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Abstract Introduction: Ciltacabtagene autoleucel (cilta-cel) is a highly effective BCMA-redirected CAR T-cell therapy for RRMM. While the pivotal CARTITUDE-1 trial established a target dose of 0.75 x 10^6 CAR+ viable T-cells/kg, the approved cell dose is 0.5-1.0 x 10^6 and the optimal dosing strategy to balance efficacy and toxicity remains unclear. This question is of interest given that a dose-response association has been demonstrated for idecabtagene vicleucel (a related BCMA-directed CAR T product). It has also been hypothesized that lower doses of cilta-cel may be associated with reduced toxicity. This study aims to evaluate the association between cilta-cel dose and key efficacy and toxicity outcomes using a large, real-world dataset from the US Multiple Myeloma Immunotherapy Consortium. Methods: We conducted a multicenter, retrospective analysis of 751 RRMM patients treated with commercial cilta-cel across 15 US academic centers. The administered cilta-cel dose (million cells/kg) was categorized into four groups: low (<0.5), standard-low (0.5 to <0.6), standard (0.6 to <0.8), and standard-high (0.8 to 1.0). We compared incidence rates of cytokine release syndrome (CRS), immune effector cell-associated neurotoxicity syndrome (ICANS), delayed neurotoxicity (DNT), and immune effector cell-associated hemophagocytic lymphohistiocytosis-like syndrome (IEC-HS) across these dose categories using logistic regression. Best response rates and progression-free survival (PFS), estimated using the Kaplan-Meier method, were also compared, with differences assessed using the log-rank test for the latter. Results presented are derived from multivariable models adjusting for extramedullary disease, ECOG status, penta-refractory disease and receipt of bridging therapy. Results: Among 751 infused patients, the dose distribution was: <0.5 (n=33), 0.5 to <0.6 (n=131), 0.6 to <0.8 (n=550), and 0.8 to 1.0 (n=37). The four dose groups were well-balanced in terms of baseline patient and disease characteristics, including age, high-risk cytogenetics, and extramedullary disease, with the exception of t(14;16), which was more common in the standard-low and standard dose groups (p=0.006). There were no statistically significant differences in the rates of any grade CRS (p=0.11), any grade ICANS (p=0.84), grade ≥3 ICANS (p=0.36), duration of CRS (p=0.18) or ICANS (p=0.64), or IEC-HS (p=0.16) across the four dose categories. Time to onset of CRS was shorter for the standard-high dose compared to the low dose (6 days vs. 8 days; p=0.08). Importantly, there was no significant difference in the rate of DNT (3.0%, 9.2%, 8.8%, 5.4%; p=0.24). Similarly, there was no significant difference in overall response rates (97%, 96%, 96%, 88%; p=0.50) or complete response rates (75%, 65%, 75%, 66%; p=0.10) by dose. The median follow-up was 12.3 months (IQR: 6.9, 20.5). For patients who received a standard-low dose (0.5, 0.6), the median PFS was 17.5 (IQR: 13.5, NR) months. For the standard dose range of (0.6, 0.8), the median PFS was 28.7 (95% CI: 19.8, NR) months, while the median PFS for the standard-high dose (0.8, 1.0) was not reached. For the low dose range of <0.5, the median follow up was only 8.7 months, which did not allow reliable estimation of the median PFS. While the overall difference in PFS among the groups did not reach statistical significance by the log rank test, there was a clear trend toward improved PFS with higher cell doses in the multivariable model, with outcomes clearly ordered in the same direction as the cell dose categories. A similar trend was also evident in the rates of 12-month PFS which showed an improvement with increasing dose (62% ,67%, 73%, 80%). Conclusions: In this large, real-world cohort of RRMM patients treated with cilta-cel, a lower cell dose was not associated with reduced incidence or severity of CRS, ICANS, DNT, or IEC-HS. Conversely, a dose-response correlation with PFS was observed, with higher doses trending toward longer median and 12-month PFS. It remains unknown if a lower cell dose in the commercial setting reflects poor T cell quality, yet these findings suggest that dose reduction of cilta-cel may not be an effective strategy to mitigate toxicities and might be associated with a trend toward lower efficacy. Therefore, the standard target dose should be utilized to maximize patient outcomes and further prospective dose exploration is warranted.

