Citations

Abstract Background: Venetoclax (VEN)+obinutuzumab (VO) is an effective therapy for CLL/SLL requiring regular monitoring for tumor lysis syndrome (TLS) during VEN ramp-up. The CLL14 trial of VO reported no TLS during VEN ramp-up; however, there are limited real-world data on monitoring practices and TLS outcomes for different dose levels and monitoring timepoints. This study assessed VEN initiation prophylaxis and monitoring outcomes for patients (pts) with CLL/SLL starting VO in first line (1L) in an outpatient, real-world setting. Methods This interim analysis relied onretrospective observational data from 4 US sites of the CLL Collaborative Study of Real-World Evidence (CORE). Adult pts with CLL/SLL were eligible if they: (1) started VO per-label outside of a clinical trial in 1L, or immediately after exposure in 1L to agents with different mechanisms of action (i.e., BTKi, anti-CD20 only) of <30 days; (2) prior to VEN start, had either (i) low physician-determined tumor burden (TB) (i.e., all lymph nodes [LN] <5 cm and ALC <25 x 109/L), or (ii) medium physician-determined TB (i.e., any LN ≥5-<10 cm or ALC ≥25 x 109/L) with creatinine clearance ≥80 mL/min; (3) had no strong CYP3A inhibitors or prophylactic rasburicase from 3 days prior to VEN start until end of VEN ramp-up; and (4) had VEN ramp-up in an outpatient setting. TB-related labs/imaging was assessed from 2 months prior to obinutuzumab initiation (i.e., index date) until VEN start. VEN characteristics (i.e., dosing, duration), prophylaxis measures (i.e., antihyperuricemics and IV hydration), and TLS-related monitoring and management (i.e., lab results and interventions received) were collected per ramp-up week and TLS monitoring timepoint. Results Of 128 pts in CORE who initiated VO in any line, 72 pts met inclusion criteria (low TB: 57 [79.2%]; medium TB: 15 [20.8%]). Median (IQR) age was 62 (56.0, 68.5) years, 58.3% were male, and 81.9% had ECOG grade ≤1. Among pts tested, 7/68 (10.3%) had del(17p)/TP53 mutation and 43/66 (65.2%) had unmutated IGHV. Median (IQR) time from index to VEN start was 23.0 (22.0, 30.0) days. Most pts completed ramp-up (98.6% [71/72]) and followed a per-label regular dosing schedule (93.1% [67/72]). Prior to VEN ramp-up, all pts received prophylactic antihyperuricemics (allopurinol: 71 [98.6%]; febuxostat: 2 [2.8%]) and prophylactic hydration. In the 2 days prior to a dose escalation for at least 1 week of ramp-up, prophylactic IV hydration was reported for 27 (37.5%) pts based on physician determination. One pt stopped VEN after week 2 due to neutropenia (grade 3+). During ramp-up (median [IQR] of 9 [8, 12] blood tests per pt), no lab or clinical TLS was reported. Of 21 (29.2%) pts who received an intervention following a lab assessment, most had low TB at VEN start (16 [76.2%]). All interventions were either prophylactic or non-TLS-related. Following a lab assessment for at least 1 week of ramp-up, prophylactic IV or escalated oral hydration intervention was reported in 17/21 pts (81.0%) based on physician determination (e.g., to manage impaired baseline renal function in those with low TB, patient request, or institutional practice) (IV hydration: 15 pts; escalated oral hydration: 2 pts). By per-label monitoring timepoints, hydration intervention was given prophylactically following pre-dose lab tests for 7 pts (across weeks 1-5), 6-8 hours post-dose for 5 pts (weeks 1-2), and 24 hours post-dose for 10 pts (weeks 1-2). By per-label monitoring timepoints, other non-TLS-related interventions (i.e., blood transfusion for anemia, insulin for hyperglycemia, and potassium for non-TLS-related hypokalemia) were given following pre-dose lab tests for 2 pts (weeks 1-5) and 24 hours post-dose for 4 pts (weeks 1-2). Conclusion Consistent with the CLL14 trial, no TLS was reported in this real-world, interim analysis of pts with mostly low TB and good renal function at 1L VO initation. All interventions during VEN ramp-up were prophylactic or non-TLS-related, with prophylactic hydration commonly given based on physician preference. These results suggest that VO initiation is manageable in an outpatient setting. Consideration should be given for simplified monitoring requirements including potential removal of 6-8 hour post-dose lab in this population and be further explored in prospective studies. Data collection for this study is ongoing to further contextualize real-world VEN initiation prophylaxis and monitoring outcomes in a larger cohort.

