Baz, Rachid

The treatment landscape for multiple myeloma (MM) is evolving rapidly and includes several new options. The management must be tailored to the individual. The NCCN Guidelines for MM provide a framework to base decisions regarding diagnosis, workup, treatment, and follow-up of both newly diagnosed and previously treated relapsed/refractory MM. This manuscript outlines the recommendations from NCCN Guidelines for MM specific to newly diagnosed MM (NDMM).

ABSTRACT Chimeric antigen receptor T-cell (CART) and T-cell engager (TCE) therapies targeting B-cell maturation antigen (BCMA) are transforming the treatment landscape for relapsed multiple myeloma (MM). However, despite impressive initial response rates, most patients eventually relapse. To investigate this unmet medical need, we applied whole-genome sequencing (WGS) to MM cells from cohorts of 102 relapsed patients treated with anti-BCMA CART and TCE therapies. Several genomic alterations were associated with clinical outcomes, particularly primary refractoriness, including high genomic complexity and mutations in genes regulating plasma cell identity, which predicted resistance to therapy. Single-cell RNA sequencing further revealed that MM cells from refractory patients exhibited high proliferation signatures and reduced expression of TNFRSF17 (encoding BCMA), while were less enriched for plasma cell–associated transcriptional programs, a phenomenon we term “plasma cell identity escape.” This profile was strongly associated with immune dysregulation of CD8 T cells including increased activation and exhaustion. This evolution of MM toward a more proliferative and lineage-divergent state, refractory to the anti-BCMA T-cell redirecting therapies, was functionally validated in preclinical MM mouse models. Collectively, our results comprehensively define the cellular and molecular mechanisms underlying primary resistance to anti-BCMA therapies.

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: 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: The GPRC5D-directed bispecific antibody (BsAb) Talquetamab (Talq) has shown promising results for patients (pts) with relapsed/refractory multiple myeloma (RRMM) in the MonumenTAL-1 clinical trial (Chari et al. NEJM 2022). However, there are limited data on the use of Talq in the real-world setting. Methods: All pts with RRMM who started Talq between 8/2023-3/2025 across 15 US academic centers were included. High-risk cytogenetic abnormalities (HRCA) were defined as del(17p), t(4;14), t(14;16) and/or gain/amplification 1q21. Time-to-event analyses were estimated using the Kaplan-Meier method. Toxicities including CRS and ICANS were graded using CTCAE v5.0 or ASTCT criteria. Results: A total of 484 pts were included, with a median age of 65 years (range 35-89), and 83 pts (17%) were aged ≥75 years. 20% of pts were black. 21% had baseline CrCl<40, 65% had HRCA and 29% had >1 HRCA (i.e Ultra high-risk MM). The median number of prior lines of therapy was 6 (IQR 4, 8). 50% were penta-refractory, 69% received at least one prior BCMA-directed therapy (46% CART; 32% BsAb). Prior to initiation of Talq, 11 pts (2%) had CNS MM, 29 (6%) had PCL and 126 (26%) had true extramedullary disease (EMD). 70% would have been ineligible for the MonumenTAL-1 trial. For most pts (n=405; 84%) the dosing strategy from Cycle 2 was 0.8 mg/kg every 2 weeks. and the 0.4 mg/Kg weekly dosing was used in 28 patients (6%). In 6% of pts, an additional drug was added to Talq, mostly pomalidomide (n=20) or daratumumab (n=10). 101 pts (21%) received Talq as bridging for CART. Median duration of Talq treatment was 102 days. 62% developed CRS (Grade ≥3, 2%; including one Grade 5 event). 15% developed ICANS (Grades 3-4, 4%). Steroids were used in 213 patients (44%), tocilizumab in 145 (30%) and anakinra in 9 (2%). 22 patients (5%) required ICU stay during the first cycle, for a median of 6 days (range 1-31). A total of 200 pts (41%) had infections (median 1 infection each, range 1-6), including 99 (20%) with bacterial infections, 113 (23%) viral infections and 21 (4%) fungal infections. IVIG was used in 261 pts (54%). 79% of patients (n=384) developed Talq-related oral toxicity, 55% (n=269) skin toxicity and 199 (41%) nail toxicity. 157 patients died after a median follow up of 11.5 months (mos), and the leading causes of death were MM progression (n=120) and infection (n=10). 8 pts (1.7%) developed invasive second primary malignancies. The ORR was 73%, including 46% ≥VGPR. The median PFS (mPFS) for the entire cohort was 7.8 mos (95% CI 6.9-9.4) and the 12 months PFS rate was 39%. The median OS had not been reached and the 12 months OS rate was 63%. For pts who would have been eligible for MonumenTAL-1, the mPFS was 12.2 mos (95% CI 9.7 – not reached (NR); for trial-ineligible pts, the mPFS was 6.9 mos (5.8 – 8.0; p=0.003). For BCMA-naive pts, the mPFS was 15.7 mos (11.8-NR); for BCMA-exposed pts, the mPFS was 6.8 mos (6.0-7.8; p=0.0002). For patients who received Talq as bridging prior to CART, the median PFS was NR (14.1 – NR); for those who did not receive Talq as bridging the mPFS was 6.5 mos (5.3-7.6; p<0.0001). In multivariable analyses, worse OS and PFS were associated with trial ineligibility [(HR 1.38, 95% CI 1.03-1.86; p=0.03) and (2.33, 1.31-4.14; p=0.004)], BMI<30 [(1.42,1.06-1.89; p=0.02) and (1.50, 1.01-2.22; p=0.045)] and true EMD at baseline [(1.95, 1.49-2.56; p<0.001) and (1.65, 1.16-2.36; p=0.005). On the other hand, use of Talq as bridging to CART was associated with better PFS (0.27, 0.17-0.43; p<0.001) and OS (0.13, 0.05-2.56; p<0.001). Ultra high-risk MM (1.40, 1.06-1.84; p=0.02) and baseline albumin <3 (1.68, 1.18-2.37; p=0.004) were associated with worse PFS; ECOG ≥2 (1.68, 1.18-2.40; p=0.004), and baseline Plt<50K (2.14, 1.48-3.10; p<0.0001) was associated with worse OS. Conclusions: In this large real-world analysis of 484 Talq recipients, the ORR was comparable to MonumenTAL-1 but the median PFS was shorter. This likely reflects differences in patient selection, with 70% of patients in our cohort being trial-ineligible. Patients who received Talq as pre-CAR-T bridging had superior survival outcomes. Rates of toxicities were similar to MonumenTAL-1, including >70% of patients developing dysgeusia.