Abstract Introduction: Elranatamab, a BCMA-CD3 bispecific antibody, has shown efficacy in relapsed multiple myeloma (MM), but real-world data on its safety and effectiveness are limited. Methods: We conducted a retrospective, multi-center study of patients (pts) treated with commercial elranatamab from 8/2023–3/2025 at 9 U.S. academic centers. Logistic and Cox regression were used for binary and time-to-event outcomes, respectively. Multivariable analysis (MVA) adjusted for prior lines of therapy (LOTs), baseline Hgb (per g/dL), and LDH (per 100 U/L) as continuous variables; and for BCMA exposure, extramedullary disease (EMD; extraosseous soft tissue lesions), and ECOG ≥2 as binary variables. Results: Of 130 pts, median age was 71 yrs (range 39–95); 57% were female, 82% white, 13% black, and 35% had ECOG ≥2 (11% ≥3). Median LOTs was 6; 91% were triple-class refractory, 49% penta-refractory, 49% BCMA-exposed (median 15.5 mo [IQR 11.8–20.5] since last exposure), and 49% had prior anti-BCMA CAR-T. Most recent BCMA exposures included: CAR-T (84%), TCE (9.4%), and ADC (6.3%). Only 22% met MagnetisMM-3 cohort A eligibility (which excluded BCMA-exposed pts). High-risk cytogenetics (del(17p), t(4;14), t(14;16), or amp(1q)) were present in 44% (25%, 13%, 6.3%, and 7.9%, respectively). EMD was seen in 22%. Median treatment duration was 4.0 mo (95% CI 2.93–6.3) overall and 7.9 mo (95% CI 5.83–NA) with ≥VGPR. Discontinuation due to toxicity or non-relapse mortality occurred in 12% but was significantly lower among those receiving IVIg (5% vs. 17%, p=0.031); IVIg was given in 47%. The overall response rate (ORR) was 65%, including ≥VGPR in 46% and ≥CR in 36%, consistent with MagnetisMM-3 (ORR 61%, ≥CR 35%; Lesokhin et al. Nat Med. 2023). After median follow-up of 7.5 mo, median PFS was 4.3 mo (95% CI 3.4–11.3), OS was 14.6 mo (95% CI 8.6–NA), and DOR was 12.2 mo (95% CI 6.1–NA). In contrast, MagnetisMM-3 (Prince et al., ASH 2024) reported median PFS and OS of 17.2 and 24.6 mo, respectively, with DOR not reached despite 28.4 mo of follow-up. In univariate analysis, ECOG ≥2 was associated with lower ORR (45% vs. 71%; OR 0.34, 95% CI 0.16–0.73, p=0.006), shorter OS (4.3 mo vs. NA; HR 2.41, 95% CI 1.33–4.35, p=0.004), and shorter PFS (1.7 vs. 6.5 mo; HR 1.77, 95% CI 1.09–2.87, p=0.020). Prior BCMA-directed therapy was linked to reduced odds of ≥VGPR (OR 0.38, 95% CI 0.19–0.77, p=0.008) and ≥CR (OR 0.43, 95% CI 0.20–0.89, p=0.025). Higher baseline LDH was linked to shorter OS (HR 1.37, 95% CI 1.23–1.53, p<0.001) and PFS (HR 1.31, 95% CI 1.18–1.44, p<0.001). Higher baseline Hgb was associated with higher ORR (OR 1.46, 95% CI 1.20–1.81, p<0.001) and ≥CR (OR 1.54, 95% CI 1.26–1.92, p<0.001). Among BCMA-exposed pts, recent exposure (<1 [n=15] vs. ≥1 yr [n=32]) was associated with shorter OS (4.1 mo vs. NA; HR 3.66, 95% CI 1.26–10.6, p=0.017). In MVA, higher baseline LDH remained independently associated with shorter OS (aHR 1.36, 95% CI 1.19–1.54, p<0.001) and PFS (aHR 1.27, 95% CI 1.13–1.43, p<0.001); higher Hgb with greater odds of ≥CR (aOR 1.44, 95% CI 1.14–1.85, p=0.003) and longer PFS (aHR 0.84, 95% CI 0.72–0.99, p=0.034); and BCMA exposure with lower odds of ≥CR (aOR 0.32, 95% CI 0.10–0.91, p=0.037). CRS occurred in 40% (grade ≥2 in 12.3%, grade 3 in 2.3%), and ICANS in 17% (grade ≥2 in 7.7%). These rates contrast with MagnetisMM-3 (no grade ≥3 CRS, 3.4% ICANS). ICANS risk was lower in BCMA-exposed pts (9.4% vs. 24%; OR 0.32, 95% CI 0.11–0.85, p=0.029), and decreased with more LOTs (OR 0.73, 95% CI 0.55–0.92, p=0.016) and higher Hgb (OR 0.71, 95% CI 0.52–0.94, p=0.023). Tocilizumab and steroids were used in 36% (treatment 28%, prophylaxis 9.2%) and 23%, respectively. Steroid use was less common in BCMA-exposed pts (11% vs. 34%; OR 0.23, 95% CI 0.08–0.60, p=0.004) and declined with more LOTs (OR 0.68, 95% CI 0.52–0.85, p=0.002). Infections occurred in 40% of the cohort, more common in pts with CrCl <40 mL/min (59% vs. 36%; HR 2.58, 95% CI 1.02–6.80, p=0.049). IVIg was linked to improved infection-free survival (HR 0.59, 95% CI 0.37–0.93, p=0.023). Conclusions: Elranatamab demonstrated meaningful activity in real-world relapsed MM, though PFS and OS were shorter than in MagnetisMM-3, likely reflecting an older, frailer population with higher disease burden. ICANS was more frequent than in MagnetisMM-3. Baseline anemia and elevated LDH, markers of poor marrow reserve and higher disease burden, were strongly linked to worse outcomes.

