Bal, Susan

Abstract Background: BCMA- and GPRC5D-targeting immunotherapies including CART cell therapy and Bispecific antibodies are currently approved for the treatment of multiple myeloma. However, clinical outcomes after dual antigenic exposure remain undefined. Herein we report the first report of BCMA-GPRC5D dual targeted multiple myeloma (DEMM). Methods: We conducted a retrospective multi-center study of RRMM patients treated with both BCMA- and GPRC5D-targeted treatments (TT) (CAR T, bispecific antibodies, ADCs) between November 1, 2022, and July 1, 2025. Outcomes included PFS1 (post-dual exposure), and overall survival (OS). Kaplan-Meier estimates and event-free probabilities were calculated. Results: One hundred and fifty patients who underwent TCE treatments were included and 49 patients met the criteria for inclusion. Median age was 65 years, 22.4% had creatinine clearance <=30 and ECOG 2 or greater was present in 22.2%; 57% had high-risk cytogenetics (IMWG 2016), and 60.5% were penta-refractory. Patients received a median of 6 prior lines of therapy (LOT) before 1st TCE and 9 prior LOT before DEMM. 65.3% received 1 TCE, 30.6% received 2 TCE and 4.1% received 3 TCE before DEMM. Similarly, 67.3% received 1 BCMA, 24.5% received 2 BCMA TT and 4.1% received 3 BCMA TT before DEMM. Prior TT included- BCMA CART (57.1%), BCMA Bispecific (57.1%), BCMA ADC (18.4%), other TCE (10.2%). The last dual exposure was GPRC5D Bispecific in 91.8%, BCMA Bispecific in 6.1% and BCMA CART in 2%. The median followup post relapse was 3.4 months (range 0.0-16 mos). The median PFS during the last dual exposure TT was 3.98 months (95% CI: 2.96–6.70). 32.7% did not receive any subsequent LOT and died due to progressive disease. 67.3% of patients had progressive MM and received next LOT. Median PFS1 was 1.77 months (95% CI: 1.28–6.21) with 3-, 6-, and 12-month event-free probabilities of 44%%, 19% and 0% respectively. Median OS was 5.7 months (95% CI: 2.53-12.16) for DEMM from the time of refractoriness to dual antigenic targets. Conclusions: Patients dual-exposed to BCMA- and GPRC5D-directed therapies have a poor prognosis, 32.7% had not received further treatment and in those who received treatment the PFS1 was less than 2 months and an OS of 5.7 months from progression. This reflects an area of high unmet need for the patients that are dual-exposed to BCMA- and GPRC5D-directed therapies. Further data on the cohort will be updated at the meeting. Acknowledgements include, the International Myeloma Foundation, IMWG.

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.

Introduction: Talquetamab (Talq) is a GPRC5D targeting bispecific antibody recently approved for the treatment of relapsed refractory multiple myeloma (MM) based on the MonumenTAL-1 study. Real World Evidence (RWE) is needed to understand the safety and efficacy of Talq in patients treated outside of a clinical trial as they may have different outcomes and toxicities. Here we report outcomes of 118 patients treated with Talq. Methods: Patients treated with standard-of-care Talq were included. Data was collected through a retrospective chart review from 01/2023 until 7/2024 from 7 International Myeloma Foundation (IMF) associated MM academic centers. Results: 118 patients were included in the analysis. The median age was 64, 37% had HR disease, 22% had EMD at presentation. The median LOT was 6, median number of immunotherapies before TAL was 2 (range 1,4) and 71% received prior BCMA therapy. 72% were triple refractory and 44% were penta refractory. 25% (n=60) would not have been eligible for TAL clinical trial due to exclusion criteria and15% had an ECOG of 2 or greater. 18% (n=97) received TAL as an outpatient and the median number of hospital days was 9 (0,37) for inpatients. CRS during Step up Dose (SUD) 1 was present in 30% Gr 1 (57%), Gr2 (11%), Gr 3 (6%), CRS during SUD 2 was present in 31%, Gr 1 (65%), Gr 2 (11%), CRS during SUD 3 when administered was present in 14% , Gr 1 (82%), Gr 2 (6%) and with first full dose was 12% , Gr 1 (71%), unknown (29%). ICANS occurred in 6% (7/97), Gr 1 (14%), Gr 2 (29%), Gr 3 (14%) and unknown in 43% there was no evidence of HLH. Skin toxicity was present in 62% of patients (n=105/118) with 4% needing dose interruptions and presented as rash (20%), dryness (42%) and itching (20%). Nail toxicity was present in 20% (n=65/118), with 9% needing dose interruptions. Dysgeusia was present in 51% (n=97/118), with 10% needing dose interruptions. Oral toxicity manifest as stomatitis (10%), glossitis (1%), ulcerations (2%), dry mouth (27%), was present in 34% (n=61/118), with 12.5% needing dose interruptions. Infections were present in 34% (n=82/118) and CMV reactivation in 23% while only 1 patient needed