity in patients with diffuse large B‐cell non‐Hodgkin lymphoma (DLBCL). The growth of the lymphocyte populations early after chimeric antigen receptor T‐cell (CAR‐T) therapy is well described by an exponential function and the growth rate of the cells appears to be one of the most critical determinants of overall survival in these patients. The maximum lymphocyte peak and the area under curve for lymphocytes within the first 4 weeks after CAR‐T therapy had no impact on survival. Receiver operator characteristic analysis determined that a replication rate ≥0.3876/day is associated with superior rates of complete response and durable responses. This threshold is associated with higher grades of cytokine release syndrome and the need for tocilizumab. However, patients with this threshold have a median overall survival of 3.04 years compared to 1.035 years for patients with slower lymphocyte replication ( p = 0.0206). The major determinant of depth of response and durability of response to CAR‐T in NHL is the speed of lymphocyte expansion.

ABSTRACT 162 patients with relapsed secondary central nervous system lymphoma (R‐SCNSL) (median age, 65 years; male, 59.9%) including central nervous system (CNS)‐only ( n = 120) and concomitant CNS/systemic relapse ( n = 42) were retrospectively analyzed. Overall, 21.9% of patients were classified as high risk according to the CNS International Prognostic Index (CNS‐IPI). Several biological and clinical features were significantly associated with leptomeningeal involvement, including double‐ or triple‐hit (DHL/THL) status, MYC rearrangement, negative BCL6 expression by IHC, bone marrow involvement, and concomitant R‐SCNSL. Multivariable analysis showed that leptomeningeal involvement independently predicted inferior OS and was associated with a 98% increase in the hazard of death compared with parenchymal relapse (HR = 1.98, 95% CI: 1.20–3.26, p = 0.008). Based on anatomical localization, R‐SCNSL was classified into four subtypes: parenchymal‐only involvement (parenchymal‐CNS [P‐CNS], 68/42%) and parenchymal involvement plus systemic relapse (parenchymal‐concomitant [P‐concomitant], 17/10.5%); and leptomeningeal with or without parenchymal involvement (leptomeningeal‐CNS [LM‐CNS], 52/32.1%) and leptomeningeal with systemic relapse (leptomeningeal‐concomitant [LM‐concomitant], 25/15.4%). This anatomical classification significantly impacted OS and PFS ( p < 0.001). Two‐year OS and PFS were 58.2% and 29.1% for P‐CNS, 32.4% and 17.7% for P‐concomitant, 22% and 13.9% for LM‐CNS, and 7.1% and 0% for LM‐concomitant, respectively. ASCT showed a trend toward improved survival among patients with a response (CR/PR) in a 4‐month landmark analysis. These findings support the clinical application of the anatomical classification in the management of R‐SCNSL.

Abstract Castleman disease (CD) is a heterogeneous group of lymphoproliferative disorders anatomically classified by distribution (unicentric CD [UCD], oligocentric CD [oligoCD], or multicentric CD [MCD]). Human herpes virus 8–negative MCD is called idiopathic MCD (iMCD), which includes clinical subtypes with varying phenotypes and responses: TAFRO (thrombocytopenia, anasarca, fever, renal dysfunction and/or reticulin fibrosis, and organomegaly), IPL (idiopathic plasmacytic lymphadenopathy), and not otherwise specified. OligoCD has recently emerged as an intermediate form between UCD and MCD, with unclear clinical behavior, and IPL has not been validated in a Western cohort. We retrospectively analyzed 217 patients with CD evaluated at our institution between January 2004 and August 2024. Survival probabilities were compared using log-rank tests. Overall, 57% had UCD, 20% had oligoCD, and 23% had iMCD. Patients with oligoCD and iMCD more frequently exhibited systemic symptoms than those with UCD. Patients with oligoCD and iMCD had significantly shorter event-free survival (EFS) of 8.9 and 2.3 years, respectively, than those with UCD (not reached; P&lt; .001 and P&lt; .02). Among iMCD subtypes, iMCD-IPL demonstrated a longer EFS than iMCD-TAFRO (P = .02), with no deaths during the follow-up periods. The results validate oligoCD and iMCD-IPL as new subtypes in this Western cohort. The survival outcome in oligoCD was intermediate between UCD and iMCD, with only a subset of patients with oligoCD requiring systemic therapy. iMCD-IPL had a favorable survival outcome in this US cohort, similar to what has been reported in non-Western countries. Tailoring treatment strategies to disease subtypes and vigilant monitoring of oligoCD for progression may improve survival outcomes in CD.

Abstract Chimeric antigen receptor (CAR) T-cell therapy has demonstrated remarkable response rates in relapsed/refractory aggressive B-cell non-Hodgkin's lymphoma. However, durable remissions occur in only 40% of treated patients, highlighting mechanisms of therapeutic resistance and immune escape. While cytotoxicity is principally executed by CAR T-cells, monocytes shape CAR-T cell efficacy and orchestrate cytokine-driven immunity. In this study, we defined distinct metabolic profiles of T-cell and monocyte subsets based on clinical response. Single-cell RNA sequencing (scRNA-seq) and T-cell receptor sequencing (scTCR-seq) were performed on peripheral blood mononuclear cells at three timepoints: before lymphodepletion (BL), at peak CAR-T expansion (PK), and one-month post-infusion (M1). Data were processed with CellRanger v7.0.1 and analyzed with the immunopipe pipeline (Wang et al., 2025). Seurat v4.3.0 was utilized for unsupervised hierarchical clustering analysis; subsets identified included classical monocytes (CM), intermediate monocytes (IM), non-classical monocytes (NM), and monocytic myeloid derived suppressor cells (mMDSC). Metabolic profiles were compared across patients achieving ≥6-month complete remission (CR, n=16), primary refractory disease (PD1, n=4), or relapsed after a prior response (PD2, n=12). A total of 107035 T cells and 129981 monocytes from 77 serial samples in 32 patients were analyzed. CR patients had a higher T-cell:monocyte ratio than PD1/PD2 at all time points, especially at BL and PK (BL 1.2 vs 0.4, p=0.011; PK 1.3 vs 0.3, p=0.027). Clinical responses were compared with metabolic pathway analysis and identified oxidative phosphorylation (OXPHOS) as the dominant pathway. OXPHOS was consistently enriched in PD cohorts across T-cell subsets, particularly in PD1 vs CR at BL (mucosal-associated invariant T-cell (MAIT) and T peripheral memory (Tpm)), and at PK (CD4/CD8 memory precursor effector cells (MPEC) and activated MPECs (MPECa), CD4 T-helper 1 proliferating (Th1p), CD4 Th2 activated (Th2a), regulatory T-cell (Treg), CD8 naive senescent (CD8NS), CD8 T effector memory (Tem) tumor recirculating (TR), CD8 Tpm, CD8 T resident memory (Trm) TR and MAIT Tpm). By M1, OXPHOS enrichment in CD4/CD8MPECa, CD4Th2a, CD8NS, CD8TemTR reversed, now predominant in CR although CD8Tpm and CD8TrmTR remained enriched in PD1. In the monocyte subsets at BL, PD2 showed OXPHOS enrichment in CD163+ monocytes (mono), IM IL1, mMDSC SIRPA, mMDSC TGFβ, and CM IL6 subsets compared to PD1 and CR, while PD1 showed OXPHOS enrichment in IM CD38, CM TGFβ, and mMDSC HIF1A vs CR and PD2. This persisted at PK. By M1, the pattern reversed and mirrored that of T-cells, with CR patients showing OXPHOS enrichment in CD163+mono, CM IL6, CM TGFβ, IM CD38, mMDSC HIF1A, mMDSC SIRPA and mMDSC TGFβ, and additionally in CM EMT, CM p53, NM, NM CD36 vs PD1/PD2. Glycolysis/gluconeogenesis (GLY) was also enriched across subsets. In T-cells, PD1 vs CR showed GLY enrichment in CD4Th2a, CD8Tpm, CD8Tpm proliferating and MAIT Tpm at PK. In monocytes, GLY was enriched in PD1/2 vs CR at BL (CD163+mono, CM IL6) and PK (CD163+mono, IM CD18, mMDSC SIRPA). By M1, GLY metabolism was enriched in CR vs PD1/PD2 in CD163+mono, CM IL6, mMDSC SIRPA. Additional GLY enriched subsets at CR vs PD1 included CM, CM p53, EMT, IM CD38, IM IL1, mMDSC HIF1A, NM, NM CD36. Inositol phosphate metabolism (IP) was predominantly enriched in PD2 vs CR at BL (CD8NS, CD8Tcm, CD8Tpm activated), PK (CD4Th2, CD8NS, CD8Tem TR, CD8Tpm proliferating, γδT Tem) and M1 (CD4/CD8 MPECa, CD4 Th1/Th2, CD8NS, CD8Tpm, CD8 Tpm proliferating, Treg and MAIT Tpm). Notably, Treg was the only T-cell subset enriched for IP at PK in CR vs PD1/PD2. Additionally, the TCA cycle was enriched in PD1 Tregs and Th2 cells at BL and PK vs CR/PD2. A higher T-cell:monocyte ratio in CR vs PD1/PD2 supports prior evidence that elevated pre-lymphodepletion lymphocyte:monocyte ratios predict better outcomes. We identified distinct metabolic signatures in T-cells and monocytes between CR and PD1/PD2. OXPHOS enrichment in T-cells and monocytes at M1 in CR patients may reflect oxidative programming as a hallmark of sustained anti-tumor immunity. Conversely, GLY enrichment in PD1 T-cells at PK may reflect short-lived effector states lacking persistence. Overall, these findings highlight metabolic profiling as a promising predictive biomarker and therapeutic programming target to enhance CAR T-cell outcomes.

Abstract Introduction: CAR-T therapy has transformed cancer therapy. with its first Food and Drug Administration (FDA) approved product in August 2017. Given the expanding indications and growing experience, particularly with management of immediate toxicities requiring specialized expertise such as Cytokine Release Syndrome (CRS) and Immune Effector Cell-Associated Neurotoxicity syndrome (ICANS), FDA recently removed the Risk Evaluation and Mitigation Strategies (REMS) for CD19 and BCMA targeting CAR-T on June 26th2025. In particular, given that CRS and ICANS typically occur in the first 2 weeks post CAR-T infusion, the minimum required stay near CAR-T treatment center is reduced from one month to 2 weeks. While this could reduce treatment burden for patients (pts) who need to travel away from home to receive CAR-T, there is a need to update the transition of care from CAR-T center to pts' local oncology practice. Pts carry in their rate of recovery and have varying supportive care needs in the second half of the month post CAR-T infusion. To assist with care transition and planning, we examine the use of AI multimodal large language model (LLM) to predict patients' supportive care needs 2 weeks after CAR-T infusion based on the clinical data at the time of CAR-T evaluation, prior to leukapheresis. This timepoint was selected to also maximize travel, lodging and caregiver planning for pts and family as well. Methodology: Pts who were treated with FDA-approved CAR-T at Mayo Clinic Rochester between December 2022 and June 2025 were examined. Based on experiences with referral practices in the Midwest region, we defined patients with high monitoring needs as those who between day 14-30 post CAR-T had either hospital admission due to recurrent CRS or ICANS or required transfusion of more than 1 blood product per week (red blood cell or platelets). Others were classified as low monitoring needs. Clinical notes, labs, vital signs and electrocardiogram at the time of CAR-T evaluation were abstracted and summarized by Gemini LLM for association with patients with high versus low monitoring needs post CAR-T. Model was developed and tested for predicted needs and concordance with actual outcome of these pts. Results: Among the 362 pts who received FDA approved CAR-T in the timeframe, 84 pts had high monitoring needs. An additional 84 pts with low monitoring needs were randomly selected from 278 pts. These were divided into a training cohort and test cohort of 84 pts each, with 42 pts with high and 42 pts with low monitoring needs. Demographics of the two cohorts displayed no statistical difference. LLM analysis of the clinical data at the time of CAR-T eval identified 5 categories associated with risk for high monitoring needs: 1) Disease status (clinical notes about bulky, progressive disease or CNS involvement); 2) inflammatory and tumor burden markers (CRP, LDH); 3) hematologic status (platelet, plt; neutrophil count ANC); 4) renal function; 5) performance status. Using common clinical lab parameter convention (platelets &lt;100, ANC&lt; 1, CrCl&lt; 30ml/min), and prioritizing for not missing pts with high monitoring needs, LLM model was defined to predict patients for high monitoring needs if high risk feature was identified in category 1 or any category combinations; whereas patients with no high risk feature or only 1 category that is not disease status was predicted as low monitoring needs. In this model, the sensitivity was 85.7%, specificity 23.8%, F1 score 65.5%. Applying this model to test cohort 2, the sensitivity was 83.3%, specificity 28.6%, and F1 score 65.4%. Discussion: We demonstrate proof-of-concept that LLM can be used to analyze clinical data at the time of evaluation for CAR-T eligibility to predict for supportive care needs post treatment. Not surprisingly, features identified by LLM to be associated with high monitoring needs are those previously reported by us and others at the time of CAR-T evaluation and or pre-lymphodepletion to be associated with risk for cytopenia, infection, hospitalization and non-relapse mortality. Based on the summary output generated by LLM, additional opportunities for classification methods were identified to improve specificity and balanced accuracy of the LLM model. This is a promising tool for further development to assist clinicians and patients to plan their treatment journey.

Abstract Background Chimeric-antigen-receptor (CAR) T-cell therapy has transformed outcomes for relapsed or refractory hematologic malignancies, yet early identification of patients at highest risk for death remains elusive. A prognostic model that leverages only the information routinely available at the time of CAR-T evaluationcould guide pre-infusion counseling, intensity of follow-up, and resource allocation. Methods We analyzed a prospectively maintained cohort of CAR-T recipients treated at Mayo Clinic to develop and test our model. For each patient, data (vital signs, lab results, cardiac assessments [ECG and echocardiography], and PET/CT images) from initial CAR-T evaluation (up to 60 days prior to CAR-T infusion) was considered. Vital signs and labs were left un-imputed, while ECG, echocardiographic parameters, and PET/CT features were forward-filled from the preceding 60 days. Each patient-day was labeled as “outcome present” or “no outcome,” enabling supervised training of gradient-boosting models to predict overall survival (OS) at 6 months post CAR-T infusion. Model performance was evaluated using the area under the ROC curve (AUC) with 10,000-fold bootstrapping with data shuffling between each iteration to derive confidence intervals for stability. To enhance interpretability, we also developed a simplified model using the top 19 features (determined by Shapley value-based importance), aiming to preserve predictive accuracy with a smaller feature set. Results A total of 570 CAR-T cell treated patients were included in this study (476 patients in the training cohort and 94 patients in the validation cohort). The median age was 64 years and 61% males. The primary diagnoses were B-cell lymphoma (324 patients) and multiple myeloma (246 patients). A total of 4,851 individual vital-sign readings, 11,781 laboratory measurements were included. PET/CT images were available in 318 patients. The ML model demonstrated high discriminative ability for predicting OS at 6 months post CAR-T infusion. Vital signs alone produced a mean AUC of 0.63; radiomics features alone produced a mean AUC of 0.71, while laboratory tests alone produced a mean AUC of 0.84. The features most contributory to each single-modality model were then combined into a simplified multimodal model with a total of 19 features, which produced a mean AUC of 0.87, with a 95% CI of 0.73 - 0.97. The 19 features included in the simplified model were: LDH, ferritin, uric acid, eosinophils, fibrinogen, D-dimer, heart rate, mean arterial blood pressure, QTc, QT interval, and the radiomics features of sphericity, first-order Kurtosis, first-order mean, first-order energy, first-order total energy, shape maximum2D diameter (sagittal plane), SUV CoV, SUVp90, shape flatness. This multimodal predictive model was then applied to the validation cohort (uninvolved with model training or testing), which produced an AUC of 0.93, with a 95% CI of 0.84 - 0.98. Conclusions Our ML-driven approach successfully predicts overall survival 6 months post CAR-T infusion, highlighting those individuals at most risk of poor outcomes at the time of CAR-T evaluation. The strong performance of the multimodal version of the model suggests that each data domain contributes complementary resolving power, and by including novel data types, such as PET CT radiomics features, the most accurate predictions could be realized. By providing accurate, near-real-time risk stratification for poor outcomes within 6 months of CAR-T infusion, the model could facilitate proactive patient management. Prospective studies of the integration of this ML model into CAR-T treatment workflows will be crucial to confirm its clinical benefits and to facilitate its adoption in practice.

Abstract Background: De novo secondary central nervous system (CNS) lymphoma (SCNSL), characterized by concurrent systemic and CNS aggressive B-cell lymphoma at diagnosis, is a rare entity with a dismal prognosis. The prognostic significance of the initial anatomical compartment of CNS involvement (parenchymal vs. leptomeningeal) is not well-defined. We sought to analyze outcomes based on CNS localization in a single-institution cohort. Methods We retrospectively reviewed 34 patients with de novo SCNSL (including diffuse large B-cell lymphoma [DLBCL], high-grade B-cell lymphoma, not otherwise specified (HGBCL NOS), and double-/triple-hit lymphoma) treated at the Mayo Clinic between 2002 and 2025. Clinicopathological features, radiologic findings, treatment details, and survival outcomes were abstracted from the medical records. Patients were categorized by the primary site of CNS involvement. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and groups were compared with the log-rank test. Results The study cohort had a median age of 61.5 years (range 19-79) and a median International Prognostic Index score of 3 (range 2-4). Pathological subtypes included double-/triple-hit lymphoma (n=14, 41.2%), non-germinal center B-cell like (non-GCB) DLBCL (n=11, 32.4%), germinal center B-cell like (GCB) DLBCL (n=8, 23.5%), and HGBCL NOS (n=1, 2.9%). Among patients with available data, 14 (43.8%) were positive for MYC rearrangement, 13 (54.2%) for BCL2 rearrangement, and 10 (45.5%) for BCL6 rearrangement. First-line regimens received by patients included MR-CHOP (n=18, 52.9%), DA-R-EPOCH (n=5, 14.7%), combined CODOX-M/IVAC (n=4, 11.7%), R-CHOP with intrathecal methotrexate (n=3, 8.8%), miscellaneous therapies (n=3, 8.8%), and MRT (n=1, 2.9%). The complete response rate was 58.8% (n=20). Intrathecal chemotherapy was administered to 61.8% of patients, and consolidation with autologous stem cell transplant was performed in 35.3%. Based on the CNS compartment involved, de novo SCNSL (DN-SCNSL) were classified into two subtypes: the leptomeningeal subtype, defined as leptomeningeal involvement with or without parenchymal CNS disease (LM-DN-SCNSL; n=22, 64.7%), and the parenchymal subtype, defined as parenchymal-only CNS involvement (P-DN-SCNSL; n=12, 35.3%). Parenchymal disease was multifocal in 75% of cases, supratentorial in 58.3%, and associated with a midline shift in 30%. Although no tested factors (including pathological subtype, age, sex, and bone marrow involvement) were significantly associated with the anatomical compartment, a non-significant trend was noted for BCL6 rearrangement to be more common in the leptomeningeal group (8/13, 61.5%) than the parenchymal group (2/8, 25.0%) (P = 0.18). Survival outcomes were analyzed for both anatomical and pathological classifications. For the parenchymal versus leptomeningeal cohorts, 2- and 5-year Overall Survival (OS) rates were 75.0% vs. 45.1% and 41.0% vs. 38.7%, respectively (P = 0.34). For Progression-Free Survival (PFS), the 2- and 5-year rates were 48.6% vs. 32.5% and 29.2% vs. 26.0%, respectively (P = 0.53). The 2-year OS rates by pathological subtype were 81.8% for non-GCB DLBCL, 45.8% for DHL/THL, and 37.5% for GCB DLBCL (P = 0.27). Survival outcomes (OS/PFS) were not significantly associated with patient age, sex, pathological subtype, or anatomical compartment. Conclusion DN-SCNSL can be anatomically classified into two subtypes: LM-DN-SCNSL and P-DN-SCNSL. While a prognostic trend favoring the parenchymal subtype was observed, the difference did not achieve statistical significance, a finding likely attributable to the small cohort size. This classification may hold clinical utility for guiding risk stratification, and larger studies are needed to validate these findings and identify the most optimal treatments for each subtype of DN-SCNSL.