Abstract Introduction: The real-world outcomes in patients (pts) with PCALCL in the era of targeted therapies like Brentuximab Vedotin (BV) is not well defined due to lack of large multicenter studies. We conducted a multicenter retrospective analysis (RWA) to assess patient and disease characteristics, treatment patterns, survival outcomes and impact of novel therapies in this rare type of cutaneous T cell lymphoma (CTCL). Methods: The analysis included 167 adult (≥18 years) patients (pts) with PCALCL across 9 academic institutions in the United States diagnosed between 01/2012 to 06/2022. The study was approved by the Institutional Review Boards at the respective sites. Demographic and disease factors were summarized using descriptive statistics. Overall survival (OS) and relapse-free survival (RFS) were estimated using Kaplan-Meier method and compared via log rank tests. Prognostic models included factors such as age, sex, race, performance status (PS), disease stage, type of initial lesion, presence of B symptoms, previous history of lymphomatoid papulosis and prior transplant. Prognostic factors for survival were assessed using both univariable and multivariable Cox proportional hazard models. Results: The median age at diagnosis was 61 (range 18-93) years. The majority of pts were male (55%) and white (82%), with good PS as indicated by an ECOG 0-1 (71%). The initial skin presentation consisted of tumors in 62% of the pts, while 34% presented with plaques or patches. Notably, no pts presented with erythroderma. Most pts underwent PET scan for staging at initial diagnosis (83%) with the majority having early-stage (IA-IIA) disease (86%). Furthermore, palpable lymph nodes (11%) and the presence of B symptoms (4%) were rare at diagnosis, and no pts had blood involvement. The most common sites of involvement were extremities (33%) followed by the head and neck (H&N) and trunk (31% each). Immunophenotyping revealed CD4 positivity in 59% of pts and CD8 positivity in 25%. The T cell receptor (TCR) rearrangement was positive in 28% of pts, though it was not completed in the majority of cases (72%). Most common initial treatments included localized radiation (61%) and surgical excision (19%). A small subset of pts received frontline systemic chemotherapy regimens such as cytotoxic chemotherapy (11%), BV (8%) and oral methotrexate (MTX) (8%). Approximately 7% of the pts had a stem cell transplant. Overall response rate (ORR) for radiation, oral MTX, BV and cytotoxic chemotherapy were 78% (CR:78% 74/100), 42% (CR:63% 6/12) and 39% (CR:67% 6/12), 89% (CR: 88% 15/18) respectively. At a median follow-up of 3.8 years (range 0.04-10.23), the median RFS and OS were 2.7 years (95% CI:1.86, 3.43) and 12 years (95% CI:10.6- NA) respectively. The estimated 3- and 5-year RFS are 46% (95% CI:0.38, 0.55) and 37% (95% CI:0.28, 0.46) respectively. The estimated 3- and 5-year OS were 89% (95% CI:0.82, 0.93) and 82% (95% CI:0.73, 0.88) respectively. At the time of the last follow-up, 79% were alive, while 21% were deceased. The cause of death (COD) was unknown in 50% of the cases and only 10% (3/of deaths were attributed to lymphoma. Other known CODs included infection (20%) and second malignancies 7%. On univariate analysis (UVA), age (p=.007), female sex (p=.04), ECOG PS 1-2 compared to 0 (p=.007) and prior transplant (p=.009) predicted for worse RFS. On multivariate analysis (MVA), only ECOG PS 1-2 (HR 2.31, 95 CI:1.06, 1.18, p=.009) and prior transplant (HR 5.38, 95 CI:2.30, 12.57, p=.0001) had a significant impact on RFS. Age and presence of B symptoms were strong predictors of OS on both UVA (age p=<.0001; B symptoms p=<.0001) and MVA (age: HR 1.12, 95 CI:1.06, 1.18, p=<.0001; B symptoms: HR 16.48, 95 CI: 3.69, 73.60, p=.0002). However, the impact of B symptoms should be interpreted with caution as only 4% of pts presented with this at baseline. On UVA, each one-year increase in age was associated with an 8.5% rise in the risk of death. ECOG PS 1-2 was associated with worse OS on univariate analysis (HR 2.62, 95% CI 0.99, 6.93, p=.05), but was not significant on MVA (HR 1.05, 95% CI 0.368, 2.974, p=.93). Conclusions: In this large RWA of PCALCL, excellent long-term survival was observed with predominantly skin directed frontline therapies. The use of systemic treatments, including BV, was infrequent as first line therapy. Older age and poor PS were significant predictors for reduced survival.

Abstract Background Previous studies in aggressive B-cell lymphoma demonstrate that patients with shorter diagnosis-to-treatment intervals (DTI) represent those with higher risk disease. This suggests that patients enrolled in clinical trials may carry a selection bias as they often have longer DTI than patients in the general population. This has important implications for clinical research design and the generalizability of clinical trials in aggressive lymphomas. However, the prognostic implications of DTI have not been evaluated in peripheral T-cell lymphomas (PTCL). Therefore, we examined DTI and its association with clinical factors and outcomes in a prospective observational cohort of patients with PTCL from the United States within the LEO (Lymphoma Epidemiology and Outcomes) and MER (University of Iowa and Mayo Clinic Specialized Programs of Research Excellence Molecular Epidemiology Resource). Patients and Methods We evaluated patients enrolled to the MER (2002-2015) and LEO (2015-2020) cohorts with the following forms of PTCL: PTCL-not otherwise specified (PTCL-NOS, n=217), nodal T-follicular helper (TFH) cell lymphoma (nTFHL, n=153), anaplastic large cell lymphoma (ALCL), ALK positive (ALCL, ALK+, n=74), ALCL, ALK negative (ALCL, ALK-, n=95), enteropathy associated T-cell lymphoma (n=18), and monomorphic epitheliotropic intestinal T-cell lymphoma (n=2). Associations of DTI with clinical factors and outcomes were examined using Kaplan Meier and Cox models. Event free survival (EFS) was defined as the time from start of treatment to relapse/progression, start of 2nd line therapy, or death from any cause. Overall survival (OS) was defined as the time from start of treatment until death from any cause. DTI was defined as the number of days between the first diagnostic biopsy and the start of therapy. Patients who were initially observed or had DTI > 100 days were excluded. Results In 559 patients (229 MER and 330 LEO), median age was 60, 34% had IPI>2 and 71% were stage III/IV. 472 (84%) patients initially received anthracycline-based chemotherapy. Median DTI was 23 days (interquartile range (IQR): 12-39) and was similar in MER (21 days, IQR: 11-33) and LEO (25 days, IQR: 14-42). 168 (30%) patients had DTI 0-14 days, 178 (32%) 15-28 days, and 213 (38%) 29-100 days. Overall in the cohort, shorter DTI was associated with a worse 5-year OS (DTI 0-14 days: 43%; DTI 15-28 days: 53%; DTI 29-100 days: 58%, p<0.001) and 5-year EFS (DTI 0-14 days: 31%; DTI 15-28 days: 39%; DTI 29-100 days: 45%, p<0.001). In multivariable analyses, the association of DTI with outcomes remained consistent after adjusting for age and International Prognostic Index (IPI). Shorter DTI was strongly associated with adverse clinical factors, including elevated lactate dehydrogenase levels, poor performance status, B-symptoms, and higher IPI in both cohorts (all P < .003). DTI was not associated with age, sex, or distance from the LEO/MER center (all p>0.3). 6% patients with DTI of 0-14 days received 1L treatment on a clinical trial, compared to 11% with DTI 15-28 days and 13% with DTI 29-100 days, underscoring that patients with lower DTI may be underrepresented in clinical trials. When examining within PTCL subtypes, the association between short DTI (0-14 days) and inferior outcomes was most prominent in PTCL, NOS (OS HR=2.13, 95% CI: 1.52-2.94; EFS HR =1.49, 95% CI: 1.19-1.85). Associations between short DTI and outcomes were weaker in other subtypes: nTFHL (OS HR=1.28, 95% CI: 0.83-2.00; EFS HR =1.22, 95% CI: 0.82-1.81), ALCL, ALK-, (OS HR=1.30, 95% CI: 0.59-2.86; EFS HR =1.32, 95% CI: 0.68-2.56), ALCL, ALK+, (OS HR=1.05, 95% CI: 0.26-4.17; EFS HR =2.12, 95% CI: 0.84-5.26). Conclusion Shorter DTI is associated adverse prognostic clinical factors (LDH, stage, high IPI) and inferior EFS and OS in newly diagnosed PTCL. Patients with DTI ≤ 14 days, which represents approximately 1/3 patients with PTCL, may be underrepresented in clinical trials. Understanding of this selection bias should inform clinical trial design and interpretation. Future studies should consider strategies to minimize barriers to enrollment for patients with low DTI.

