Citations

Abstract Introduction: Cilta-cel is a BCMA-directed CAR T-cell therapy that has shown remarkable efficacy in patients with RRMM. As real-world (RW) experience with cilta-cel continues to expand, and with the recent FDA guidance reducing the recommended proximity to the CAR T center from four to two weeks post-infusion, there is growing interest in identifying patients at low risk for severe early complications who may be safely managed in the outpatient setting and potentially ‘discharged’ home earlier. Methods Data were collected from 769 patients with RRMM treated with cilta-cel at 15 institutions in the U.S. via the Multiple Myeloma Immunotherapy Consortium.Logistic regression was used to identify predictors of patients who could be managed in the outpatient setting (low-risk group). Based on expert consensus within the Consortium, low-risk patients were defined as: grade ≤1 CRS, no ICANS, and no IEC-HS. The remaining patients were categorized as high-risk. We evaluated baseline characteristics with missingness < 20% as predictors, including age, sex, race, and ethnicity, ECOG performance status (PS) at time of lymphodepletion (LD), extramedullary disease, bone marrow plasma cell (BMPC) percentage, high-risk cytogenetics, bridging therapy including response, penta-refractory status, number of prior lines of therapy, prior anti-BCMA therapy, baseline C-reactive protein (CRP), and baseline ferritin. The cohort was restricted to patients with complete data on all predictors (n=455) and split into a training and testing cohort (80/20 split, n=364/91). Bidirectional stepwise regression was used to build the predictive model using variables with significance of p<0.15 selected for entry. The best model was selected based on the AIC (Akaike Information Criterion) and a significance level of p<0.05. Results Among the 455 patients with complete data included in the final model, 290 (64%) were categorized as low-risk and 165 (36%) as high-risk. Compared to the low-risk group, high-risk patients were more likely to have an ECOG PS ≥2 at time of LD (20% vs 9%, p<0.001), high-risk cytogenetics (47% vs 35%, p=0.009), and penta-refractory disease status (34% vs 24%, p=0.031). High-risk patients also had a higher median BMPC percentage (15% vs 5%, p<0.001), and higher baseline pre-LD CRP and ferritin. Overall response rates were high, at 95% vs 90% (p=0.047) for the low vs high risk groups, with complete response or better achieved in 73% vs 66% of patients, respectively (p=0.14). With a median follow-up of approximately 11 months, median progression-free survival was not reached (95% CI: 27-NA) in the low-risk group and 18.2 months (95% CI: 13.1-NA) in the high-risk group. In terms of safety, non-ICANS neurotoxicity (NINT) occurred less frequently in the low-risk group (6.6% vs 13%, p=0.015). Specifically, Parkinsonism was observed in 1.7% vs 6.1% (p=0.013), and cranial nerve palsy in 4.5% vs 5.5% (p=0.7), respectively. Non-relapse mortality (NRM) was lower in the low-risk group (4.2%) compared to the high-risk group (14%; p < 0.001). The most common causes of NRM in the low- and high-risk groups were acute toxicities (0% vs 36%, including CRS, IEC-HS, and ICANS), delayed toxicities (0% vs 8%, including colitis, NINT, and Parkinsonism), infections (50% vs 48%), and other unrelated causes (50% vs 8%). The best model to predict low-risk patients that could be managed in the outpatient settingincluded BMPC percentage and ECOG PS at LD. In the training cohort, patients with a higher pre-LD BMPC percentage and an ECOG PS ³2 were less likely to be in the low-risk group(OR per 1-unit change in BMPC percentage = 0.99, 95% CI=0.98-0.99, p<0.001 and OR for ECOG PS 2-4 = 0.38, 95% CI=0.20-0.72, p=0.003). The AUC for this model was 0.663 in the training cohort and 0.659 in the testing cohort. Conclusion In this large, multi-institutional cohort of patients with RRMM treated with cilta-cel, we identified clinical factors associated with lower risk for early severe toxicities, supporting outpatient administration and the potential for earlier discharge in selected patients, particularly those who are fit and have low disease burden. Our findings provide a practical framework to guide risk stratification and outpatient CAR T management strategies, particularly in light of evolving regulatory guidance and growing RW experience with cilta-cel.

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 <100, ANC< 1, CrCl< 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 Introduction: Monoclonal gammopathy of thrombotic significance (MGTS) is a recently recognized thrombophilia where monoclonal platelet factor 4 (PF4)-specific IgG antibodies initiate a chronic prothrombotic state characterized by recurrent and potentially life-threatening thrombosis. Studies from large data sets demonstrate that patients with monoclonal gammopathy of undetermined significance (MGUS) have a heightened risk of experiencing thromboembolic events without a precise explanatory mechanism. The prevalence of MGTS in MGUS-related thrombosis is unknown; however, the recent identification of MGTS antibodies as a cause of thrombosis suggests a potentially causative mechanism. Emerging evidence indicates that detecting pathogenic MGTS antibodies presents diagnostic challenges due to the insensitivity of FDA-approved diagnostic assays adopted from HIT (HIT ELISAs) and gold-standard functional tests that use heparin-treated platelets, such as the serotonin release assay (SRA). Only PF4-enhanced functional assays, including the PF4-dependent P-selectin expression assay (PEA) and PF4-SRA, have proven sensitive for detecting MGTS antibodies. In this study, the PEA was utilized to better define the incidence of pathogenic anti-PF4 antibodies among a cohort of MGUS patients with a history of thrombosis. Methods: A search of the Mayo Clinic Dysproteinemia Bank was conducted to identify two cohorts of IgG MGUS patients, one with venous thromboembolism-associated diagnosis code(s) and the other without. A diagnosis of multiple myeloma was exclusionary. Each serum sample was assessed using the PEA. Mayo Clinic's Institutional Review Board approved the research study. Results: Among the 134 patients studied in the thrombosis cohort, 17 (13%) stimulated platelet activation in the PEA (positive cut-off ≥19%), some weakly. Of these, four patients (Patients 1-4) were confirmed to have PF4-dependent platelet-activating antibodies inhibitable with high concentrations of heparin and sensitive to blockade of the IgG receptor on platelets, FcGRIIa. The thrombotic complications experienced included recurrent deep venous thrombosis (DVT) over several years (Patient 1), a single DVT (Patient 2), a thrombotic cerebrovascular accident (CVA) (Patient 3), and a series of thrombotic events, including DVTs, left atrial thrombosis, pulmonary embolism, and acute limb ischemia (Patient 4). Notably, longitudinal samples spanning twelve years (Patient 1), six years (Patient 2), three years (Patient 3), and on a single sample date (Patient 4) were confirmed positive by PEA. The prolonged persistence of platelet-activating anti-PF4 antibodies in Patients 1-3 supported a diagnosis of MGTS in these patients. Strikingly, all four patients tested negative in two FDA-approved HIT ELISAs (Immucor PF4 IgG and Zymutest HIA IgG). SRA was negative for Patients 1 and 2, weakly positive for Patient 3 (33%), and positive for Patient 4 (72%). Of the 166 patients in the MGUS minus thrombosis cohort, one patient demonstrated a non-heparin induced HIT-like antibody that was HIT ELISA (Optical Density >1.0) and PEA-positive, and inhibitable using high concentrations of heparin and FcGRIIa blockade. No follow-up samples were available to assess antibody longevity. The patient had no history of thrombosis, and testing demonstrated that the anti-PF4 antibody was not synonymous with the MGUS antibody.Conclusions: Among a cohort of 134 MGUS patients with thrombosis, the prevalence of MGTS was found to be 2.2% (3 patients with persistent platelet-activating anti-PF4 antibodies). The identification of anti-PF4 antibodies among MGUS patients provides a mechanism contributing to the increased thrombotic risk associated with monoclonal gammopathies. Antibody negativity in HIT ELISA and variable positivity in the SRA highlight the nonclassical serology associated with anti-PF4 antibodies in MGTS and support performing PF4-enhanced functional testing. In addition, some patients appear to produce coincidental (non-monoclonal) platelet-activating anti-PF4 antibodies without evidence of thrombosis, although the longevity of such antibodies could not be examined in the one patient where it was identified. These findings highlight the need for larger, prospective MGUS studies to validate these observations, further define the interplay between monoclonal gammopathies and thrombotic risk, and to better understand the long-term outcomes of patients with MGTS.

Abstract Background Teclistamab (Tec) and Talquetamab (Tal) are the two first FDA approved bispecific antibodies (BsAb) for the treatment of patients (pts) with relapsed/refractory multiple myeloma (RRMM). Both Tec and Tal should be initiated with step-up dosing (SUD) in an inpatient (IP) setting to mitigate the risk of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), per US label. However, standard of care practice continues to evolve and more pts receive SUD as an outpatient (OP) to reduce healthcare resource utilization and improve pt convenience. While most real-world evidence has focused on clinical and safety outcomes of pts treated with Tec and Tal, pt experience associated with these novel BsAb therapies is relatively unexplored. Methods HealthTree Foundation, a multiple myeloma pt advocacy group which provides enrolled pts with information on treatments, community groups, and research participation, surveyed RRMM patients who have received Tec or Tal. Eligible pts who completed the treatment experience survey had at least 4 months of follow-up after starting BsAb. The survey was fielded from May 2024 through June 2025. Data collection followed IRB-exempt protocols with informed consent. Results A total of 32 patients (24 Tec, 8 Tal) completed the survey. The median age was 70 years, 50% were male, and 84% were white. Most pts (n=24; 75%) received SUD at their primary oncology clinic (n=19, 59% at an academic center; n=5, 16% at local community center), and 8 (25%) at an academic center which was not their primary oncology clinic. All pts who received SUD at an academic center that was not their primary oncology clinic later transitioned to their local community clinic post-SUD and reported being satisfied or very satisfied with their transition of care experience. Overall, most pts (n= 21; 66%) received their entire step-up dosing during a single hospitalization, while some (n=6; 19%) received all doses of the SUD during separate hospitalizations for each dose. About 13% (n=4) received all SUD in an OP setting, and 3% (n=1) received SUD in a hybrid setting (mix of IP and OP). Although 85% (n=27) of the pts received IP SUD, 66% (n=21) would have preferred IP SUD in one hospitalization, while the remaining 34% (n=11) would have preferred OP or hybrid SUD. Among pts who received IP SUD (n=27), almost a quarter reported a preference for either OP (n=4; 15%) or hybrid SUD (n=2; 7%) and 78% (n=21) preferred one IP hospitalization for SUD. The factors influencing their preference for the setting of SUD in this IP sub-group were feeling more secure with IP monitoring (78%), convenience (26%), less worry about staying near healthcare centers (15%), being able to stay with their local physician (11%), staying closer to home (7%), and lower costs to the pt (4%). Among pts receiving OP SUD (n=4), 75% (n=3) preferred fully OP SUD and 25% (n=1) preferred hybrid SUD because of convenience (n=2; 50%), lower cost to pt (n=1; 25%), flexible dosing schedule (n=1; 25%), and feeling of security with IP monitoring (n=1; 25%). All the pts receiving hybrid SUD (n=1) preferred fully OP SUD due to convenience. Although Tec and Tal are subcutaneous (SC) injections, when patients were asked to compare the options of BsAbs with comparable efficacy and safety profile, they favored SC injection (n= 22; 69%) over intravenous infusion (n = 3; 9%), while 22% (n=7) had no preference for mode of drug administration. The challenges that impacted pt experience with Tec or Tal were treatment side effects (Tal pts: n=6, 75%; Tec pts: n=9, 38%) and distance or travel time to the treatment facility (Tal pts: n=2, 25%; Tec pts: n=4; 17%). Other reasons included caring for others, continuing to work, cost and insurance, lack of caregiver/care partner, being away from home, unavailability of the therapy in community setting near home, and eligibility criteria. Conclusions Most pts in this study received SUD at their primary oncology clinic. While most pts received IP SUD and preferred a single planned IP visit, one third preferred OP or hybrid SUD due to convenience. As the field moves toward OP-only SUD, this study underscores the need to consider pt preferences. There is an unmet need for community clinics providing SUD options closer to pt homes.

Abstract Background: The phase II and III GRIFFIN and PERSEUS studies evaluated DVRd vs. VRd in NDMM pts that were transplant eligible (TE). These studies included consolidation (cons) and dual agent maintenance (maint) with dara and len (DR). Little is known about the efficacy of DVRd in RW practice including frequency of bor use, use of cons, use of DR maint, and subsequent treatment after progression (PD) on DVRd. We aim to evaluate the RW efficacy of NDMM pts treated with DVRd across the tri-site Mayo Clinic Comprehensive Cancer (MCCC). Methods: We retrospectively analyzed the medical records of pts treated with DVRd between June 2018 and June 2024 at the MCCC. Outcomes were estimated using the Kaplan-Meier method. Results: 464 pts were included; 278 pts were male, and the median (m) age of MM diagnosis was 64 years (yr). 114 pts had ISS III, 205 pts had R-ISS III, 266 pts had high risk (HR) FISH, 80 pts had extramedullary disease, 165 pts had ultra HR disease (dz) (as per 2025 IMS/IMWG consensus), and 47 pts had renal insufficiency (RI) with creatinine >2 mg/dL. Starting len dose was 25mg in 356 pts, 15 mg in 40 pts and ≤10mg in 65 pts. 399 pts received bor 1x per week and 63 2x per week, 91 pts received 1-2 cycles of a different regimen prior to DVRd due to hospitalization (n=23), RI (n=38), poor performance status (n=6), other (n=34). 315 (67.9%) pts underwent autologous transplant (ASCT). The m number of induction cycles was 5; 4 for pts who underwent ASCT and 6 for pts who did not. The best ORR to induction for pts who underwent ASCT was 98% with 247 (79%) achieving ≥VGPR, and 82 (26%) achieving minimal residual disease negativity (MRD-) to at least 10-5. The best ORR for pts who did not undergo ASCT was 87%. For those who underwent ASCT, (96% with melphalan 200mg/m2), the ORR at day 100 was 97% with 56% achieving MRD-. At 1-yr post ASCT, 30% (93/312) were MRD-. 42 pts (13%) received post ASCT cons with DVRd for a m of 2 cycles. 281 pts received post ASCT maint including 107 (38%) len, 53 (19%) bor-len, 91 (32%) dara-len, 14 (5%) dara, 16 (6%) other. 61(13%) pts had change in treatment, due to change to second line therapy (35; 55%), discontinuation (d/c) of len (11; 17%), d/c of dara (3; 5%), d/c of bor (15; 23%), d/c of dex (0; 0%). The m follow-up time for all pts was 26 months (mo) (17-39). The m PFS of pts who underwent ASCT was not reached (NR), and was 57 mo (52-NA) for pts who did not undergo ASCT. For pts who underwent ASCT, the PFS at 24mo for pts who did not have HR FISH was 93% (88-99%) compared to 80% (73-88%) for pts with HR FISH (p=0.12) and 77% (68-87%) for pts with ultra-HR dz (p=0.013).The PFS at 24mo of pts with RI who underwent ASCT was 81% (66-98%) compared to 86% (82-92%) for those without RI, p=0.57. The PFS at 24mo of pts with RI who did not undergo ASCT was 53% (28-100%) compared to 64% (55-75%) for those without RI, p=0.42. The ORR and MRD- rate for pts who received once-weekly bor was 94% and 24%, compared to 94% and 27% for pts who received 2x weekly bor (p=0.85, p=0.93). For pts who underwent ASCT, the PFS at 24mo for pts who received len maint was 91% vs. 83% for pts who receive dual agent maint (DR or VR) (p=0.25), although pts who got dual agent maint were more likely to have HR FISH than pts who received len maint (p<0.001). The PFS at 24mo for pts that received post-ASCT cons was 91% compared to 85% for those that did not (p=0.53); pts who got post-ASCT cons were more likely to have HR FISH (p=0.07). For pts that underwent ASCT, the 3 yr PFS rate is 85% and the 3 yrs OS rate is 96%. For pts that did not undergo ASCT the 3 yrs PFS rate is 60% and the 3 yr OS rate is 85%. 55 pts had functional HR (FHR) MM (relapse within 18 mo) and m PFS for FHR pts who underwent ASCT was 15 mo (11-NA), while m PFS was NR for pts without FHR MM (p<0.001). 79 pts relapsed after 1st line DVRd. The most common 2nd line therapies (tx) were dara-carfilzomib (K)-D, dara-pomalidomide(P)-D, KPD, and other. The m follow-up time from 2nd line tx was 10 mo, the best ORR to 2nd line tx was 76%, and the m PFS with 2nd line tx was 18 mo (7-NA). Conclusion: In this RW analysis, the efficacy and survival outcomes of NDMM pts treated with DVRd was comparable to that reported in the PERSEUS and GRIFFIN trials, although MRD- rates appear lower. DR maint and post-ASCT cons use was not common and was used more frequently in pts with HR FISH. Pts can be effectively salvaged following PD on front-line DVRd with available tx.

Abstract Introduction: Reporting patient outcomes by CAR-T treatment centers is part of the accreditation requirement under the FACT (Foundation for Accreditation of Cell Therapy) Immune Effector Cell (IEC) Program standard. Currently, this is a time-consuming and manual process, making it increasingly difficult to sustain with the growing CAR-T applications and patient volume. The objective of this study is to evaluate how a Large Language Model (LLM) can be used to automate the abstraction and summarization of medical record for CAR-T toxicities. Methods: Clinical data from patients treated with CAR-T between January 2018 and June 2025, including hematology clinical notes, lab results, flowsheets, vital signs, and medication administration record, were used as the source of patient information. The American Society of Transplant and Cell Therapy (ASTCT) CAR-T toxicity grading guideline for cytokine release syndrome (CRS) and immune effector cell associated neurologic syndrome (ICANS) were used to define these toxicities. With the large context window of the LLM (Gemini 2.5 pro), we created a prompt by embedding both the patient data and the ASTCT guidelines for CRS and ICANS, along with an outline of specific information we aimed to abstract from the data. Additionally, the LLM was instructed to provide contextual justification for the data it extracted from patient information. The LLM-generated output included event onset date, resolution date, maximum grade, date of maximum grade, and medications given for management. The CRS and ICANS outcome reports generated by the LLM were then compared to the IEC compliance program data. Any discrepancies identified were reviewed manually. Results: Among patients (pt) treated with CAR-T in the specified timeframe, 47 were selected as training cohort. This cohort included pt with toxicities events, no events, and a mix of events of varying grades. For the test cohort, 66 pts who received CAR-T from March to June 2025 were included. Demographics for the training and test cohorts are reflective of evolving clinical practice (training, test cohorts: median age 69, 65; male 55%, 74%; lymphoma/leukemia 66%, 48%; multiple myeloma 34%, 52%; CD19 CAR-T 46%, 50%). Compared to data from the IEC compliance program, the LLM-generated summaries for CRS events demonstrated an accuracy of 90%, precision 95%, sensitivity 100%, specificity 80%, F1 score 97%, and Matthew's correlation coefficient 87%. For ICANS event, the LLM achieved an accuracy of 91%, precision 92%, sensitivity 92%, specificity 90%, F1 score 92%, Matthew's correlation coefficient 83%. Maximum grade, for both CRS and ICANS, were identified with >90% accuracy. However, dates for CRS and ICANS were less accurate, with the lowest accuracy noted in identifying the event resolution date, 45% for CRS and 67% for ICANS. Medical records were reviewed for all discrepancies between the LLM and the IEC Compliance Program data. The most common discrepancy was a mismatch in event resolution date, determined to be due to differing criteria used by the compliance team and the LLM prompt. Of note, a few discrepancies were attributed to missed information by the IEC Compliance Team, which was correctly identified and categorised by the LLM. An updated LLM prompt (LLMv2) was developed and applied to the test cohort. In version 2, the prompt was revised to include clearer instructions on how to summarize CRS and ICANS events, as well as new instructions on additional data elements to be summarized. The performance of LLMv2 on this cohort for CRS event identification was 100% across all categories (accuracy, precision, sensitivity, specificity, F1 score, and Matthew's correlation coefficient). For ICANS the LLMv2 achieved accuracy of 96%, precision 69%, sensitivity 100%, specificity 93%, F1 score 82%, Matthew's correlation coefficient 80%. Accuracy in identifying event resolution date improved significantly from 64% to 99%. Conclusions: Our study demonstrates that LLMs can significantly reduce the time required to abstract and summarize CAR-T toxicities, while maintaining high accuracy. One limitation of our study is that it is based on data from a single institution. However, plans are already underway to evaluate the use of LLMs in a multi-institutional setting.

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: Patients (pts) with soft tissue plasmacytomas noncontiguous with bone (true extramedullary disease [EMD]) have poor outcomes with standard therapies shown by low overall response rates (ORRs), which are not durable. Talquetamab (Tal; anti-GPRC5D×CD3) and teclistamab (Tec; anti-BCMA×CD3) are first-in-class bispecific antibodies (BsAbs) approved as monotherapies for triple-class exposed (TCE) relapsed/refractory multiple myeloma (RRMM). Primary analysis from the RedirecTT-1 (NCT04586426) dedicated phase 2 EMD cohort (March 2025 data cut; median follow-up [mFU] 12.6 mo) showed Tal + Tec elicited an ORR of 78.9% (assessed by independent review committee) and a 12-mo progression-free survival (PFS) of 61.0%. Here, we report updated efficacy, using investigator assessment, and safety results from the phase 2 RedirecTT-1 EMD cohort with Tal + Tec. Importantly, we report EMD location and a novel analysis of tumor burden as a prognostic indicator of ORR. Methods: Pts had TCE RRMM and true EMD defined as ≥1 nonradiated soft tissue plasmacytoma noncontiguous with bone ≥2 cm in 1 dimension (with or without paramedullary plasmacytomas). Nonsecretory/oligosecretory disease was permitted. Prior CAR-T and non-BCMA/-GPRC5D BsAb therapies were permitted. Pts received Tal 0.8 mg/kg + Tec 3.0 mg/kg Q2W, preceded by step-up doses, with a permitted switch to monthly dosing at investigator's discretion after cycle 6 or after cycle 4 with confirmed ≥VGPR. Response was assessed per IMWG; EMD response was assessed by PET-CT or MRI whole-body scans. Tumor burden was assessed by total EMD tumor volume. Results: As of July 2025, 90 pts received Tal + Tec, with a median follow-up of 16.3 mo (range 0.5–23.7). Baseline characteristics were as previously reported; 39% had nonsecretory/oligosecretory disease, 20% had prior anti-BCMA CAR-T therapy, and 9% had prior BsAb therapy (all anti-FcRH5). The median number of plasmacytomas was 2 (range 1–7); 17 (18.9%), 29 (32.2%), and 74 (82.2%) pts, respectively, had ≥1 nodal, organ, or soft tissue EMD, while 11 (12.2%) also had ≥1 additional paramedullary plasmacytoma. Of 268 EMDs across all pts, 95 (35.4%) were nodal EMD, 77 (28.7%) were organ EMD (most commonly liver), and 64 (23.9%) were soft tissue EMD; 32 (11.9%) were paramedullary. Baseline EMD tumor volume was <25 cm2in 43 (47.8%) pts, 25–50 cm2 in 21 (23.3%) pts, and >50 cm2 in 26 (28.9%) pts. Per investigator assessment, ORR (95% CI) was 77.8% (67.8–85.9); 50.0% had a ≥CR. Median duration of response (DOR) was not estimable (NE; 12-mo DOR rate, 60.1%), 12-mo PFS was 55.6%, and median overall survival (OS) was NE (12-mo OS rate 73.8%). ORR was 90.7% (77.9–97.4; ≥CR 60.5%) in pts with EMD tumor volume <25 cm2, 66.7% (43.0–85.4; ≥CR 52.4%) for 25–50 cm2, and 65.4% (44.3–82.8; ≥CR 30.8%) for >50 cm2. Common adverse events (AEs) included CRS (77.8%; no grade [gr] 3/4) and neutropenia (72.2%; gr 3/4 62.2%). Taste changes (78.9%), non-rash skin AEs (68.9%), and nail AEs (55.6%) were all gr 1/2, and rash AEs (30.0%) were mostly gr 1/2. ICANS occurred in 11 (12.2%) pts (gr 3, 1.1%; gr 4, 1.1%). Infections occurred in 72 (80.0%) pts (gr 3/4 40.0%), most commonly upper respiratory tract infection (26.7%; gr 3/4 5.6%); IVIG was highly recommended to prevent and manage hypogammaglobulinemia and infection. Ten (11.1%) pts discontinued Tal + Tec due to treatment-emergent AEs (4 pts due to infections and 6 due to gr 5 AEs). Two pts discontinued Tal only due to AEs. In total, 11 (12.2%) pts had gr 5 AEs (6 due to infections), 6 of which were deemed to be drug related by investigators. Data will be updated with an additional 4 mo of follow-up for the presentation. Conclusions: With longer follow-up in pts with TCE RRMM with true EMD regardless of baseline tumor characteristics, Tal + Tec efficacy exceeded all approved therapies, including T-cell redirecting and cellular therapies, noting limitations of cross-study comparisons. Lower total EMD tumor volume was associated with a higher ORR but low pt numbers in each group and lack of statistical testing limits robust interpretation. The safety profile of Tal + Tec was generally consistent with each monotherapy; AEs were not exacerbated with the combination. These data continue to highlight the clinical benefit of the novel combination of Tal + Tec in pts with true EMD, a population with high disease burden and significant unmet need.

Abstract Introduction Understanding the tumor immune microenvironment (TIME) in multiple myeloma (MM) is critical for identifying prognostic biomarkers and therapeutic targets. We hypothesized that specific immune cell populations within the bone marrow TIME are associated with clinical outcomes and could enhance patient stratification. To this end, we conducted the largest CyTOF-based immune profiling study to date in MM, profiling >300 million bone marrow immune cells from patients enrolled in the CoMMpass study. Methods We analyzed >1,000 bone marrow samples from ~700 newly diagnosed MM patients enrolled in the MMRF CoMMpass study (NCT01454297), using a harmonized protocol and 41-antibody CyTOF panel at five academic centers. The majority were baseline samples (n=671), with additional samples spanning up to 3.5 years post-diagnosis (n>300). Each site contributed ~200 samples on average. The cohort included 40% females, with a median age of 63 years and BMI of 27.8. ISS stages were evenly distributed (I: 36%, II: 36%, III: 29%), and 84% had ECOG 0-1. Autologous stem cell transplant was performed in 58% of patients, and 22% received maintenance therapy. Results We profiled 311 million single cells across the cohort, identifying major immune compartments: Neutrophils (36.0%), CD4 T cells (19.7%), NK cells (9.9%), monocytes (7.6%), B cells (5.7%), and CD8 T cells (5.6%). Less abundant populations included dendritic cells, γδ T cells, plasmablasts, and pDCs. In our preliminary analysis with multivariate cox regression modeling, we identified clinical factors including stem cell transplant, ISS stage, and ECOG status, as independent predictors of overall survival (OS). After adjusting for age and sex, higher proportions of naïve B cells, pDCs, and γδ T cells were independently associated with improved OS, while CD4+ T cell abundance was positively associated with prolonged progression-free survival (PFS). In contrast, elevated neutrophil proportions were significantly linked to inferior OS and demonstrated a trend toward shorter PFS. Longitudinal immune profiling in more than 200 patients identified a gradual accumulation of naïve B cells and a pronounced post-treatment rise in CD45+ plasmablasts, highlighting persistent B cell activity as a candidate mechanism for sustained therapeutic efficacy. Conclusion This study presents the largest immune proteomic atlas in MM to date, linking TIME composition to clinical outcomes. A favorable immune landscape was marked by preserved humoral immunity (naïve B cells, plasmablast expansion), enrichment of pDCs and γδ T cells, and lower neutrophil abundance, collectively associated with improved survival outcomes. These findings lay the groundwork for immune-guided prognostication and highlight new opportunities for therapeutic targeting in MM. Ongoing analyses aim to further resolve baseline and longitudinal immune dynamics in relation to treatment response.

Abstract Introduction: Multiple myeloma (MM) predominantly affects older adults who vary widely in physiological status and treatment outcomes. Comprehensive Geriatric Assessment (CGA) is considered the gold standard for frailty assessment in older cancer patients (pts), but clinical useis limited. Current frailty tools for MM include only select GCA domains, rely on trial datasets, and do not incorporate pt-reported outcomes (PROs). Since their development, treatment strategies have evolved with the use of anti-CD38 MAbs and quadruplets in older pts. The impact of geriatric impairments on treatment tolerance in the era of modern therapy remains unclear and changes in geriatric domains during treatment are not well characterized. Aim: This prospective study evaluates the association between pt-reported CGA and treatment outcomes in older MM pts.Methods: We included MM pts ≥60 years initiating a new treatment at Mayo Clinic from March 2023-June 2024. Pts completed the CARG GCA (Hurria et al 2005) electronically prior to and after 4 treatment cycles. We collected data on toxicity using CTCAE and PRO-CTCAE and quality of life using the PROMIS10-GH SF.Results: Ninety pts were enrolled. Median age was 72 (range: 63-86), 42% female, and >90% non-Hispanic white. Over half (59%) were newly diagnosed with 41% and 56% receiving quadruplets and triplets, respectively. Among newly diagnosed pts, 34% had early stem cell transplant. Baseline median self- and physician- reported KPS were 80% and 90%, respectively, with high correlation (r=0.657). The median number of meds per pt was 9 (range:0-30), 39% had ≥3 comorbidities, 21% reported ≥1 fall in the past 6 months, and 40% reported ≥1 IADL limitation. On the Hospital Anxiety and Depression Scale, 3% and 7% had anxiety and depression, respectively. On the Blessed Orientation-Memory-Concentration test, 19% had mild cognitive impairment, and 1% had severe cognitive impairment. While only 19% had grade (G) ≥3 non-hematologic toxicity by CTCAE, 71% had ≥1 treatment delay, dose reduction, or discontinuation, and 39% had ≥1 ED visit or unplanned hospitalization within the first 4 cycles. This suggests physician grading of non-hem toxicities may inadequately capture toxicity burden from MM therapy. Notably, the rate of G≥3 toxicity by PRO-CTCAE was 49%, highlighting the discrepancy between physician- and pt-reported symptom burden. CGA domains significantly associated with G≥3 non-hem toxicity were: age (74 v 71.5, p=0.032), ≥3 comorbidities (65% v 33%, p=0.015), anxiety (18% v 0%, p=0.006), ≥1 IADL limitation (65% v 33%, p=0.018), physician KPS ≤80 (53% v 27%, p=0.042), limitations in vigorous activities (100% v 78%, p=0.023) and limitations in climbing several flights of stairs (88% v 56%, p<0.001). Predictors of PRO-CTCAE G≥3 toxicity were ≥1 falls (30% v 11%, p=0.030), ≥3 comorbidities (52% v 26%, p=0.011), polypharmacy (≥9 meds) (67% v 43%, p=0.023), and physician KPS ≤80 (43% v 22%, p=0.030). CGA domains associated with ≥1 treatment adjustments were polypharmacy (62% v 33%, p=0.017) and unintentional weight loss (35% v 12%, p=0.028). Polypharmacy was the only domain associated with healthcare utilization (68% v 45%, p = 0.040), which may reflect underlying multimorbidity and greater pain burden. On multivariable logistic regression, any level of limitation in climbing several flights of stairs (OR: 6.0, 95% CI 1.2-30.3; p= 0.030) and older age (OR: 1.1, 95% CI 1.0-1.1; p=0.032) were independently associated with G≥3 non-hem toxicity, reflecting impaired functional status and reduced physiologic reserve, while ≥3 comorbidities only trended toward significance (OR:1.9, 95% CI 1.1-3.9, p=0.051).Compared to baseline, there were no significant changes in CGA domains or PROMIS10 scores after 4 cycles. While there was no significant difference in the proportion of pts reporting limitations in IADLs or physical function, we observed heterogeneity among individual pts, with changes in all 3 directions (improvement, stability, and decline). Conclusions: Geriatric impairments are prevalent in older pts with MM; pt-reported impairments are significantly associated with G≥3 non-hem toxicities, need for treatment modifications, and increased healthcare utilization, even in the era of novel therapies. Physical functional trajectories during treatment are variable among individual pts, underscoring the need for personalized treatment strategies and reassessment of geriatric domains throughout treatment.