treatment for CMV. The Overall Response Rate (ORR) was 64.9% with a VGPR rate or higher of 43.3% in this population. Updated efficacy data including PFS will be reported at the time of presentation Conclusions: This is the first largest RWE of the safety and efficacy of Talq in a heavily pretreated population with a high prior BCMA exposure. The ORR is consistent with a prior study by Jakubowiak et al which showed an ORR OF 65.7% after prior T cell engagers. The safety profile - CRS, ICANS, skin and oral toxicities was similar to the MonumenTAL study, CMV reactivation was higher and this may be related to treatment with prior immunotherapies and should be monitored in the future. This report shows that Talq has a similar safety and efficacy profile in the real world when sequenced after prior BCMA therapies.

Background The International Myeloma Working Group (IMWG) defines progression of disease (PD) in multiple myeloma by the increase in serum or urine paraprotein beyond a certain threshold. With more common use of serial bone marrow-based measurable residual disease (MRD) assessment, some patients will evolve with increase in MRD burden without meeting IMWG criteria for PD and no consensus exist on the best approach for this circumstance. Understanding the implication of increasing MRD burden is particularly relevant in patients with NDMM treated with quadruplet therapy (QUAD, consisting of a PI, an IMiD, an anti-CD38 mAb and dexamethasone) and autologous stem cell transplantation (ASCT), since most will reach MRD negativity. Methods We analyzed a large dataset of patients with NDMM patients treated with QUADs + ASCT +/- QUAD consolidation +/- single or dual-agent maintenance and monitored with serial MRD assessment by next-generation sequencing (clonoSEQ®) at end of induction, post ASCT, post consolidation and at least yearly thereafter. The dataset was built from clinical trial participants and from patients receiving standard care under an institutional guideline. MRD progression (MRD-P) was arbitrarily defined as quantitative increase in MRD burden by at least 1 log10 above the nadir. Treatment modification in the event of MRD-P without IMWG-defined PD was at discretion of treating physician. For patients with MRD-P without concomitant PD we describe cumulative incidence of PD after MRD-P. To contextualize the clinical implications of MRD-P, we describe survival free of failure of second line therapy (SFF2T), defined as time from progression event (MRD-P or PD not preceded by MRD-P) until occurrence of IMWG-defined PD or death on second line therapy, regardless of whether second line was initiated due to MRD-P or subsequent IMWG-defined PD. Results Among the 216 patients, 113 (52%) were clinical trial participants, median age was 61 years (IQR 56-68), 21% age 70 or older, 32% were non-White, 57% male, 38% had MM with 1 high risk chromosome abnormality [HRCA, gain/amp 1q, t(4;14), t(14:16), del(17p)], 15% had 2+HRCA. Median duration of follow up is 39.5 months, and 966 MRD datapoints were assessed. Overall, 83% of patients achieved sCR, 78% achieved MRD negativity at 10-5, 68% at the 10-6 threshold, and 56% ceased therapy after confirmed MRD negativity. Forty-nine patients had MRD-P(N=19) or PD not preceded by MRD-P (N=30). Patients with MRD-P or PD not preceded by MRD-P often had 1 or more HRCA (73.7% and 82.8%), International staging system III (36.8% and 30.0%), and high LDH at diagnosis (31.6% and 23.3%). Median time from onset of therapy to MRD-P was 24.4 mo (IQR 12.6-35.8) and to PD not preceded by MRD-P was 23.2 mo (IQR 18.4-29.4). Among the 19 patients with MRD-P, 12 (63%) were on observation at time of MRD-P, 2 were receiving single agent lenalidomide, 5 were receiving a QUAD, 17 (89%) had previously obtained MRD negativity at <10-5 including 10 (53%) who had also achieved MRD negativity at 10-6. Upon detection of MRD-P, 12 (63%) pts changed therapy, all to a monoclonal antibody-containing triplet or quadruplet regimen. Yet, median time from MRD-P to PD was 10.1 months. Patients with MRD-P had 1-year SFF2T of 55.6%, in contrast to 35.0% for patients with PD not preceded by MRD-P. OS 2-year from progression event was 78.0% for MRD-P and 53.9% for PD not preceded by MRD-P. Conclusions In the context of NDMM treated with QUAD + ASCT, MRD-P indicates imminent IMWG-defined PD, and is driven by a thriving plasma cell population unlikely to be controlled by reinstitution of anti-CD38 mAb-based combinations. Outcomes of patients with MRD-P are similar to those of patients with IMWG-defined PD. These findings challenge the paradigm of IMWG-defined PD and paraprotein measurability as minimal parameters for change in therapy and introduction of agents with new mechanisms of action.