Abstract Background: Multiple myeloma (MM) is always preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage or high tumor cell burden (i.e. SLiM criteria, SV Rajkumar Lancet Onc 2014), as morphology and cytogenetics cannot reliably distinguish them. Methods: To identify genomic features underlying clinical behavior in MGUS and SMM, a total of 374 patients with SMM (n= 290) or MGUS (n=84) with available whole exome (whole exome sequencing, WES, n=190) or whole genome sequencing (whole genome sequencing WGS, n=184) were included in the study. Overall, none of the patients had evidence of SLiM or CRAB criteria at the time of the biopsy. Based on the center of origin and availability of WES and WGS, 227 and 97 patients were used to form our study training and validation set. The study was designed in two parts: 1) defining a new classification for MM precursor conditions; 2) integrating genomics to existing prognostic score to improve accuracy in identifying patients at imminent risk of progression. Overall, 68 patients in the training set were either lost to follow-up or enrolled in a clinical trial and they were only included in the classification part of the study. Results: By leveraging the distribution of established MM-defining genomic events (Maura et al. JCO 2024) in the training set, we developed a workflow that differentiates MGUS and SMM into two genomically distinct entities: one with evidence of neoplastic transformation (i.e., genomic MM) and one without (i.e., genomic MGUS). Overall, 39% of MGUS and 91% of SMM cases had genomic evidence of neoplastic transformation in the training set (i.e., genomic MM). When we applied the same workflow and classification to the validation set, 46% and 83% of MGUS and SMM had evidence of neoplastic transformation, respectively. Importantly, none of the patients classified as genomic-MGUS progressed to MM in either the training or validation cohorts, with a median follow-up of 40 and 61 months, respectively. Moreover, all patients with IMWG 2/20/20 high risk SMM were classified as genomic MM in both the training and validation set. Interestingly, 5 out of 62 (8%) patients enrolled in early intervention trials for high risk SMM were genomically classified as genomic-MGUS. Overall, these data demonstrated that the MM genomic background and neoplastic transformation can be acquired very early in time, even before the SMM phase, in line with what observed in solid tumors. To avoid overestimating the prognostic impact of myeloma-defining genomic events—which are, by definition, enriched in the genomic-MM group compared to genomic-MGUS—we restricted our prognostic analysis to patients in whom transformation has already occurred (genomic-MM). In fact, distinct genomic drivers may predict malignant transformation but not necessarily the risk of imminent progression to MM once transformation has occurred. After running 5-fold cross validations corrected for IMWG 2/20/20, only presence of RAS mutations, genomic events involving MYC, presence of neoplastic copy number variant (CNV) signatures and APOBEC mutagenesis were predictive of early progression in the training set. Adding the presence of high-risk myeloma-defining genomic events to the IMWG 2/20/20 model (i.e., genomic-IMWG) significantly improves the accuracy of predicting MM progression in both the training (c-index 0.69 vs. 0.74) and validation sets (c-index 0.74 vs. 0.79), compared to the IMWG 2/20/20 alone. Conclusion: By leveraging comprehensive genomic profiling integrated with the clinical IMWG 2/20/20 risk score, we propose a novel classification and prognostication system for MM precursor conditions, which will better define patients who may benefit from early therapeutic intervention versus watch-and-wait monitoring.

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 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 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.