Abstract Introduction: Outcomes for FL have markedly improved, and the 10-year (yr) overall survival (OS) for patients (pts) diagnosed in the rituximab era is about 80%. Historically, FL is the leading cause of death in the first decade after diagnosis (dx); however, modern outcomes beyond 10 yrs after dx remain unknown. Here we report long-term outcomes of FL from a large prospective cohort of pts with FL from the rituximab era. Methods: Pts with biopsy-proven FL 1-3A at dx were prospectively enrolled within 9 months of dx from 2002-2015 in the MER. Outcomes of interest were OS, event-free survival (EFS), histologic transformation (HT), and cause of death. HT was defined as subsequent biopsy-proven FL 3B, diffuse large B cell lymphoma, or high-grade B cell lymphoma. Analyses were performed using Cox models and KM curves; cause of death was evaluated using a competing risk approach. A subset analysis was performed in younger (18-59 yrs) vs older (60+ yrs) pts. A landmark analysis was conducted in pts alive at 10 yrs. Results: 1,155 pts with FL 1-3A were enrolled in the MER from 2002-2015. Median age at dx was 60 yrs (IQR 51-69). Clinical characteristics were: 67% stage III/IV, 12% grade 3A, 4% ECOG PS 2-4, and 19% elevated LDH. Initial management was 35% observation (obs), 12% R-monotherapy (R-mono), 39% immunochemotherapy (IC; 43% R-CHOP, 28% R-CVP, 27% BR), and 14% other. FLIPI scores were 40% low, 33% intermediate (int), and 27% high; FLIPI24 risk categories were 49% low, 25% int, and 26% high. At a median follow-up of 14 yrs (IQR 11-18 yrs), 751 events, 148 HTs, and 402 deaths were observed. EFS estimates (95% CI) were: 10-yr: 40% (37-43), 15-yr: 31% (28-35), and 18-yr: 27% (24-31). 15 yr & 18 yr EFS by initial txs were 22% (18-27) & 18% (14-25) for obs, 30% (23-40) & 18% (11-30) for R-mono, and 40% (35-46) & 38% (33-45) for IC. The incidence (95% CI) of HT was 12% (10-14) at 10 yrs, 13% (11-16) at 15 yrs, and 14% (12-17) at 18 yrs. OS (95% CI) for the entire cohort was 77% (75-80%) at 10 yrs, 63% (60-66) at 15 yrs, and 55% (51-59) at 18 yrs. The incidence of non-lymphoma-related death (non-LRD) surpassed lymphoma-related death (LRD) after 12 yrs in pts with known cause of death. Estimates (95% CI) for LRD were 11% (10-13) at 10 yrs, 14% (12-17) at 15 yrs, and 16% (14-19) at 18 yrs, while estimates for non-LRD were at 8% (7-10) at 10 yrs, 17% (15-20) at 15 yrs, and 22% (19-26) at 18 yrs. Among pts diagnosed before age 60, LRD remained the predominant cause of mortality into the second decade following dx, with incidences (95% CI) of LRD vs. non-LRD of 7% (5-9) vs 3% (2-4) at 10 yrs, 10% (8-13) vs 5% (3-8) at 15 yrs, and 13% (9-17) vs 6% (4-10) at 18 yrs, respectively. In patients age >60 non-LRD was the predominant cause of mortality in the second decade. Incidence of LRD vs. non-LRD in those aged ≥60 at dx were 15% (13-19) vs 13% (10-16) at 10 yrs, 18% (15-22) vs 28% (24-32) at 15 yrs, and 20% (16-24) vs 35% (31-41) at 18 yrs, respectively. In the landmark analysis of pts alive at 10 yrs from dx (n=720), median age was 69 yrs (IQR 60-77). 63 pts (9%) had HT prior to landmark. The median number of prior treatments was 1 (IQR 1-2, range 1-8). Risk of death (95% CI) was 19% (15-22) in the next 5 yrs (i.e. 15 yrs from dx) and 29% (24-33) in the next 8 yrs (18 yrs from dx). The risk of LRD vs non-LRD was 4% (3-6) vs 12% (9-15) at 5 yrs and 7% (3-9) vs 18% (10-23) at 8 yrs.Conclusions: Long-term outcomes for pts with FL remain excellent into the second decade from dx. HT risk decreases significantly after 10 yrs, though late HTs still occur. At 15 yrs from dx, 40% of pts remained alive and event-free after 1L IC. Nearly a quarter of pts observed at dx remained treatment-free. The most common cause of death after 10 yrs from dx was from non-lymphoma causes, notably in older pts aging into their 70s and 80s. While younger pts have a lower overall risk of LRD compared to older pts, FL represents the leading cause of death in this population during the second decade following dx. These results provide critical insights into the natural history of FL diagnosed in the modern era.