Introduction QUADs with an anti-CD38 mAb, an IMiD, a proteasome inhibitor and dexamethasone followed by autologous stem cell transplantation (ASCT) in the treatment of newly diagnosed multiple myeloma (NDMM) led to substantial improvements in depth of response, including minimal residual disease (MRD) negativity, and progression-free survival. The therapeutic success of QUAD + ASCT has reinvigorated an interest in fixed-duration therapy, yet optimal short term efficacy endpoint for treatment cessation is unknown. We used a large dataset of patients (pts) treated with QUAD + ASCT, monitored with serial MRD assessment and managed with MRD-adapted treatment duration to determine the best short term efficacy endpoint to identify pts at low risk of treatment failure. Methods We analyzed 221 pts with NDMM treated with QUAD + ASCT and monitored with serial marrow-based MRD by next-generation sequencing. Based on trial design (N=116) and institutional practice (N=105) most pts received post ASCT QUAD consolidation followed by treatment cessation if MRD<10-5 in two consecutive datapoints. Pts were monitored with MRD post induction, ASCT and consolidation, and at least yearly thereafter. We utilized Cox regression to build parallel models of predictors of disease progression or MRD resurgence utilizing the same patient and disease features and one distinct short term efficacy endpoint per model, inputted as time-varying covariate. Efficacy endpoints tested were IMWG-defined stringent complete response (sCR), MRD<10-5 (single datapoint), MRD<10-6, sustained MRD (S-MRD, two consecutive assessments at least 1 year apart) <10-5and S-MRD<10-6. Best fitting models were determined using Akaike's information criterion (AIC, lower value indicates better fitting model), an information theory approach, and Heagerty & Zheng C index. Results Median age of the 221 pts. was 61 years (IQR 55-68), 21% age 70 or older, 37% had MM with 1 high risk chromosome abnormality [HRCA, gain/amp 1q, t(4;14), t(14:16), del(17p)], 16% had 2+HRCA, 30% were non-White and 58% male. We followed pts for a median of 40.6 mo. and performed 979 MRD assessments. One hundred and eighty-three pts (83%) achieved sCR, 170(77%) MRD<10-5, 146 (66%) MRD<10-6 , 110 (50%) S-MRD<10-5 and 90 (41%) S-MRD<10-6. Average time to achieve the endpoint was 7.8 mo for sCR, 7.1 mo. for MRD <10-5, 9.4 mo. for MRD<10-6, 19.3 mo. for S-MRD<10-5 and 20.5 mo. for S-MRD<10-6. We first tested models to predict PFS among all 221 pts. Predictive models included same covariates (ISS, high LDH and number of HRCA) other than the efficacy endpoint. The best fitting model (AIC 417.2, C-stat 0.757) was based on S-MRD<10-5 (HR=0.23, 95% C.I. 0.11-0.47) and included presence of 1 HRCA (HR=2.93, 95% C.I. 1.31-6.52), 2+ HRCA (HR=7.60, 95% C.I. 3.31-17.43), high LDH (HR=1.64, 95% C.I. 0.81-3.33), ISS2 (HR 1.31, 95% C.I. 0.62-2.77) and ISS3 (HR 1.96, 95% C.I. 0.90-4.28). The model with S-MRD<10-6 had similar, but not better performance (AIC 419.4, C-stats 0.752). We subsequently analyzed the 121 (55%) pts who reached MRD-guided treatment cessation for the best fitting model to predict progression or MRD resurgence in absence of continuous therapy. Among these pts, 117(97%) achieved sCR, all (by definition) MRD<10-5, 116 (96%) MRD<10-6 , 95 (79%) S-MRD<10-5 and 81 (67%) S-MRD<10-6. The best fitting model (AIC 197.2, C-stat 0.766) was based on S-MRD<10-5 (HR 0.01, 95% C.I. 0.002-0.05) and included presence of 1 HRCA (HR=1.41, 95% C.I. 0.49-4.07), 2+ HRCA (HR=5.43, 95% C.I. 1.75-16.84), high LDH (HR=3.19, 95% C.I. 0.98-10.40), ISS2 (HR 1.25, 95% C.I. 0.53-2.96) and ISS3 (HR 0.73, 95% C.I. 0.23-2.37). The model with S-MRD<10-6 did not perform better (AIC 232.4, C-stat 0.727). Among the 94 pts who achieved S-MRD<10-5 and were monitored off therapy, the risk of MRD resurgence or progression 2.5 years after cessation of therapy was 6.1%, 15.0% and 22.2% and risk of progression was 3.0 %, 12.0% and 11.1% for patients with 0, 1 and 2+ HRCA, respectively Conclusion In the setting of QUAD therapy + ASCT, no short term conventional or MRD-based efficacy parameter negates the cumulative impact of HRCA on prognosis. S-MRD<10-5 is the best predictor of PFS and yields the best predictive models for risk of MRD resurgence or progression in the setting of fixed duration therapy. This analysis validates S-MRD<10-5 as efficacy parameter for treatment cessation in trials exploring fixed duration therapy in NDMM.

Abstract Background: MM that is refractory to a proteasome inhibitor (PI), an immunomodulatory agent (IMiD) and an anti-CD38 monoclonal antibody (CD38MoAb) is labeled triple-class refractory (TCR) and recognized as a modern therapeutic challenge. In recent years, new agents have shown activity in this setting in single arm trials and many more are in development. The assessment of the impact of new agents in the TCR setting is impaired by limited information on the therapeutic outcomes of these patients when treated with non-investigational therapies. Methods: We utilized an independent RWD dataset of patients with MM refractory to CD38MoAb built from academic collaboration (MAMMOTH study) to identify patients with TCR MM who received subsequent therapy. Patients with MM that was CD38MoAb refractory but not TCR were followed longitudinally and only included if, after subsequent lines of therapy, MM became TCR. Patients were excluded if they had plasma cell leukemia, poor renal function (serum creatinine > 2 mg/dl) or if next therapy after TCR status included experimental agents. Refractoriness to a MM agent was defined as lack of objective response and/or progression while receiving therapy or within 60 days of last dose as per International Myeloma Working Group (IMWG) criteria. Time zero for analysis was initiation of next therapy after MM became TCR. Response to therapy and progression were adjudicated utilizing IMWG criteria. MM that was TCR but also exposed to 2 PIs, 2 IMiDs and a CD38MoAb was considered penta-exposed, and when refractory to 2 PIs, 2 IMiDs and a CD38MoAb, it was considered penta-refractory. Results: Data collection occurred between 2016 and 2018 (prior to commercial availability of selinexor, belantamab mafodotin, melflufen or ide-cel). Of 275 patients in the MAMMOTH study, 177 were included. Median age was 65 years (range 27-90), 53% were male, 76% white, 28 % had International Staging System stage 3, and 29% high risk cytogenetics [t(4;14), t(14;16) or del(17p)]. Median number of prior lines of therapy was 5 (range 3-17), median time from diagnosis to TCR was 4.8 years (range 0.9-19.4), 73% had received prior autologous hematopoietic cell transplantation, 84% were refractory to bortezomib or ixazomib, 58% were refractory to carfilzomib, 87% to lenalidomide and 74% to pomalidomide. Penta-exposed patients were 58% and penta-refractory 30%. The first regimen after MM became TCR included cytotoxic chemotherapy in 45%, CD38MoAb