Abstract Introduction There is currently no standard-of-care for patients (pts) who cannot tolerate full dose anthracycline regimens in frontline large B-cell lymphoma (LBCL). R-miniCHOP is a commonly used regimen that provides curative intent treatment with manageable toxicity. Despite this, lymphoma and treatment-related mortality are the leading causes of death in these pts. Additionally, many pts may not be eligible to receive R-miniCHOP due to comorbidity or frailty. There are limited clinical trial and real-world data focused on this population. Methods Pts with LBCL age 18 years (yrs) and older were identified from the Lymphoma Epidemiology of Outcomes (LEO) cohort, a prospective study of newly diagnosed pts with non-Hodgkin lymphoma enrolled from 2015-2020 at 8 academic medical centers in the US. Pts with LBCL were included in this analysis if they had received R-miniCHOP or a regimen that did not include an anthracycline (nonAC). NonAC regimens included R-CVP, BR, rituximab, radiation and lenalidomide and rituximab. Pts completed the Vulnerable Elders Survey (VES-13) and were considered vulnerable if they had a score >3. Event-free survival (EFS) was defined as the time from start of treatment until progression/relapse, retreatment, or death due to any cause; EFS at 24 months (EFS24) was a secondary endpoint. Overall survival (OS) was defined as the time from start of treatment until death due to any cause. EFS and OS for R-miniCHOP and non-IC groups, as well as vulnerable and not vulnerable by VES-13 were estimated using Cox models. Results A total of 190 pts received R-miniCHOP (N=139) or nonAC (N=51). R-miniCHOP-treated pts were older (median 82 vs 72 yrs) and more commonly female (55% vs 35%). The majority in both groups (86% vs 78%) received their treatment at a LEO center and did not receive therapy on a clinical trial (89% vs 100%). Most pts receiving R-miniCHOP had high-intermediate (32%) or high (30%) international prognostic index (IPI) score, while both high-intermediate (22%) and high (20%) IPI were lower in the nonAC-treated pts. Cell of origin was determined by immunohistochemistry as available clinically, with GCB 42% vs 31%, non-GCB 32% vs 29%, and not done/unknown 26% vs 39% in R-miniCHOP vs nonAC pts. Double-hit status by FISH was known in 115 pts and was positive in 13% of R-miniCHOP pts and 10% of nonAC pts. The diagnosis-to-treatment interval (DTI) was ≤14 days in 30% of R-miniCHOP pts and 24% of nonAC pts. Of pts who had a VES-13 score (N=119), vulnerable status trended higher in the R-miniCHOP (66%) vs the non-IC group (50%; p=0.15). With a median follow-up of 50.5 months, the median EFS was 37.1 months and median OS was 50.0 months. R-miniCHOP, compared with non-IC, was associated with improved EFS (unadjusted HR=0.54, 95% CI 0.36-0.81; p=0.003) and OS (unadjusted HR=0.58, 95% CI 0.38-0.88; p=0.011). When adjusted for age, IPI, LBCL subtype (diffuse large B-cell lymphoma, not otherwise specified vs other), DTI and VES-13, R-miniCHOP was strongly associated with improved EFS (HR=0.26, 95% CI 0.14-0.50; p<0.001) and OS (adjusted HR=0.29, 95% CI 0.15-0.57; p<0.001). EFS24 rate was 56% in all pts and was superior in pts treated with R-miniCHOP vs non-IC (62.7% vs 34.1%; p=0.001). In the R-miniCHOP group, vulnerable status (adjusted for IPI) was associated with inferior OS (HR=2.22, 95% CI 1.09-4.50; p=0.028) and trended towards inferior EFS (HR=1.76, 95% CI 0.93-3.32; p=0.083). In a competing-risk cumulative-incidence analysis, lymphoma was the leading cause of death for pts receiving R-miniCHOP at 2 (0.16, 95% CI 0.11-0.24) and 5 (0.20, 95% CI 0.14-0.28) yrs, as well as for those receiving non-IC at 2 (0.35, 95% CI 0.24-0.53) and 5 (0.38, 95% CI 0.26-0.56) yrs. Treatment-related mortality was similar in both groups. In the R-miniCHOP group, the 2-yr (0.20 vs 0.03) and 5-yr (0.20 vs 0.11) lymphoma-related mortality was higher in pts who were vulnerable vs not by VES-13, while there were no differences for mortality due to therapy or other causes by vulnerable status. Conclusions These data support R-miniCHOP as a curative regimen in older and frail pts with the majority achieving EFS24. R-miniCHOP compared to non-IC use is strongly associated with improved EFS and OS when adjusted for disease and patient related variables. Within the R-miniCHOP group, vulnerable status is associated with inferior OS. Additional research efforts are needed to optimize outcomes for this group of pts.

Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Abstract Background: Chimeric Antigen Receptor T-cell therapy (CAR-T) has revolutionized the treatment landscape of hematological cancers, including B-cell non-Hodgkin's lymphoma (NHL), multiple myeloma (MM), and acute lymphoblastic leukemia (ALL). However, the cardiac toxicity profile of this therapy is not well described in the literature. The majority of patients receiving CAR-T are older adults who may have pre-existing cardiovascular risk factors, received prior cardiotoxic therapy including anthracycline, alkylators, corticosteroids, proteosome inhibitors, radiation, autologous and allogeneic stem cell transplants. Due to a stricter patient selection for CAR-T clinical trials, cardiac adverse events (AEs) are infrequent. As the survival of patients with hematological malignancies continues to improve with advancements in therapy, it becomes critical to consider the cumulative cardiotoxic effects of these therapies. Therefore, a post-marketing pharmacovigilance analysis of the cardiac AEs reported to the FDA Adverse Event Reporting System (FAERS) for each CAR-T product was conducted to address this knowledge gap. Methods: All individual case safety reports of cardiac AEs listing any of the approved CAR-T therapies [Tisagenlecleucel (Tisa-cel), Axicabtagene ciloleucel (Axi-cel), Lisocabtagene maraleucel (Liso-cel), Brexucabtagene autoleucel (Brexu-cel), Idecabtagene vicleucel (Ide-cel), Ciltacabtagene autoleucel (Cilta-cel) and Obecabtagene autoleucel (Obe-cel)] as the suspected drug were identified from the FAERS database. Patient characteristics, including primary malignancy, age, sex, CAR-T product and AEs were described. Disproportionality analysis was performed using Reported Odds Ratio (ROR) to determine significant associations between CAR-T products and cardiac AEs. Results: There were 1362 cardiac AEs after CAR-T therapy reported in the FAERS database(602 with Axi-cel, 444 with Tisa-cel, 77 with Cilta-cel, 81 with Ide-cel, 128 with Brexu-cel, 30 with Liso-cel and 0 with Obe-cel).Of these, 57% were males, 8.6% occurred in patients <18 yrs, 35.4% in 18–64 yrs, and 32% in >65 yrs. There were 778 reports of arrythmias, 158 heart failures, 184 cardiac arrests, 43 pericardial AEs, 16 valvular AEs, 59 ischemic AEs, 10 cardiogenic shock, 8 myocarditis, and 106 other cardiac disorders (cardiac thrombus, cardiomegaly, cardiac rupture, orthostatic hypotension, hypertensive emergency/crisis etc.). In the entire cohort, males were more likely to develop pericardial (ROR=3.55, p=0.004) and valvular disorders (ROR=9.13, p=0.03), with females developing heart failure (ROR=1.61, p=0.005). Patients <18 years had a higher incidence of pericardial (ROR=3.44, p=0.006) and valvular disease (ROR=12.79, p<0.0001), while adults aged >65 had higher propensity of developing atrial tachyarrhythmias (ROR=2.74, p<0.0001), ventricular arrhythmias (ROR=3.04, p=0.001) and cardiogenic shock (ROR=8.38, p=0.05), and a trend towards higher risk of developing acute coronary syndrome (ACS) (ROR=1.79, p=0.06). For ischemic cardiac AEs, Brexu-cel was associated with increased risk of myocardial infarction (ROR=2.34, p=0.04), and Ide-cel was associated with elevated troponin levels (ROR=6.23, p=0.002). For functional cardiac AEs, Tisa-cel was associated with cardiac arrest (ROR=1.68, p=0.001), pericardial disorders (effusion, tamponade and pericarditis) (ROR=3.56, p<0.001), valvular disorders (ROR=55.97, p<0.0001), myocarditis (ROR=6.2, p=0.012) and heart failure (ROR=2.24, p<0.001). B-ALL was associated with higher odds of cardiac arrest (ROR=1.63, p=0.018). For conduction-related cardiac AEs, Brexu-cel had higher rates of brady-arrythmias (ROR=1.86, p=0.04), Cilta-cel had increased incidence of atrioventricular block (ROR=7.87, p=0.02), and tachy-arrhythmias (ROR=1.71, p=0.0001). Tisa-cel was associated with increased risk of any arrhythmias (ROR=1.68, p<0.001). Axi-cel was associated with higher odds of developing orthostatic hypotension (ROR=2.57, p=0.019). Conclusion: This post-marketing pharmacovigilance analysis highlights patterns of cardiac AEs following CAR-T therapy. Trends in AEs based on CAR-T product, age, and sex support the ongoing need for vigilance for these unique toxicities. As this study is limited by FAERS reporting bias, prospective studies to validate these associations and elucidate the underlying mechanisms are needed, incorporating prior systemic therapies and baseline characteristics of patients undergoing CAR-T therapy.

Abstract Background: Dissemination and implementation science (D+I) efforts often begin after clinical trial (CT) efficacy data are available. However, delaying this work limits opportunities to identify barriers and facilitators that can enhance adoption of evidence-based practices. Integrating D+I during trial development, activation, and conduct supports more timely, effective, and scalable implementation. The Blood and Marrow Transplant Clinical Trials Network (BMT CTN) includes >125 centers, conducting transplant and cellular therapy (TCT) trials with practice-changing potential, with >17,000 patients enrolled since 2001. Data from Center for International Blood and Marrow Transplant Research (CIBMTR) provides a way to measure real-world adoption. With this comprehensive structure in place, the BMT CTN launched a D+I Committee that established a D+I process to better understand uptake of CT findings and to leverage that information to promote adoption. Methods: Informed by established D+I frameworks, a structured, cyclical process to integrate implementation considerations spanning the CT lifecycle was developed. A multidisciplinary team including experts in D+I, clinicians, and investigators iteratively refined the proposed D+I algorithm. The process begins upstream when a trial concept is approved to move forward, it is shared with the D+I Committee for initial assessment. This includes a landscape review for studies in development using CIBMTR data, literature, and expert experience. The Committee then reviews the developing protocol with the BMT CTN protocol team to proactively identify implementation barriers and facilitators to implementation in real-world settings and outline plans for dissemination. The Committee also provides recommendations for integrating relevant implementation data collection and analyses within the protocol. After study completion, both clinical efficacy and implementation outcomes are analyzed, followed by active dissemination. Additional assessment using surveys, qualitative methods, and CIBMTR data occurs after dissemination to understand adoption. Insights gathered also inform further refinement of the process. Tools and templates are in development to build capacity and ensure consistency for Committee members. Results: To date, the Committee has published three peer-reviewed articles addressing implementation implications of three BMT CTN trials (PMC7735536, PMC8578257, PMC9364468) and a fourth is in press. Using the designed D+I process flow, a current effort used a survey sent to US CIBMTR centers, to evaluate factors influencing the implementation of results of the BMT CTN 1703 trial of post-transplant cyclophosphamide as graft-versus-host disease (GvHD) prophylaxis and assessed dissemination and adoption considerations for the upcoming BMT CTN 2203 CT of ruxolitinib as GvHD prophylaxis. CIBMTR data is being analyzed to demonstrate practice patterns before, during, and after BMT CTN 1703 study completion. This effort has allowed for further refinement of the BMT CTN D+I process flow and has highlighted critical opportunities for incorporating dissemination and implementation objectives and endpoints into BMT CTN protocols. We also used the process to guide a review of severe aplastic anemia treatment gaps and ongoing studies. This review underscored how proactive transplant and non-transplant stakeholder engagement and early implementation planning, core elements of this process, can bridge evidence to practice and advance access to care. A complementary survey on current practice patterns in severe aplastic anemia is ongoing. Conclusions: With the existing structure of the BMT CTN and associated practice registry of the CIBMTR, the BMT CTN D+I Committee developed a systematic process to build D+I considerations into trial workflows to increase real-world impact. This process aims to ensure that barriers to uptake of trial results can be identified and addressed appropriately, improving care quality for patients undergoing TCT.

Abstract Background: Prolonged cytopenias are a well-recognized complication following CAR-T therapy, leading to increased morbidity and healthcare utilization. Autologous SCB offers a potential strategy to promote hematologic recovery. We conducted a retrospective multi-institutional analysis across 18 centers comparing outcomes of SCB versus supportive care alone in RRMM patients who experienced prolonged cytopenias >30 days after CAR-T infusion. Methods: Patients were included if they received SCB within 1 year after commercial CAR-T between 6/2021 and 3/2024. To identify matched controls, we reviewed other CAR-T recipients from the same consortium and selected those with an absolute neutrophil count (ANC) of <0.72x109/L and platelet count of <21K at day 30 post-infusion-thresholds representing the 75th percentile of cytopenia severity in the SCB cohort. These criteria ensured control patients had comparable hematologic toxicity but without SCB. Hematologic recovery in the SCB cohort was assessed using the CIBMTR engraftment criteria. For the non-SCB (nSCB) group, cell counts were analyzed cross-sectionally at day 90 post-CAR-T and compared to the SCB cohort with Kruskal Wallis tests. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan Meier methods. Results: Of the 590 CAR-T recipients, 91 patients (15.4%) developed prolonged cytopenias; 39 patients received SCB and 52 did not. SCB patients more frequently had ISS stage III disease (23.1% vs. 11.5%), exrtamedullary disease (59% vs. 46.2%) and penta-refractory status (43.6% vs. 34.6%). The median number of prior lines of therapy was 6 in both cohorts. Thirteen patients (33.3%) in the SCB and 11 (21.2%) in the nSCB received high intensity infusional chemotherapy (DCEP/PACE/HyperCVAD). Pre-CAR-T cytopenias tended to be less frequent in the SCB vs. nSCB cohort: ANC <1000 in 5.1% vs. 13.5%, Hgb <8 in 23.1% vs. 21.2%, and platelets <50K in 28.2% vs. 40.4%. Median plasmacytosis in the bone marrow prior to CAR-T in the SCB group was 35% and 47.5% in the nSCB group. In the SCB cohort, 2 patients harbored DNMT3A mutations, one of whom had CCUS. Ide-cel was administered in 64.8% and cilta-cel in 35.2% of all patients. The rates and grades of cytokine release syndrome did not differ between groups. Six patients (15.4%) had HLH in the SCB group vs. none in the control group. All (100%) SCB patients received growth factor support; 58% also received TPO agonists. In the nSCB group, 43 patients (82.7%) received growth factor, and 16 patients (30.8%) received TPO agonists. Out of 24 pre-SCB bone marrow biopsies available, only 1 patient had relapsed MM while the remainder had hypocellular marrows. Median CD34+ cell dose was 2.93 million/kg (range: 1.76-23.55) administered at a median of 53 days post-CAR-T (range 24-265). All but one patient (97.4%) in the SCB group achieved hematologic recovery; median time to recovery was 24 days (range 9-87). No new toxicities attributable to SCB were observed. On day 90 post CAR-T infusion, SCB patients had higher median ANC (2.12 vs. 1.59x109/L, p=0.277), Hgb (10.6 vs. 8.7g/dL, p=0.002), and platelet counts (135 vs. 35K/L (p<0.001). Minimal residual disease negativity was achieved in 82.4% (SCB) vs. 83.3% (nSCB). Infections occured in 53.8% and 48.1% of SCB and nSCB cohorts. All serious infections occurred prior to SCB. There were 12 deaths in the SCB group (7 from disease progression, 2 from infection, 1 from neurotoxicity (NT), and 1 unknown) and 27 in the nSCB group (22 from progression, 3 from infection, 1 from HLH, 1 from NT). After a median follow-up period of 12.6 months in the SCB cohort and 11.6 months in the nSCB arm, the mPFS was 11.0 months and 8.2 months, respectively. The mPFS was 10.6 months (SCB) and 5.8 months (nSCB) (p=0.216), and 11.0 months (SCB) and 10.9 months (nSCB), for ide-cel and cilta-cel treated-patients, respectively. Median OS was not reached vs.12.3 months in the SCB vs. nSCB groups, respectively. Conclusion: Overall, SCB was safe and effective in promoting rapid hematologic recovery in nearly all patients. Compared to controls, SCB recipeints had significantly higher Hgb and platelet levels by day 90 post-CAR-T infusion. SCB was associated wih a near doubling of PFS in patients who received ide-cel, though interpretation is limited by non-randomized design and small sample size. Further study is needed to optimize paient selection, timing, and integration of SCB into CAR-T care.

Abstract Introduction: Ciltacabtagene autoleucel (cilta-cel) has shown high efficacy in relapsed MM, but further efforts are needed to mitigate non-ICANS delayed neurotoxicity (DNT) and non-relapse mortality (NRM). Identifying risk factors associated with DNT and NRM may help with risk mitigation by aiding the development of interventions for potentially modifiable risk factors and also help with clinical decision making. Methods: In this multi-center retrospective study from the US MM Immunotherapy Consortium, we evaluated 761 patients treated at 15 centers receiving standard of care cilta-cel for relapsed MM between May 2022 to December 2024. Risk factors for DNT, particularly Parkinsonism and NRM were evaluated in by univariable and multivariable analysis. Any NRM events occurring after disease progression were censored for NRM evaluation. Results: The median age of the cohort was 65 years old (range: 30-88), median prior lines of therapy (pLoT) were 5 (range: 1-23). Cilta-cel was used in earlier relapse (1-3 pLOT) in 16% (n=120) patients. High-risk cytogenetics [del 17p, t(14;16) or t(4;14)] were present in 39%, with extramedullary disease (EMD) in 27% and R-ISS stage III in 18% of patients, respectively. Majority of patients (86%) received bridging therapy with response to bridging (≥ partial response, PR) seen in 33% of patients, respectively. Median follow up was 10.1 months, with response rate of 92% and CR rate of 70%. DNT was seen in 10% (n=75) of patients, with distribution as follows: Parkinsonism in 2.9% (n=22), cranial nerve palsy in 4.6% (n=35) and other DNT in 2.4% (n=18), with some patients manifesting more than one type of DNT. Risk of DNT was higher in patients who did not respond to bridging therapy (Any DNT: 12% vs 6%; Parkinsonism: 5% vs 0.5%, both p<0.05) Of the 22 cases of Parkinsonism, 21 patients (95%) did not respond to bridging, even though they achieved a post CAR-T response with ORR of 91% and ≥ CR in 68%. Absolute lymphocyte count (ALC), a surrogate measure of CAR expansion was higher in patients who developed DNT, particularly Parkinsonism, including ALC at days 7,14,21,28 and as peak ALC in the first month post cilta-cel (p<0.05 for all). Median peak ALC for patients with vs without Parkinsonism was: 5.88 vs 1.17/uL (p<0.001). We evaluated risk of Parkinsonism with various thresholds of peak ALC expansion. Amongst patients who developed Parkinsonism vs. not, peak ALC was as follows, > 1000/uL: 100% vs 57%, > 2500/uL: 73% vs 19% and > 3000/uL: 68% vs 14% (all p<0.001). The absolute risk of Parkinsonism with ALC > 3000 vs ≤ 3000/uL was 12% vs 1%, p<0.001; for ALC 2500 vs ≤ 2500uL was 9% vs 1%, p<0.001. On multivariable analysis, peak ALC > 3000/uL (OR: 12.7, p<0.001) and non-response to bridging therapy (OR: 9.9, p=0.03) were independent risk factors for developing Parkinsonism after cilta-cel. After cilta-cel, 1 and 2 year NRM estimates were 9% and 10%, respectively. Amongst 63 (8%) patients experiencing NRM events, the most common cause of NRM was infectious complications (35, 56%), followed by acute immune-mediated adverse events (AEs) like CRS, ICANS, IEC-HS in 14 (22%), delayed immune mediated AEs like DNT and colitis in 6 (9.5%), second cancers in 5 (8%) and other causes in 3 (5%) patients, respectively. When evaluating the timing of NRM events, the risk of infection related mortality remained relatively stable in the first year, though immune mediated toxicty deaths were uncommon after 6 months, while SPMs were uncommon within the first 6 months. On multivariable analysis, non-response to bridging (HR 2.41, p=0.046), poor performance status ≥ 2, high-risk cytogenetics and age ≥ 70 years were independent predictors for NRM. Conclusion: In a large cohort of over 750 patients receiving cilta-cel, we identified potentially modifiable risk factors for Parkinsonism and NRM. Non-response to bridging therapy and peak ALC > 3000/uL were independent predictors of developing Parkinsonism. Peak ALC of > 2500/uL and > 3000/uL were associated with 9% and 12% absolute risk of Parkinsonism. This indicates that peak ALC of 2500/uL or 3000/uL in the first month after cilta-cel may be a potential biomarker to identify patients for pre-emptive interventions such as steroids that can suppress rapid CAR expansion and perhaps decrease the risk of Parkinsonism. In addition, we need to focus on effective bridging strategies to further decrease the risk of Parkinsonism, as well as NRM with cilta-cel.

Abstract Introduction Marginal zone lymphoma (MZL) is an indolent and heterogenous disease. Several prognostic models have been proposed to assess outcomes in MZL, including FLIPI, IPI (primarily designed for overall survival [OS]), and MZL-specific scores such as MALT-IPI (event-free survival [EFS]) and MZL-IPI (progression-free survival). FLIPI24 is a recently developed prognostic index for patients with follicular lymphoma (FL) treated with first-line (1L) immunochemotherapy (IC), identifying a high-risk population with inferior survival and increased risk of lymphoma-related death. FLIPI24 has also demonstrated robust performance in the entire FL population, including patients under observation. This study aimed to evaluate the prognostic utility of FLIPI24 in patients with MZL and to compare its performance with other established indices (FLIPI, MZL-IPI, IPI, MALT-IPI). Methods We pooled harmonized data from newly diagnosed MZL patients with complete available FLIPI24 variables (age, white blood cell count [WBC], hemoglobin [HGB], serum lactate dehydrogenase [LDH], and beta-2-microglobulin [B2M] levels) treated with 1L IC. Data were collected from three prospective international cohorts: NiHiL (Czech Republic; n=897; enrolled 2005–2023), LEO (USA; n=62; 2015–2020), and MER (USA; n=32; 2010–2015), forming a pooled cohort of 991 1L IC-treated patients. The analysis was then extended to include all newly diagnosed MZL patients (n=2,116), regardless of treatment. The primary endpoint in the 1L IC-treated cohort was EFS at 24 months (EFS24), and for all MZL patients, it was OS. Secondary endpoints included OS24 for 1L IC treated cohort, lymphoma-related mortality by FLIPI24 risk groups, and comparative prognostic performance of FLIPI, IPI, and MALT-IPI, by C-statistics; performance of MZL-IPI was assessed on a subgroup of NiHiL patients with available data (n=877 all MZL, n=485 1L IC-treated). Results Among the 991 1L IC-treated patients, the median age at diagnosis was 66 years (range 22–94); 47% were male; 11% had ECOG performance status ≥2, 68% clinical stage III–IV, 42% elevated LDH, 40% IPI 3–5, 42% FLIPI 3–5, and 62% MALT-IPI 2–3. The median B2M level was 2.8 mg/L, WBC 7.0 × 10⁹/L, and HGB 13.1 g/dL. MZL subtypes were: 64% extranodal (EMZL), 22% nodal (NMZL), and 14% splenic (SMZL). Most common 1L IC regimens were R-CVP (46%), R-CHOP-like (32%), R-chlorambucil (9%), and B-R (9%). FLIPI24 stratified patients into low- (18%), intermediate- (37%), and high-risk (45%) groups. High-risk patients were older (median 54 vs 65 vs 71 years for low-, intermediate-, and high-risk groups, respectively; P<0.01), had more frequent adverse baseline features, and were more likely to have the SMZL subtype (2% vs 7% vs 25% for low-, intermediate-, and high-risk groups, respectively; P<0.01). After a median follow-up of 7.2 years, EFS24 was 89%, 85%, and 65% (P<0.01) across low-, intermediate-, and high-risk groups; OS at 2 years was 98%, 97%, and 79%; and OS at 5 years was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 13% in high-risk vs 6% in low-/intermediate-risk groups. FLIPI24 showed better prognostic accuracy for EFS compared with FLIPI, MZL-IPI, IPI and MALT-IPI (C-index: 0.640 vs 0.630, 0.622, 0.620 and 0.603, resp.), as well as for OS (C-index: 0.710 vs 0.672, 0.641, 0.663, 0.652, resp.). Prognostic performance was consistent across MZL subtypes. In the extended cohort of 2,116 newly diagnosed MZL patients (47% receiving IC, 17% rituximab monotherapy, 11% radiotherapy, 8% surgery, 2% antibiotics; 15% observed), FLIPI24 stratified patients into low- (24%), intermediate- (39%), and high-risk (37%) groups. OS at 2 year was 99%, 97%, and 83%, at 5 years it was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 12% in high-risk vs 4% in low-/intermediate-risk patients. FLIPI24 outperformed other indices (OS C-index: 0.754 vs MZL-IPI 0.654, FLIPI 0.700, MALT-IPI 0.694, IPI 0.699). Conclusion FLIPI24 demonstrates strong and consistent prognostic performance across all MZL subtypes, identifying ~40% of patients as high-risk with significantly worse survival and increased lymphoma-related mortality. The FLIPI24 outperforms FLIPI, MZL-IPI, IPI, and MALT-IPI in predicting outcomes and may serve as a practical tool to guide risk-adapted management and selection of patients for novel therapies in MZL. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.

Abstract Introduction Ciltacabtagene autoleucel (cilta-cel) has demonstrated unprecedented response rates and progression-free survival (PFS) in relapsed/refractory multiple myeloma (RRMM), but a proportion of patients experience early relapse. Identifying these patients is essential to guide future therapeutic strategies, such as enhanced bridging therapy or consolidation, while avoiding overtreatment in those likely to achieve durable disease control. Methods We conducted a multi-center study of patients treated with cilta-cel at 15 U.S. academic centers. Outcomes were evaluated based on high-risk (HR) features, including functional HR disease (FHR; relapse within 18 months of first-line therapy initiation), true extramedullary disease (EMD), traditional HR cytogenetics as defined in CARTITUDE-1 [deletion 17p, t(4;14), t(14;16)], and a 2024 IMS-IMWG-adapted HR definition (deletion 17p; t(4;14) or t(14;16) with gain 1q or deletion 1p; and gain 1q with deletion 1p). Multivariable Cox regression was used to examine the association of HR features (FHR, adapted IMS-IMWG HR, and EMD, individually and collectively) with PFS while adjusting for baseline ferritin, prior BCMA, and ECOG performance status (PS ≥2). Among patients with ≥18 months of follow-up, we evaluated predictors of early relapse (≤18 months post infusion) using logistic regression. Results Our cohort included 598 patients treated with cilta-cel between 5/2022 and 12/2024 who had available data on all HR features. The median age was 65 years (range 33-83), and the median prior lines of therapy (pLOT) was 5 (range: 1-18, 84% with >3 pLOT); 8% had received prior BCMA-directed therapy, and 27% were penta-refractory. Most patients (88%) received bridging therapy and 30% achieved ≥ partial response. In our cohort, 33% (n=195) had FHR, 43% (n=258) had traditional HR cytogenetics, 42% (n=253) had adapted IMS-IMWG HR disease, and 11% (n=64) had EMD. Median follow up was 10.6 months (range 0.4-34.1). Overall response rate (ORR) and complete response (CR) rates were lower in patients with vs without HR features: FHR (ORR: 89% vs 94%, CR: 61% vs 75%), traditional HR (ORR: 90% vs 94%, CR: 65% vs 74%), adapted IMS-IMWG HR (ORR: 91% vs 94%, CR: 64% vs 75%) and EMD (ORR: 77% vs 94%, CR: 61% vs 71%). Corresponding 12-month PFS was also lower in patients with vs without HR features: FHR (55% vs 79%), traditional HR (63% vs 78%), adapted IMS-IMWG HR (61% vs 80%) and EMD (59% vs 73%). ORR, CR rate, and 12-month PFS in patients without any HR features compared to those with ≥1 HR feature were 96% vs 90%, 81% vs 64%, and 83% vs 65%, respectively. In multivariable models, each HR feature (FHR, adapted IMS-IMWG HR, and EMD) was independently associated with inferior PFS after adjusting for baseline ferritin, prior BCMA, and ECOG PS ≥ 2. However, because early relapse cannot always be identified a priori based on traditional risk factors, we sought to identify predictors of relapse within 18 months of cilta-cel in a subset of patients with ≥18 months of follow-up (N=247; infused by 12/2023). Notably, while FHR (OR=3.04, 95% CI=1.59-5.89) and adapted IMS-IMWG HR (OR=2.07, 95% CI=1.10-3.89) were independently associated with odds of relapse within 18 months, EMD was not (OR=0.90, 95% CI=0.32, 2.40) when accounting for prior BCMA, ECOG PS ≥ 2, and baseline ferritin. We also used a time-varying Cox model to examine each HR feature associated with PFS at two time periods, <18 and ≥18 months, while adjusting for baseline ferritin, ECOG PS, and prior BCMA. We confirmed that FHR and adapted IMS-IMWG HR were both associated with relapse <18 months (HR=2.05, 95% CI=1.48-2.83 and HR=1.56, 95% CI=1.11-2.19) but not in the ≥18-month time period (HR=0.70, 95% CI=0.19-2.59 and HR=0.76, 95% CI=0.24-2.40). The magnitude of the association for EMD with PFS was similar across both time periods (<18 months HR=1.67, 95% CI=1.09-2.57 and ≥18 months HR=2.17, 95% CI=0.45-10.40). Conclusion While cilta-cel leads to high response rates and durable PFS in RRMM, a subset of patients with FHR and adapted IMS-IMWG HR remains at increased risk for early relapse. In this large multi-center cohort, we describe PFS outcomes across high-risk subgroups and identify key predictors of relapse within 18 months of cilta-cel. These findings inform risk-adapted therapeutic strategies and interventional trials, including bridging, consolidation, or maintenance approaches, to improve outcomes in the highest-risk RRMM patients.