Abstract Background: Real-world data suggest that safety and efficacy of ide-cel and cilta-cel mirror data from pivotal trials, yet older adults remain underrepresented. We report outcomes of the largest cohort of RRMM patients aged ≥75 years receiving CAR-T and compare them with propensity-matched younger patients. Methods: We retrospectively analyzed RRMM patients receiving standard-of-care BCMA CAR-T at 15 centers from the US Myeloma Immunotherapy Consortium between May 2021 and December 2024. Patients ≥ 75 years were 2:1 propensity-matched to patients < 75 based on CAR-T product, sex, performance status, extramedullary disease, baseline ferritin, penta-refractory status, bridging therapy, prior autologous SCT and lines of therapy. Continuous outcomes were analyzed with multivariable linear regression, binary outcomes with logistic regression, and time-to-event endpoints with Cox proportional-hazards models. We estimated average treatment effects via G-computation, using cluster-robust standard errors to account for the matched sets. Results: After 2:1 propensity matching, the cohort included 194 patients ≥ 75 years (cilta-cel: 64 and ide-cel: 130) and 388 patients < 75 years (cilta-cel: 128, ide-cel: 260). Median ages were 78 (range: 75-90) for the older cohort vs 65 (range: 35-74) for the younger cohort. The older cohort had a higher frequency of t(14;16) (9% vs. 3%, p = 0.005), lower baseline ferritin (151 vs. 196 ng/mL, P = 0.046), and lower likelihood of prior ASCT (57% vs. 71%, P = 0.001). Median prior lines of therapy were 5. Median follow-up time for ≥ 75 and < 75 groups for cilta-cel was 11.5 and 11 months and for ide-cel was 16 and 24.3 months, respectively. ORR did not differ amongst the older vs younger patients: cilta-cel (97% vs. 97%) and ide-cel (90% vs. 88%).For patients ≥ 75 years, median PFS with cilta-cel was 28.7 months (95% CI: 13.3–NR) and with ide-cel was 16.4 months (95% CI: 12.1–22.4). In patients < 75 years, median PFS was not reached for cilta-cel but was 11.5 months (95% CI: 9.6–12.7) for ide-cel, reflecting inferior PFS with ide-cel in the younger group (HR 0.4, 95% CI 0.3–0.6). On sensitivity analysis by Cox proportional hazards model, we did not observe any statistically significant differences in PFS in older vs younger patients receiving cilta-cel, although older patients paradoxically had better PFS with ide-cel compared to their matched younger cohort. In the cilta-cel cohort, HR for PFS for older vs younger patients was 1.48 (95% CI:0.77-2.84; p=0.2) and in the ide-cel cohort it was 0.7 (95% CI: 0.5, 0.98; p=0.04). Median OS was reached only in the < 75-year ide-cel cohort at 40 months (95% CI: 32.5–43.5). Rates of CRS were similar, with any-grade (grade ≥3) CRS seen in 74% vs 78% (0% vs. 0.8%) of cilta-cel recipients and 86% vs. 87% (3.1% vs. 1.5%) of ide-cel recipients in the older vs younger groups, respectively. ICANS rates were 21% vs. 20% for cilta-cel (p = 0.79) and 29% vs 20% for ide-cel (p = 0.07), with similar rates of grade ≥ 3 ICANS. In the cilta-cel cohort, Parkinsonian delayed neurotoxicity (DNT) occurred in 3/62 (4.8%) older patients and 6/128 (4.7%) younger patients. Similarly, other non-Parkinsonian DNT rates were similar across age groups, with 6.4% vs 5.5% in older vs younger cilta-cel cohort and 0% vs 1% in the older vs younger ide-cel cohort. Rates of IEC-HS, and infections were comparable across the cohorts. There was no difference in hospital length of stay and ICU admission rate between products within either age cohort. The overall non-relapse mortality (NRM) was 6.7% for patients ≥ 75 years and 6.2% in patients < 75 years. For cilta-cel, NRM in older vs younger cohort was 9.4% vs 4.7% (p= 0.96) and for ide-cel it was 5.4% vs 6.9%, respectively (p= 0.65). Conclusion: Appropriately selected older adults (≥75 years) receiving CAR-T therapy for RRMM can derive a similar efficacy benefit with CAR-T as a propensity-matched younger cohort, without any increased signal of toxicity including CRS, ICANS or delayed NT. NRM was numerically greater, but not statistically significant, in older adults receiving cilta-cel. Median PFS with cilta-cel and ide-cel in older adults were 28.7 months and 16.4 months with median OS not reached and 40 months, respectively. Older adults, ≥75 years old, should not be excluded from CAR-T therapy solely due to advanced age. Overall, cilta-cel was not associated with worsened toxicities in older adults and may offer better PFS.

Abstract Introduction: Teclistamab is the first FDA approved BCMA-directed bispecific antibody for the treatment of relapsed and refractory multiple myeloma (RRMM). With BCMA-targeting CAR-T therapies, cytokine release syndrome (CRS) is a risk factor for cardiotoxicity. Teclistamab was associated with fatal cardiovascular adverse events (CVAEs) in a recent US pharmacovigilance database analysis, but this analysis was limited by reporting bias. Therefore, the aim of our study is to conduct a multicenter study to define the real-world incidence of CVAEs in RRMM patients treated with teclistamab. Method We performed a retrospective multi-center cohort study of patients receiving teclistamab at 5 medical centers. Baseline oncologic and cardiovascular characteristics (including vital sign and echocardiographic data) were collected. Baseline cardiovascular disease (CVD) was defined as presence of coronary artery disease, congestive heart failure, severe or symptomatic valvular heart disease, or stroke at baseline. CVAE was collected and categorized based on CTCAE v5.0 by each institution. Major adverse cardiovascular event (MACE) was a composite outcome with any of the following: congestive heart failure, asymptomatic cardiomyopathy (interval LVEF drop >10% to resultant LVEF less than 50%), coronary artery disease requiring intervention, stroke or cardiovascular death. Arrhythmia was a composite outcome with any of the following: atrial tachyarrhythmia, ventricular tachyarrhythmia or bradyarrhythmia. Median follow-up was calculated through reverse Kaplan-Meier method. Multivariable Cox regression analysis was used to define the relation between MACE and survival. Cause of death was categorized as myeloma-related death or non-myeloma-related deaths (i.e. CRS, infection or cardiovascular death). Cause-specific Cox regression was performed to define relationship between MACE and cause of death. Results In a cohort of 219 patients treated with teclistamab with median follow-up of 20.1 months, 7.3% (N=16) developed MACE, 7.3% (N=16) developed arrhythmia and 12.8% (N=28) developing any MACE or arrhythmia. MACE occurred at a median of 4.5 days (IQR 2.25-15.75 days) after teclistamab step-up. The incidence of MACE was 16.4% in patients with baseline CVD versus 2.7% in those without baseline CVD (p<0.001). Patients who developed MACE had inferior ECOG performance status (PS) (PS >=2: 62.5% vs. 27.7%; p=0.008). Additionally, baseline hemoglobin level (9 vs 10g/dL; p=0.072) was numerically lower in MACE, compared to no MACE. There was no difference in age, sex, bone marrow (BM) plasma cell burden, ferritin, C-reactive protein or LDH levels between MACE vs. no MACE group. Patients who developed MACE had lower baseline diastolic blood pressure (67.7 vs 73.8mmHg; p=0.041) and numerically lower LVEF (51.4 vs 59.3%; p=0.059; baseline echocardiogram performed in 86% of all cohort). Patients who developed MACE had similar incidences of CRS (Grade >=2: 25.0 vs 16.7%; p=0.620) and immune effector cell-associated neurotoxicity (ICANS) grade 2 or higher (12.5 vs 7.5%; p=0.812). In multivariable Cox regression analysis, MACE was independently associated with inferior overall survival (HR 2.72; 95% CI 1.41-5.25; p=0.003), after adjusting for baseline CVD, age, high BM burden, extramedullary disease, and plasma cell leukemia. In cause-specific multivariable Cox regression analysis, MACE was independently associated with non-myeloma-related death (HR: 10.77 95% CI 4.39- 26.41; p<0.001) but not with myeloma-related death (1.54; 95% CI 0.64- 3.70; p=0.336). Conclusion In conclusion, in this large, real-world multicenter study, we observed that MACE occurred in over 7% of patients following teclistamab for RRMM, typically within 2 weeks of initiation. MACE was significantly associated with increased non-myeloma-related mortality. In contrast to CAR-T therapy, CRS or ICANS were not associated with MACE, whereas majority of patients who developed MACE had ECOG PS >=2 or baseline cardiovascular disease. More studies are necessary to define mechanisms and strategies to reduce these MACE and improve survival. Patients with baseline cardiovascular disease or poor performance status may benefit from cardiovascular optimization before and during teclistamab therapy.

Abstract Introduction: Bispecific T-cell engagers (TCE) targeting BCMA (teclistamab, elranatamab) and GPRC5D (talquetamab) are important therapeutic options in relapsed/refractory MM (RRMM). However, data on the independent prognostic impact of individual cytogenetic abnormalities and functional high-risk MM on outcomes with TCEs remains limited. Methods We included RRMM patients treated with BCMA TCEs (teclistamab, elranatamab) and talquetamab across 15 centers in the US. Patients where TCEs were used only as bridging therapy to CAR-T were excluded. High-risk cytogenetic abnormalities (HRCA) included del(17p), t(4;14), t(14;16), 1q gain/amplification (1q21+), del(1p) before initiation of TCE. Functional high-risk disease (FHRMM) was defined as PFS <18 months with frontline therapy. Extramedullary disease (EMD) included visceral or soft tissue disease and excluded paraskeletal disease. Progression-free survival (PFS) was estimated from TCE initiation using the Kaplan–Meier method and compared using the log-rank test. Univariate and multivariable Cox proportional hazards models were used to identify predictors of PFS in the entire cohort and the subcohorts of BCMA TCEs and talquetamab (Talq). Results We analyzed 943 treatment initiations with TCEs in RRMM, comprising 577 BCMA-directed TCEs [teclistamab (n=436) and elranatamab (n=141)] and 366 talquetamab initiations. The median follow-up from TCE initiation was 13.4 months (95% CI: 12.5–14.2) and median age was 68 years (interquartile range 61-75 years). Two ore more HRCAs were noted in 30% of the cohort (34% in Talq vs. 28% in BCMA TCEs, p=0.04), EMD was present in 21% of patients (26% in Talq vs. 18% in BCMA TCEs, p=0.002), and 45.5% of patients had FHRMM (47% in Talq vs. 45% in BCMA TCE, p=0.54). The median prior lines of therapy was 6 (interquartile range: 5-8), with 92% being triple-class refractory (TCR); 60% received prior BCMA-directed therapy (85% in Talq vs. 45% in BCMA TCE, p<0.0001) and 45% had prior CAR-T in 45% (57% in Talq vs. 37% in BCMA TCE, p<0.001). The best overall response rate (ORR) was 67.1 % for the entire cohort (66.4% for BCMA cohort and 68.2% for Talq), with 32.5% patients achieving a ≥ complete response. The median PFS was 7.7 months (95% CI: 6.7–8.6) for the entire cohort, with a median PFS of 10.1 months (95% CI: 7.5-13.4) for teclistamab and 10.1 months (95% CI: 3.9-NR) for elranatamab. In the more heavily pretreated talq cohort, the median PFS was 6.4 months (95% CI: 5.1-7.5). In a univariate analysis (UVA), several HRCAs were associated with inferior PFS−del(17p) (HR 1.59), t(4;14) (HR 1.43), del(1p) (HR 1.54), and ≥2 HRCAs (HR 1.64), all p<0.01. Apart from HRCAs, adverse disease characteristics included FHRMM (HR 1.20) and EMD (HR 1.46); all p<0.05. Among laboratory markers, hemoglobin <9 g/dL (HR 2.10), platelet count <75 ×10⁹/L (HR 1.96), and elevated ferritin (≥600 ng/mL; HR 2.17) (all p<0.01) were prognostic for PFS. ECOG ≥2 (HR 1.62), prior BCMA-directed therapy (HR 1.56), and prior CAR-T (HR 1.44) (all p<0.001) were also associated with inferior PFS. In a multivariable analysis (MVA), prior BCMA therapy (HR 1.72, p<0.0001), ferritin >600 ng/mL (HR 1.68, p<0.0001), hemoglobin <9 g/dL (HR 1.53, p=0.001), ECOG PS ≥2 (HR 1.52, p=0.0009), del(17p) (HR 1.44, p=0.0034) and FHRMM (HR 1.26, p=0.047), were associated with inferior PFS. Within the talq cohort (n=366), EMD (HR 1.64), del(17p) (HR 1.42), del(1p) (HR 1.54), FHRMM (HR 1.34), ECOG ≥2 (HR 1.56), ferritin >600 (HR 1.88), hemoglobin <9 g/dL (HR 1.6), platelet count <75 ×10⁹/L (HR 1.36) and leukopenia <0.25 x 10⁹/L (HR 1.52) were adverse prognostic markers on UVA. A MVA confirmed the independent impact of ferritin >600 ng/mL (HR: 1.77), ECOG ≥2 (HR 1.61) and functional high-risk status (HR 1.52) on PFS, whereas del(17p) and EMD were trending toward significance. Within the BCMA TCE cohort (n=577), prior BCMA therapy (HR 1.9), ferritin >600 (HR 1.79), ECOG ≥2 (HR 1.55), Hb <9 g/dL (HR 1.54), and del(17p) (HR 1.52) were independently associated with inferior PFS on a MVA.Conclusions: In this large real-world cohort of TCE, outcomes varied by fitness, disease biology, and treatment history. The ECOG PS, elevated ferritin, functional high-risk status and del(17p) were consistently associated with inferior PFS. Prior BCMA exposure was an independent risk factor for inferior PFS in the BCMA TCE cohort, but not with talquetamab.

Abstract Despite a characteristic indolent course, a substantial subset of follicular lymphoma (FL) patients has an early relapse with a poor outcome. Thus far, efforts to identify factors that predict survival have been unsuccessful. However, we and others have demonstrated the prognostic relevance of CD4+ T cells in the tumor microenvironment (TME) of FL and developed a bio-clinical risk model (called BioFLIPI) that offers improved risk stratification (Mondello et al, BCJ 2021). However, the mechanisms defining different BioFLIPI scores remain to be fully understood. To identify the programs associated with the BioFLIPI scores, we first interrogated the RNA-seq of purified B cells from 67 newly diagnosed FL1-3A (BioFLIPI 1 n=21; BioFLIPI 2-3 n=36; BioFLIPI 4 n=10). We found 1,156 upregulated genes and downregulation of 930 genes in BioFLIPI 4 vs 1, including well-known immune molecules such as CD70, IL10RA, CD69, and CCR6 (FDR<0.05). Gene set enrichment analysis (GSEA) using the MSigDB confirmed a negative enrichment in multiple immune response and interferon gamma signatures and revealed striking positive enrichment for cell proliferation and antigen presentation pathways in BioFLIPI 4 compared to BioFLIPI 1 tumors. The same pathways were dysregulated in BioFLIPI 2-3 but a lower magnitude. To investigate the somatic mutations associated with different BioFLIPI scores, we performed WES of the same 67 FLs and further expanded this cohort for a total of 90 patients (BioFLIPI 1 n=26; BioFLIPI 2-3 n=51; BioFLIPI 4 n=13). We found enrichment for mutations in several regulators of the germinal center in BioFLIPI 4 and 2-3, such as MEF2B (p=0.029), FOXO1 (p=0.038) and IRF8 (p=0.035), suggesting the cooperation of multiple oncogenic events promoting lymphomagenesis. In contrast, BioFLIPI 1 tumors harbored a higher rate of mutations in TNFRSF14 gene, known to enhance anti-lymphoma immune response. To investigate whether BioFLIPI modulates immune signatures of the microenvironment, we performed TME deconvolution by applying CIBERSORTx to bulk RNA-seq of these 67 FLs. We found that FLs with BioFLIPI 4 and 2-3 were enriched for CD4+ Tcm exh (p=0.02), Tem exh (p=0.04), Tfhexh (p=0.07) and NK cells (p=0.01) compared to BioFLIPI 1. In line with this data, CyTOF performed on a subset of these patients (BioFLIPI 1 n=12; BioFLIPI 2-3 n=25; BioFLIPI 4 n=6) confirmed progressive increase of CD4+ Tcm exh (p=0.006), Tem exh (p=0.009) and Tfh exh (p=0.025) cells from BioFLIPI 1 to BioFLIPI 4. Single cell RNA/BCR-seq of 21 FLs (BioFLIPI 1 n=6; BioFLIPI 2-3 n=12; BioFLIPI 4 n=3) corroborated a higher abundance of Tem exh, cytotoxic (CTL) Tem exh, Tfhexh and NK cells in BioFLIPI 4 and 2-3. Conversely, CD8+ naïve T cells were prevalent in BioFLIPI 1 tumors. Differential gene expression in T cell clusters from BioFLIPI 4 vs BioFLIPI 1 FL revealed a marked upregulation of multiple immune genes involved in antigen presentation (e.g., HLA-DRB, HLA-DQA, HLA-DPA/B) and immune response (e.g., ETS1, TNFSF8, IL7R). GSEA showed a positive enrichment for antigen presentation signatures and negative enrichment for TNFα signaling and Oxphos metabolism. Similar findings were observed in BioFLIPI 2-3 FLs. Using CellChat analysis, we found a stronger interaction between malignant B cells and Tem exh and CTL Tem exh cells in BioFLIPI 4 and 2-3 vs BioFLIPI 1 tumors. This was linked to an increased strenght of MHCI-CD8 interaction and concordant decrease of MHCII-CD4. Notably, the suppressive BTLA-TNFRSF14 signaling axis was present in BioFLIPI 4 and 2-3 but not in BioFLIPI 1 FLs. This was accompanied by a decreased signaling through TNF/LTA-TNFRSF1B, CD80/CD86-CD28/CTLA4. Linking the BioFLIPI-specific immunogenicity to lymphomagenesis, we found that FL patients with BioFLIPI 4 had two-three folds higher risk of transformation to an aggressive lymphoma (12% vs 7%) or death (21% vs 3%) than those with BioFLIPI 1, suggesting that this immune dysfunction favors the expansion of a dominant tumor clone and promotes a more aggressive form of FL. Collectively, our findings demonstrate that BioFLIPI scores in FL reflect distinct patterns of tumor immunogenicity that shape the TME. Notably, high BioFLIPI scores are paradoxically associated with enhanced antigen presentation alongside a suppressed immune response. This suggests a sustained antigen-specific T cell response that may drive immune exhaustion, promote tumor progression, and ultimately lead to histologic transformation

Abstract Background: Prognostication for patients with non-transformed relapsed/refractory (R/R) follicular lymphoma (FL) is not well defined. Progression of disease within 24 months (POD24) and number of lines of prior therapy are commonly used to benchmark outcomes and for trial eligibility in this space. However, a comprehensive model for risk prediction in R/R FL is lacking. Here we utilize patients from the LEO Consortium for Real World Evidence (CReWE) and Iowa/Mayo Clinic Lymphoma SPORE MER to develop a clinical prediction model for R/R FL. Methods: Patients with grade 1-3A FL were prospectively enrolled at diagnosis in the MER and/or initiated second line or later therapy (2L+) for non-transformed FL at one of the 8 LEO Centers from a previous LEO CReWE study (Casulo et al, Lancet Haem 2022). All available lines of therapy were abstracted; lines of therapy after histologic transformation were not used in the analyses. A management plan of observation was considered as a type of therapy in the 1L setting but not in the 2L+ setting. Clinical variables and outcomes were abstracted at each line of therapy. Variables considered for modeling included demographics, clinical labs, treatment history, and pertinent clinical variables (including FLIPI and FLIPI24 components). Multiple imputation was used to address missing data in modeling; beta-2 microglobulin (B2M) was unable to be imputed due to the amount of missing data. Index therapy was defined as the date of initiation of a line of therapy (2L, 3L or 4L) for non-transformed FL. The primary endpoint for model development was the time from index therapy until the histologic transformation or lymphoma-related death (HT/LD). Cox proportional hazards models were used for model development. Modeling was first performed separately for each line of therapy and then evaluated across lines. Bootstrapping on imputed datasets was used to assess optimism in model performance. Results: N=1001 patients initiated 2L+ therapy and were utilized for modeling. Of these patients, N=654 initiated 3L and N=344 initiated 4L therapy. Median age at index therapy was (60, 61, and 62) for lines 2-4, respectively. Median follow-up by line of therapy was 8.2, 6.1, and 6,1 years and number of HT/LD events for modeling was 272, 154, and 88, respectively. Observed outcomes decreased modestly as the line therapy increased: median event-free (1.6, 1.5, and 1.2 years) and overall survival (17.6 years, 14.5 years, and 12.3 years), for lines 2-4, respectively. 5-year estimates of HT/LD by line of therapy were 21.6% (95% CI: 18.9-24.3), 23.7% (95% CI: 19.9-27.4) and 29.3% (95% CI: 23.3-34.7), respectively. A clinical prediction model was independently developed for each line of therapy; the final model for each line consisted of the same variables: increasing age, male sex, higher LDH, lower hemoglobin, higher white blood cell count, prior immunochemotherapy exposure, and shorter time since initial diagnosis. The parameter estimates for these variables were broadly similar across the different lines of therapy. The model output is an individual patient's risk of HT/LD. Patients with high-risk FLP-R, as defined using the upper quartile of FLP-R risk scores for each line, had observed 5 year HT/LD rates of 43%, 44% and 51% in lines 2-4, respectively. In contrast, patients with the lower quartile of FLP-R risk scores had observed 5 year HT/LD rates of 10%, 6% and 8% in lines 2-4, respectively. The optimism-corrected c-statistic for the FLP-R model across all lines of therapy was 0.685. This added significant information beyond FLIPI diagnosis (c=0.533) FLIPI at index line (c=0.563), the line of therapy (c=0.525), POD24 status (c=0.578), or all 4 variables combined (c=0.614). Conclusions: The FLP-R model identifies a group of patients with non-transformed FL in the R/R setting who are at very high risk of transformation and/or lymphoma-related death across lines of therapy. FLP-R features 4 of the 5 components of the 1L FLIPI24 prediction model (B2M was unavailable for modeling) with the addition of sex, treatment history and time since initial diagnosis. The number of prior therapies is not sufficient to identify high-risk populations for clinical trial enrichment in the R/R FL setting and model discrimination for FLP-R was greatly improved over FLIPI and/or POD24 across lines of therapy. A Shiny app will be provided for model implementation; external validation is planned.