in 25%, SLAMF7 MoAb in 7%, carfilzomib in 24%, and pomalidomide in 34% of cases. Overall response rate (ORR) was 30% (20.9% PR, 7.3% VGPR and 1.7% CR). Median progression-free survival (PFS) was 2.8 mo. (95% C.I. 2.3-3.2) and overall survival (OS) 8.6 mo. (95% C.I. 6.8-10.3),(Figure). For Patients with MM that was penta-exposed (N=102), ORR was 30%, median PFS was 2.7 mo (95% C.I 2.1-3.2), and median OS 7.7 mo (95% C.I. 6.0-9.4). For patients with penta-refractory MM (N=53), ORR was 32%, median PFS was 2.5 mo. (95% C.I. 1.7-3.3), and median OS 6.9 mo. (95% C.I. 4.9-8.9). PFS or OS was similar among patients who were TCR but not penta-exposed, TCR plus penta-exposed but not penta- refractory or TCR plus penta-refractory (Figure). Outcomes according to next regimen after MM became TCR are outlined in the Table. In multivariable analysis, no factor was predictor of PFS while refractoriness to carfilzomib (HR 2.2, 95% C.I. 1.5-3.3), presence of high-risk chromosome abnormalities (HR 1.5, 95% C.I. 1.0-2.2) and short interval from diagnosis to TCR (HR 0.92, 95% C.I. 0.85-0.99) were predictors of shorter OS. Conclusions: Patients with TCR MM have a uniformly low chance of response to subsequent conventional therapy with short PFS and OS even when not penta-exposed or penta-refractory. This dataset provides efficacy benchmark for new therapies being developed in this setting. Figure 1 Figure 1. Disclosures Costa: BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Cornell: Abvvie: Current Employment. Chhabra: GSK: Honoraria. Liedtke: Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Alnylam: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Kansagra: GSK: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Cota Health: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Alynylam: Membership on an entity's Board of Directors or advisory committees. Giri: PackHealth: Research Funding; CareVive: Honoraria, Research Funding. Malek: Amgen: Honoraria; Janssen: Other: Advisory board ; Cumberland Inc.: Research Funding; Bluespark Inc.: Research Funding; BMS: Honoraria, Research Funding; Sanofi: Other: Advisory Board; Medpacto Inc.: Research Funding; Takeda: Honoraria. Vij: BMS: Research Funding; Takeda: Honoraria, Research Funding; Sanofi: Honoraria, Research Funding; BMS: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria; Karyopharm: Honoraria; CareDx: Honoraria; Legend: Honoraria; Biegene: Honoraria; Adaptive: Honoraria; Harpoon: Honoraria. Usmani: Celgene/BMS: Consultancy, Research Funding, Speakers Bureau; Array BioPharma: Consultancy, Research Funding; Amgen: Consultancy, Research Funding, Speakers Bureau; Abbvie: Consultancy; EdoPharma: Consultancy; GSK: Consultancy, Research Funding; Janssen: Consultancy, Research Funding, Speakers Bureau; Sanofi: Consultancy, Research Funding, Speakers Bureau; Merck: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; SkylineDX: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Takeda: Consultancy, Research Funding, Speakers Bureau; Janssen Oncology: Consultancy, Research Funding; Bristol-Myers Squibb: Research Funding. Hari: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Karyopharm: Consultancy; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau. Kumar: Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Novartis: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Antengene: Consultancy, Honoraria; Beigene: Consultancy; Oncopeptides: Consultancy; Sanofi: Research Funding.

Introduction T-cell prolymphocytic leukemia (T-PLL) is a rare and aggressive malignancy with limited treatment options, frequent relapse, and poor long-term survival. Allogeneic hematopoietic cell transplantation (allo-HCT) is reported to be effective in T-PLL yielding durable remissions and improved survival. Rates of survival and non-relapse mortality vary; data is scant and limited to small retrospective series. Whether regimen intensity - a modifiable factor- is associated with outcomes is unknown. Here, we report an analysis of patients with T-PLL undergoing allo-HCT in 87 centers using data reported to the Center for International Blood and Marrow Transplant Research (CIBMTR). Methods A retrospective multicenter study was conducted utilizing the CIBMTR dataset, which captures all consecutive patients transplanted in participating centers. The study population included patients aged 18 or older with T-PLL who underwent allo-HCT between 2008 and 2018. All donor types, graft sources, and conditioning intensities are summarized (Table 1). Cox regression analysis was used to assess overall mortality, treatment-related mortality (TRM), relapse or progression, disease-free survival (DFS) and acute and chronic graft-versus-host disease (GVHD). Due to the strong correlation between regimen intensity and patients' age, a combined variable was constructed, and in all models, interactions between age/regimen and significant covariates were examined. Results A total of 266 pts were identified and included in this analysis (Table 1). Median follow up of survivors was 49 months (range 3-117); the completeness of survival data out to four years was 95%. In univariate analysis, the 4-year overall survival (OS) rate was 30% (95% confidence interval [CI]: 23.8-36.5%). The 4-year DFS, relapse, TRM rates were 25.72% (95%CI: 20-32%), 41.9% (95%CI: 35.5-48.4%), and 32.4% (95%CI: 26.4-38.6%), respectively. Cumulative incidences of grade 2-4 acute GVHD at day +180 and chronic GVHD at 1-year were 22.5%% (95%CI: 16.8- 28.9%) and 38.3% (95%CI: 32.9-44.9%), respectively. Multivariate analyses was performed using age (Age >60 vs Age ≤60) and conditioning intensity (myeloablative [MAC] vs. reduced intensity/non-myeloablative [RIC/NMA]) as main effect (Table 2). Poor performance status was associated with inferior TRM, DFS and OS. Compared to MAC/Age ≤ 60, RIC/NMA/Age≤ 60 correlated significantly with less TRM (hazard ratio [HR] 0.28, 95% CI 0.14-0.55, p= 0.0022, superior DFS [HR 0.53, 95% CI 0.35-0.81, p= 0.0029; (Figure 3) and OS HR 0.49, 95% CI 0.32-0.75, p= 0.0009; (Figure 2). Similar trend was observed for RIC/NMA/ Age> 60 for all 3 outcomes but did not reach statistical significance. Remission status at time of allo-HCT (stable disease or progression vs. complete remission) correlated with relapse (hazard ratio [HR] of relapse=2.13, 95%CI 1.23-3.71, p=0.0072), however degree of response (partial response vs. complete remission did not significantly correlate with relapse (HR of relapse=1.41, 95%CI 0.91-2.17, p=0.1257). In vivo T cell depletion with ATG (N=47) or alemtuzumab (N=2) was associated with worse TRM [HR 1.82, 95% CI 1.08-3.08, p= 0.0255] and inferior DFS [HR of death or progression=HR 1.50, 95% CI 1.05-2.15, p= 0.0276]. The most common cause of death was disease relapse (52%) followed by infection (15%) and GVHD (13%). Conclusion This CIBMTR study, with the largest cohort of allo-HCT in T-PLL to date, demonstrates allo-HCT is effective in providing durable remissions. MAC and poor performance status were predictive of inferior TRM and OS. Disease relapse was most common cause of death, and pre-allo-HCT remission inversely correlated with relapse rate. The data suggest that reduced intensity conditioning and avoidance of post-transplant ATG/alemtuzumab may be beneficial. Novel strategies are needed both pre and post-allo-HCT to further improve outcomes. Disclosures Dholaria: J&J: Research Funding; bms: Research Funding; Takeda: Research Funding; Poseida: Research Funding; Angiocrine: Research Funding. Jagadeesh:Verastem: Membership on an entity's Board of Directors or advisory committees; Debiopharm Group: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; MEI Pharma: Research Funding; Regeneron: Research Funding. Oran:Celgene: Consultancy; ASTEX: Research Funding; Arog Pharmaceuticals: Research Funding. Nakamura:Viracor: Consultancy; Celgene: Other: Support on seminar; Magenta Therapeutics: Other: Advisory board meeting; NapaJen Pharma: Consultancy; Alexion: Other: Support on a meeting presentation; Merck: Other: advisory board meeting; Kadmon Corporation: Other: Advisory board meeting; Kyowa-Kirin: Other: Support on a meeting presentation. Sauter:Spectrum Pharamaceuticals: Consultancy; Sanofi-Genzyme: Consultancy, Research Funding; Gamida Cell: Consultancy; Novartis: Consultancy; Genmab: Consultancy; Precision Biosciences: Consultancy, Research Funding; Kite - a Gilead Company: Consultancy; Celgene: Consultancy, Research Funding; GSK: Consultancy; Bristol-Myers Squibb: Research Funding; Juno Therapeutics: Consultancy, Research Funding. kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy.