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Abstract Background: Although progression-free survival (PFS) in early-stage (ES) classic Hodgkin Lymphoma (cHL) is high, there remains a subset of patients (pts) at higher risk of worse outcomes, particularly in those with unfavorable risk disease. Leveraging pt-level data from within the HoLISTIC (Hodgkin Lymphoma International STudy for Individual Care) Consortium, the E-HIPI was developed in clinical trial pts and validated in real-world registry pts to predict 2-year (y) PFS (Rodday. NEJM Evidence 2025). Continuous, objective, and readily measurable pre-treatment variables were considered, with sex, maximum tumor diameter, albumin, and hemoglobin included as significant predictors. Using the E-HIPI, interactive calculators for pt risk, comparison, and stratification were created (https://rtools.mayo.edu/holistic_ehipi/). Although the E-HIPI was developed and validated in both unfavorable and favorable ES cHL pts, the clinical predictors are primarily markers of unfavorable disease. In the development and initial validation cohorts, 2y PFS was 93.7% and 90.3%, respectively, the C-statistic was 0.63 in both cohorts, calibration was strong with slight underprediction of events in the validation cohort, and the E-HIPI outperformed the historic binary classification of patients as favorable or unfavorable using EORTC criteria. However, since pts in the original E-HIPI development and validation were primarily treated with ABVD chemotherapy protocols, additional validation is needed, particularly among pts with unfavorable ES cHL who were treated initially with more intensive chemotherapeutic platforms (e.g., BEACOPP-based). Thus, we conducted an external validation of the E-HIPI in pts treated on recent unfavorable ES cHL GHSG trials. Methods: The validation cohort included 2367 adults (ages 18 to 60y) with newly-diagnosed unfavorable cHL from randomized phase 3 trials conducted by the GHSG (HD14 von Tresckow. JCO 2012; and HD17 Borchmann. Lancet 2021). We calculated the predicted probability of 2y PFS events based on the E-HIPI model equation (scale 1-100%). Model performance was assessed using discrimination and calibration. Discrimination, which is the model's ability to separate high and low risk pts, was assessed using Harrell's C-statistic. Calibration, which is the model's ability to accurately predict absolute risk, was assessed by comparing observed and predicted probabilities of 2y PFS events within quintiles of predicted probabilities and estimating calibration-in-the-large (predicted minus observed event rate) and the calibration slope. Results: For pts treated on unfavorable GHSG trials, mean age was 33y, 95% had stage II disease, mean baseline E-HIPI score (i.e., predicted 2y PFS event rate) was 6.0% (SD=2.3%), and the observed 2y PFS rate was 96.2% (95%CI: 95.4-97.0%). The C-statistic was 0.65 (95% CI: 0.59-0.70), calibration-in-the-large was 0.02, and the calibration slope was 1.08 (95% CI: 0.52, 1.64). Within the lowest risk E-HIPI quintile, the observed 2y PFS event rate was 1.6%, compared with 6.1% in the highest risk quintile. Conclusions: In external validation of the recently published E-HIPI in pts with cHL treated on unfavorable GHSG trials using more intensive BEACOPP-based protocols, discrimination was similar to the original development and validation cohorts. Collectively, the E-HIPI is a treatment-agnostic prediction tool across varied treatment regimens for unfavorable ES cHL pts. Better 2y PFS in the GHSG trials than in the E-HIPI development and initial validation cohorts may have contributed to mild misclassification, likely reflecting differences in treatment regimens. This may be resolved with recalibration or incorporating granular treatment variables into future models. Additional research is needed to understand E-HIPI performance in pts with favorable disease who have even lower event rates as well as to more fully predict individualized pt outcomes across varied chemotherapy platforms and radiation received for all ES cHL pts.

Abstract Introduction The LEO Comorbidity Index (LCI), comprising ten equally weighted comorbidity categories (respiratory, cardiovascular, digestive, hepatic, renal, autoimmune, diabetes, cancer history, HIV, and stroke), has demonstrated prognostic utility in patients with non-Hodgkin lymphomas. However, its predictive accuracy may vary with increasing age, due to age-related rises in comorbidity burden and physiological vulnerability. To investigate these dynamics, we evaluated the age-stratified predictive performance of LCI in patients with large B-cell lymphoma (LBCL), with a focused analysis on individuals aged 80+ years. We also examined which specific comorbidities most strongly influenced overall survival (OS) and developed a simplified, clinically applicable index tailored to this population. Methods We first included adults ≥40 years with newly diagnosed LBCL and recorded comorbidities from the LEO registry (USA, 2015–2020; n=1,652) to assess age-stratified predictive performance of LCI using the C-index. Next, we focused on patients 80+ years (n=263), pooled from the LEO cohort (n=147) and NiHiL registry (restricted to General Hospital, Prague, Czech Republic, 2010–2023; n=116). Comorbidities were collected from patient self-reports (LEO) and/or medical records (LEO/NiHiL). Univariate and multivariate Cox models were used. The primary endpoint was OS. Results Among the total LBCL population (n=1,652), LCI predictive performance improved by age category with C-index for patients <65 of 0.584, 65–79 years 0.579, and ≥80 years 0.647, indicating stronger discrimination in the 80+ group. Subsequent analysis focused on patients aged 80+ years (n=263; median age 83). Within this cohort, 34% had ECOG performance status (PS) 2–4, 66% stage III–IV disease, 59% elevated lactate dehydrogenase, 35% >1 extranodal site involved, and 58% International Prognostic Index (IPI) score of 3–5. A total of 377 comorbidities were reported, averaging 1.43 per patient (1.22 in LEO; 1.61 in NiHiL). LCI distribution was: 0 points in 24% (n=62), 1 point in 33% (n=88), and 2–5 points in 43% (n=113). Higher LCI scores had worse ECOG PS 2–4: 19% (LCI=0), 33% (LCI=1), and 43% (LCI ≥2; P=0.01), and inferior OS (median 6.9 years LCI=0, 3.0 years LCI=1, and 2.8 years LCI≥2, resp.; P=0.02). Presence of ≥1 comorbidity was associated with shorter OS compared to no comorbidities (HR=1.67, P=0.01). The LCI was an independent predictor of OS after adjusting for age (HR=1.18, P=0.01, C-index 0.623), IPI (HR=1.16, P=0.03, C-index 0.628) as well as for recently proposed SENIOR-IPI (HR=1.14, P=0.049, C-index 0.665). When evaluating individual comorbidities, heart disease (HR=1.54, P=0.01), stroke (HR=1.89, P=0.03), and recent malignancy (HR=1.99, P=0.02) were independent predictors of OS. Based on these findings, we developed a simplified LCI (sLCI) for use in 80+ patients incorporating only the three comorbidities (1 point each). Patients were categorized as sLCI: 0 (49%, n=129), 1 (44%, n=115), and 2–3 points (7%, n=19). sLCI scores 0, 1, 2–3 were associated with ECOG PS 2–4 27%, 37%, and 63%, respectively (P=0.01) and inferior OS: median 5.3 years (0), 2.5 years (1), and 1.4 years (2–3; P<0.01). sLCI remained an independent and strong predictor of OS after adjusting for age (HR=1.71, P<0.01, C-index 0.636), IPI (HR=1.66, P<0.01, C-index 0.635), and SENIOR-IPI (HR=1.60, P<0.04, C-index 0.659). The results were consistent in both NiHiL and LEO cohorts and remained significant among patients treated with anthracyclines (sLCI adjusted for age: HR=1.58, P<0.01, C-index 0.607; for IPI: HR=1.53, P=0.01, C-index 0.623; for SENIOR-IPI: HR=1.51, P=0.01, C-index 0.633). Conclusion Comorbidity burden becomes increasingly prognostic with higher age in LBCL patients. In the 80+ individuals, comorbidities – particularly heart disease, recent cancer, and stroke – have an independent impact on OS. While the original LCI captures the impact of broadly defined comorbidities, its prognostic utility attenuates in the 80+ patients, likely reflecting limited relevance of indolent chronic conditions in this population's constrained survival horizon. The sLCI, focused on the most prognostically relevant comorbidities, offers practical risk stratification. Incorporation of sLCI into clinical decision-making – alongside other prognostic indices – could better identify high-risk individuals and guide treatment strategies. Funding: NU21-03-00411, U01 CA195568.

Abstract Background Accurate reconstruction of electronic health record (EHR) treatment sequences is essential for leveraging real-world data (RWD) in clinical research and trial-eligibility platforms in multiple myeloma (MM). However, inconsistencies in RWD treatment documentation and the complexity of line-of-treatment (LOT) assignments in MM hinder reproducibility and limit comparisons against published trials. To address these limitations, we developed HEAL-MM, an automated rule-based algorithm that systematically parses structured medication data to calculate LOTs and segment treatment into standardized, clinically meaningful phases. The algorithm is designed to be interpretable, adaptable to evolving therapeutic frameworks, and compatible with widely adopted EHR data standards. Here, we report its real-world validation against expert-adjudicated treatment sequences to assess concordance, identify edge-case failure points, and support RWD integration. Methods A stratified cohort of 100 MM patients (9,136 structured treatment events) was curated from 114 unique healthcare systems compiled from the multi-institutional HealthTree Foundation harmonized registry. Cohort selection was randomized to ensure coverage across diagnostic eras (pre-2010, 2015–2020, 2022–2025) and treatment exposures, including CAR T-cell therapies, bispecific antibodies, and anti-CD38-based regimens. HEAL-MM sequenced MM regimens chronologically and applied predefined logic rules to identify LOT transitions, the initiation of a new therapeutic course based on drug changes, treatment gaps, and procedural anchors such as stem cell transplant or CAR T. Within each LOT, the algorithm segments and labels therapy into phases, clinically distinct intervals (e.g., induction and maintenance) using rule-based clinical logic. Outputs were benchmarked against expert-labeled adjudications. Concordance was evaluated using concordance index (C-index), stratified by patient, LOT depth and diagnostic era. Results: HEAL-MM demonstrated high concordance with expert-labeled treatment sequences: 0.94 for LOT identification, 0.98 for treatment phase segmentation, and 0.96 for phase label assignment. Achieving complete agreement with all expert annotations in 90% of patients for LOT assignment, 94% for the number of treatment phases identified, 77% for the specific labels applied to each phase, and 75% across all three dimensions simultaneously. Among discordant patients, the absolute difference in final LOT count was 0.5 ± 0.9. Performance was highest in early lines (LOTs 1–3; C-index: 0.97), with seven patients showing discrepancies at this stage. Concordance declined in later lines (LOT ≥4; C-index: 0.87), where 50% of the discordant cases (n=4) were attributable to misclassifications in earlier LOTs, such as medication restarts following >3-month gaps, demonstrating the compounding effect of early errors on longitudinal accuracy. Temporal stratification revealed improved accuracy in post-2020 cases (C-index: 0.94) compared to 2015–2020 cohorts (0.91), reflecting the increasing adoption of structured treatment standards and EHR data quality improvements. To assess HEAL-MM performance at clinically significant junctures, we analyzed treatment transitions that initiated a new LOT or marked a change in phase, achieving C-indices of 0.97 for LOT transitions, 0.97 for treatment phase shifts, and 0.94 for phase label assignment. Conclusions: HEAL-MM provides a validated, scalable solution for standardizing MM treatment structures in RWD environments, as it accurately detects the exact treatment entry of a new LOT 97% of the time. This rule-based framework enables reproducible LOT and phase assignment across heterogeneous EHR systems, supporting real-time cohort identification across institutions and EHR platforms. The algorithm's modular design allows for continuous integration of novel therapeutic categories and evolving treatment logic. While the algorithm maintained high fidelity overall, early-stage misclassifications consistent with increased heterogeneity and documentation ambiguity occasionally propagated downstream, underscoring the compounding effect of upstream errors in longitudinal reconstruction. With its generalizable structure and compatibility with industry-standard data models, HEAL-MM lays the foundation for structured treatment reconstruction in MM across RWD infrastructure and serves as a transferable blueprint for other hematologic malignancies.

Abstract Background Patients (pts) with plasma cell leukemia (PCL) were excluded from key trials, so we assessed their outcomes with standard of care bispecific antibodies (BsAbs). Methods Our multicenter retrospective US Myeloma consortium study included PCL pts treated with BsAbs. PCL was defined as ≥5% circulating plasma cells, including primary PCL, secondary PCL, historical PCL, and active PCL within 30 days of BsAb initiation. Endpoints were toxicity rates, overall response (ORR), progression-free survival (PFS), and overall survival (OS). Results Our study involved 122 PCL pts from 15 US centers with: 27% primary PCL, 65% secondary PCL, 51% active PCL, 53% women, median age of 65 years (range 31-83), 77% white, 15% black, 60% high-risk cytogenetics, 45% high bone marrow burden (≥50% plasma cells), 5% CNS myelomatosis, and 20% EMD. Median prior lines of therapy (tx) were 6 (IQR 5-9), 94% triple-refractory, 57% penta-refractory, 73% prior transplant, and 57% prior BCMA tx (70% in talquetamab group, 41% in BCMA BsAb group). Treatments included 4 cohorts: 37% teclistamab, 11% elranatamab, 42% talquetamab definitive tx, and 11% talquetamab bridge to CAR-T. BsAb was used either as monotherapy (94%) or in combination (6%) with other agents. CRS grade (G) 1 was 41%, G2 14.8%, G3 2.5%, and G4 1.6%, while ICANS G1 was 8.2%, G2 7.4%, G3 3.3%, and G4 1.6%. Infections occurred in 34% and median hospitalization was 10 days (IQR 8-15). Of 110 evaluable pts, ORR was 54.5%, with 24.5% CR, 13.6% VGPR, and 16.4% PR. The ORR was 60.8% for talquetamab definitive tx (21.6% CR, 23.5% VGPR, 15.7% PR), 46.2% for elranatamab (38.5% CR, 7.7% PR), and 33.3% for teclistamab (20% CR, 4.4% VGPR, 8.9% PR). Talquetamab bridge to CAR-T in 12 evaluable pts had a pre-CAR-T day 30 ORR of 58.3% (16.7% CR, 8.3% VGPR, 33.3% PR). With a median follow-up of 8.3 months (mo), the median (m) PFS was 3.2 mo, and mOS was 9.2 mo, with similar outcomes between primary vs. secondary PCL (p=0.37 for PFS, p=0.18 for OS). Talquetamab definitive tx had better outcomes with a mPFS of 5.5 mo, mOS of 11.5 mo, 10-mo PFS of 31.2%, and 10-mo OS of 55.7%, and further improved when used as a bridge to CAR-T, with unreached mPFS, unreached mOS, 10-mo PFS of 53.8%, and 10-mo OS of 62.7%. BCMA BsAbs had inferior outcomes, with teclistamab yielding a mPFS of 1.2 mo, mOS of 8.1 mo, 10-mo PFS of 15.3%, and 10-mo OS of 44.3%, while elranatamab showed a mPFS of 1.6 mo and mOS of 3.6 mo (p=0.007 for PFS, p=0.023 for OS). In BCMA naive pts, BCMA BsAbs' outcomes remained inferior to talquetamab with a mPFS of 1.2 mo and mOS of 3.4 mo (p=0.003, 0.001). Sixty pts with active PCL had a poor mPFS (1.6 vs. 4.4 mo, p=0.036) and mOS (5.3 vs. 10.7 mo, p=0.004) compared to pts with only historical PCL. However, in active PCL, talquetamab definitive tx (n=29) showed superior outcomes with a mPFS of 6.9 mo and mOS of 12.2 mo (p=0.003, 0.012). Talquetamab bridge to CAR-T (n=3) showed a mPFS of 3.2 mo and mOS of 5.2 mo. BCMA BsAbs had inferior outcomes: teclistamab with a mPFS of 0.7 mo and mOS of 1.4 mo, while elranatamab showed a mPFS of 1.0 mo and mOS of 3.1 mo (p=0.003, 0.012). In BCMA naive pts, BCMA BsAbs' efficacy remained poor with a mPFS of 0.7 mo and mOS of 1.4 mo (p=0.006, 0.002). While in pts with only historical PCL (without active PCL), BCMA BsAbs in BCMA naive pts led to similar outcomes with a mPFS of 5.2 mo and mOS of 8.5 mo, compared to a mPFS of 3.7 mo and mOS of 10.4 mo with talquetamab (p=0.90, 0.86). Multivariable analysis (MVA) associated active PCL with worse PFS (p=0.035, HR=1.93, CI 1.05-3.55) and OS (p=0.017, HR=2.3, CI 1.16-4.60), talquetamab with improved PFS (p=0.009, HR=0.41, CI 0.21-0.81) and OS (p=0.012, HR=0.40, CI 0.19-0.82), and talquetamab bridge to CAR-T with improved PFS (p=0.042, HR 0.28, CI 0.08-0.95) without reaching statistical significance for OS (p=0.11, HR 0.29, HR 0.07-1.3). MVA results remained similar when the talquetamab bridge to CAR-T cohort was excluded. Conclusions Despite PCL's poor prognosis, talquetamab was superior to BCMA BsAbs in active PCL, with a mPFS of 6.9 mo and mOS of 12.2 mo, aligning with the broader cohort. BCMA BsAbs had poor efficacy in active PCL, even in BCMA naive pts, with a mPFS of 0.7 mo and mOS of 1.4 mo. In historical PCL without active PCL, BCMA BsAbs in BCMA-naive pts showed comparable outcomes to talquetamab. In the overall cohort, talquetamab bridge to CAR-T improved PFS without reaching significance for OS benefit in MVA.

Abstract Background: Talquetamab (Talq), a GPRC5D-targeting bispecific antibody, shows promising activity in relapsed/refractory multiple myeloma (RRMM). However, outcomes in patients (pts) with soft tissue plasmacytoma (STP) remain poorly characterized. Method: We retrospectively analyzed 463 RRMM pts treated with Talq at 15 U.S. centers by Dec 2024. Pts were grouped by presence of STP at Talq start: (1) extramedullary disease (EMD; lesions not contiguous with bone), (2) paraskeletal disease (PSK; bone-contiguous), (3) EMD + PSK, and (4) No-STP. Those receiving Talq as a bridge-to-CAR T (n=103, 22%) were censored at CAR T infusion if progression had not occurred. Time-to-event endpoints were calculated from Talq step-up, using Kaplan-Meier/Cox models. Result: Median age was 66 years (y) (35–89); 54 (11.7%) had EMD, 26 (5.6%) PSK, 60 (13%) EMD+PSK, and 320 (69%) No-STP. EMD pts were younger than No-STP (62 vs 66 y, p=.009), while PSK (66.5) and EMD+PSK (64.5) were similar to No-STP. Median prior lines were higher in PSK (7) vs EMD (5), EMD+PSK (6) and No-STP (6) (p=.035). Median time from diagnosis to Talq was shortest in EMD (3.8 y), followed by EMD+PSK (4.6 y), vs PSK (6.4 y), and No-STP (5.9 y) (p=.015). Among pts with any EMD (EMD or EMD+PSK), 81 (69%) had visceral involvement and 85 (73%) had multiple lesions. Rates of prior BCMA- or GPRC5D-directed therapy, plasma cell leukemia (≥5% circulating plasma cells at the time of Talq), and penta-refractoriness were similar across groups. ECOG ≥ 2 at Talq was more common in EMD (42%), PSK (39%), EMD+ PSK (37%) than in No-STP (23%) (p = .002). Other baseline features were similar. Cytokine release syndrome (CRS) rate/severity were similar across groups. The immune effector cell–associated neurotoxicity syndrome (ICANS) was more frequent in PSK (38%) vs EMD (11%), EMD + PSK (18%), and No-STP (11%), with the most PSK cases (60%, 6/10) being grade ≥2 (p=.006). No difference in CRS/ICANS onset or duration. Infection rates were lower in No-STP (36%) vs EMD (55%), PSK (46%), and EMD+ PSK (48%) (p=.025). Best overall response rates (ORR) were 71% in EMD, 68% in PSK, 67% in EMD+PSK, and 71% in No-STP (p=.9). Complete response (CR) rates were 14% in EMD, 20% in PSK, 13% in EMD+ PSK, and 25% in No-STP (p=.1) [CRs were not required to be confirmatory, which may not meet full IMWG criteria]. Radiographic response was evaluable in 41 EMD (86%), 16 PSK (61.5%), and 48 EMD+PSK (80%) pts, with partial response (PR) or better observed in 48%, 27%, and 38%, respectively. Among pts with any STP, 34% received radiation (XRT) (4 as bridge-to-CAR T), 24 (51%) were evaluable, and 71% (n=17) achieved ≥PR. The median follow-up from Talq initiation was 10.1 months (mo) (95% CI: 8.8–11.4) and was longest in EMD (13.9 mo) compared with PSK (10.8 mo), EMD+PSK (12.4 mo), and No-STP (9.8 mo) (p = .040). Median progression-free survival (PFS) was 4.3 mo (95% CI: 3.6–5.06) in EMD, 4.8 mo (95% CI: 2.2–7.3) in PSK, 3.8 mo (95% CI: 3.1-4.5) in EMD+ PSK, and 8.3 mo (95% CI: 7.0–9.6) in No-STP (p <.001). Among pts receiving XRT for any STP (within 4 weeks prior to or during Talq), responders had longer PFS vs non-responders (15.4 vs. 2.4 mo; p=.009). Multivariable analysis (MVA) showed inferior PFS with EMD (Hazard Ratio (HR) 1.58; 95% CI, 1.04-2.3; p=.029), EMD+PSK (HR 1.91; 95% CI, 1.2–2.8; p = .001), ECOG ≥ 2 (HR 1.4; 95% CI, 1.04–1.9; p = .024), and del(17p) at any timepoint (HR 1.99; 95% CI, 1.1–3.5; p=.017), while longer time from diagnosis to Talq was modestly protective (HR 0.95 per year; p = .016), likely reflecting less aggressive biology in those reaching 5th+ line later. PSK alone showed a non-significant trend toward inferior PFS (HR 1.5; p = .1). Median overall survival (OS) was 13.0 mo (95% CI: not reached [NR]–NR) in EMD, 12.9 mo (95% CI: 6.9–18.9) in PSK, 10.9 mo (95% CI: NR–NR) in EMD+PSK, and NR (95% CI: NR–NR) in No-STP (p = .017). The primary cause of death was disease-related across all groups (p = .6). MVA for OS showed worse outcomes with EMD+PSK (HR 1.7; p=.033), ECOG ≥ 2 (HR 1.98; p <.001), and active PCL at Talq (HR 2.1; p =.010). Conclusion: Soft tissue plasmacytoma, particularly EMD and EMD+PSK, remain strong adverse prognostic factors in Talq-treated patients, with significantly shorter PFS and OS despite similar response rates. Radiation to STP sites was associated with improved outcomes in select cases. Prospective strategies are needed to optimize management for this high-risk population.

Abstract Background Patients (pts) with multiple myeloma and CNS involvement (CNS MM) have poor outcomes, and we recently showed that CAR-T has activity and is reasonable in this population (Gaballa et al., 2025). We sought to evaluate the safety and efficacy of Bispecific T-cell engagers (BsAbs) in CNS MM pts, with specific interest in evaluating ICANS. Methods We conducted a retrospective study of CNS MM pts treated with BsAbs via the MM immunotherapy consortium. Primary endpoints were toxicity rates, with a specific focus on ICANS. Secondary endpoints were systemic responses, CNS responses, and survival outcomes. CNS MM was defined as involvement of the brain parenchyma, spinal cord tissue, leptomeningeal disease, or CSF positivity. CNS response was determined based on CSF and imaging, as complete CNS response, partial CNS response, and non-response/progression. Results The study included 24 pts from 13 US institutions treated with teclistamab (33%), talquetamab (50%), elranatamab (17%), and were used as monotherapy in 83% while 17% received them in combination with either daratumumab or IMiDs. The median age was 64.5 (range 41-82), 50% female, 79% white, and 17% black. High-risk cytogenetics were identified in 39%, 4% had prior primary PCL, and 21% had secondary PCL (2 active within 30 days of BsAb initiation). All pts were triple-refractory, 33% were penta-refractory, and 39% had non-CNS EMD. Pts received a median of 5 prior lines of therapy (IQR 4-7), 71% prior transplant, and 21% prior CAR-T. Prior BCMA therapy was received in 83% of the talquetamab group and 17% of the BCMA BsAbs group (teclistamab and elranatamab). CNS disease was determined based on both imaging and CSF findings in 58%, imaging only in 33%, and CSF only in 8%. Site of CNS disease included 42% brain/cranial nerves, 13% spinal cord, or 46% with both. CNS disease was diagnosed prior to BsAb in 19 pts, with a median interval of 46 days (IQR 7-234), and 3 pts were identified within 2 weeks after BsAb initiation. Two pts identified at days 68 and 121 were included in the safety evaluation but excluded from the efficacy assessments. One pt received teclistamab and intrathecal chemotherapy (IT chemo) as a bridge to CAR-T and achieved a complete CNS response before CAR-T. CNS-directed therapy consisted of: 30% radiotherapy (RT), 30% IT chemo, 13% RT + IT chemo, 9% RT + surgery, and 4% steroids. CRS grade (G) 1-2 occurred in 50%, with no G3-4 CRS. ICANS G 1, 2, and 3 occurred in 13%, 21%, and 4%, respectively, with no G 4 ICANS. One pt developed delayed parkinsonism, and another developed leukoencephalopathy; both had CNS MM diagnosed pre-BsAbs and achieved a CNS response (1 complete, 1 partial). Infections occurred in 67% of pts, with 42% being severe, and 1 infection-related death. The systemic ORR of 18 evaluable pts was 67%, including 22% CR, 17% VGPR, and 28% PR. The overall CNS response of 19 evaluable pts was 58%, including 37% complete CNS response and 21% partial CNS response. Of 11 pts achieving a CNS response, 82% didn't have subsequent CNS progression. In 9 pts achieving CNS response after BsAb initiation, the median time to CNS response was 0.9 months (range 0.03-2.8), with an unreached median duration of CNS response. With a median follow-up of 11 months, the median PFS was 5.0 months (95% CI 2.5-NA) and OS was 12.2 months (95% CI 7.7-NA). No significant difference in median PFS (10.6 vs 4.6 months, p=0.11) or OS (20.2 vs 9.3 months, p=0.37) was observed between BCMA BsAbs (n=11) and talquetamab (n=11). Due to small sample limitation, no significant difference was observed in the median PFS (4.6 vs 8.2 months, p=0.48) or OS (20.2 vs 9.9 months, p=0.73) between BsAb monotherapy (n=19) and BsAb combination therapy (n=3). One pt who received teclistamab as a bridge to CAR-T achieved a complete CNS response and remains progression-free to date, demonstrating the best long-term outcome with a PFS of 674 days. Conclusions Our study demonstrates that BsAb use in pts with CNS MM is safe without increased incidence of ICANS. The use of BsAbs in combination with a multimodal CNS-directed approach led to an overall CNS response rate of 58% and an unreached median duration of CNS response. Previous studies (Gaballa et al., 2025) reported a 100% CNS response rate with CAR-T. In this study, 1 pt treated with BsAb as a bridge to CAR-T had the longest PFS, warranting further research to evaluate this combination's efficacy in this very high-risk population.

Abstract Background Talquetamab (talq) is a GPRC5D-directed bispecific antibody (BsAb) approved for the treatment of relapsed and refractory multiple myeloma (RRMM). The pivotal monumenTAL-1 clinical trial did not include patients with renal impairment (RI, creatinine clearance<40 mL/min) and therefore, data for the use of this agent in RI is lacking. Methods We examined the outcomes of patients with RRMM treated with standard of care (SOC) talq in a multicenter, retrospective cohort study. RI was defined as creatinine clearance (CrCl) <40 mL/min. For each patient we recorded demographics, disease characteristics, prior therapies, incidence and severity of adverse events of special interest, namely cytokine release syndrome (CRS) and immune-cell associated neurotoxicity syndrome (ICANS), along with response, progression-free (PFS) and overall survival (OS). We compared binary variables between different groups using Chi-squared test and assessed progression free survival (PFS) and overall survival (OS) using Kaplan Meier and Cox proportional hazards models. Patients who received talq as a bridge therapy prior to chimeric antigen receptor T-cells (CART cells) were censored for PFS analysis at the time of subsequent therapy. Results We included 417 patients who received SOC Talq and had complete datasets. 91 (22%) had RI, including 20 (5%) on dialysis. The median age was 68 and 65 years for patients with and without RI. Patients with RI were more likely to be female (64% vs. 51%), less likely to have prior CART cells (35% vs. 48%). There were no differences in performance status, race, presence of high-risk cytogenetic abnormalities [del17p, t(4;14), t(14;16), gain/amplification 1q], lines of prior therapy (median 6 vs. 6), prior ASCT (68% vs. 72%), presence of CNS disease (4% vs. 4%), prior plasma cell leukemia (8% vs 9%), prior BCMA therapy (54% vs. 61%) and triple class refractory disease (90% vs. 94%) among patients with and without RI. Rates of CRS (63% vs. 56%, P=0.21) were similar in the two groups, while severe CRS (grade ≥3: 6% vs 2%, P=0.02) was more common in patients with RI. Any grade (20% vs 14%, P=0.21) and high grade ICANS (grade ≥3: 4% vs 4%, P=0.97) were similar in patients with and without RI. There was no difference between groups on risk of infection (P=0.65) with cumulative risk at 6 months of 39% vs. 40%. With 11.1 months of median follow up, the overall response rate (60% vs 67%; P = 0.12), and progression-free survival (median 7.3 vs. 6.5 mo.; P = 0.9) were comparable between the two groups. There was no difference in outcomes according to RI in both patients previously treated with BCMA-directed therapy and BCMA-naïve. Conversely, among patients with RI, median PFS was 4.6 and 8.5 mo. for patients with and without prior BCMA therapy. Similarly, among patients without RI, median PFS was 6.5 and 6.2 mo, respectively. Among BCMA-naïve patients, there was no difference in OS between patients with and without RI (median not reached, 12 mo. OS rate 71% vs. 73%, P=0.53), while among patients with prior BCMA-directed therapy there was a trend towards better OS for patients without RI (median 8.9 vs. 13.8 mo; 12 mo. OS rate 43% vs 59%, P=0.06). Five patients (25%) became dialysis independent following talq therapy. On multivariable analysis, ECOG >1 (HR 1.62, 95% C.I. 1.25-2.10, P<0.001) and deletion of 17p (HR 1.55, 95% C.I. 1.17-2.06, P=0.003) but not RI or prior BCMA-directed therapy affected PFS. OS was affected by ECOG >1 (HR 2.37, 95% C.I 1.71-3.30, P<0.001), triple-class refractoriness (HR 3.03, 95% C.I. 1.12-8.21, P=0.03) and prior BCMA-directed therapy (HR 1.79, 95% C.I. 1.24-2.59, P=0.002) but not by RI. Conclusion Our findings support the feasibility of talq in patients with RI, including those on dialysis, with similar safety and efficacy profile to patients without RI. While neither prior BCMA-directed therapy nor RI affect PFS, refractoriness to conventional agents and prior exposure to BCMA-directed therapy adversely affects OS. This observation likely reflects better post progression survival following talq due to the availability of efficacious therapeutic options, including those directed at BCMA.

Abstract Marginal zone lymphoma (MZL) is an uncommon non-Hodgkin B-cell lymphoma accounting for 7-10% of lymphoma diagnoses. Extranodal MZL (EMZL) of mucosa-associated lymphoid tissue (MALT) is the most common subtype (61%) of MZL. While the mutational landscape, chromosomal aberrations and transcriptome of nodal and splenic MZL have been extensively evaluated, the mutational landscape of EMZL has only been evaluated in a small number of patients and mainly by targeted sequencing. Consequently, the comprehensive genomic landscape of EMZL remains largely uncharacterized. Herein, we performed whole exome sequencing followed by targeted sequencing of potential tumor driver genes, copy number and/or RNA transcriptome analyses in 165 patients with pretreatment EMZL tumors involving 16 anatomic locations. All samples were collected and underwent expert review as part of the Atlas of Blood Cancer Genomes consortium. The most common anatomic locations were ocular adnexa (OAMZL) (n=35), gastric (n=25, including 6 positive for Helicobacter pylori), salivary glands (n=25), and lungs (n=24). Using common criteria for variant mutation calling and significant focal copy number (CN), we identified 1218 variants (1030 missense and 188 truncation mutations) across 174 genes and 2837 CN focal alterations (1614 copy gains and 1223 copy number losses). Of these genes, 44 and 11 were mutated in >5% and >10% of specimens, respectively. We detected variants identified previously by targeted sequencing in EMZL from different locations (e.g. TNFAIP3 (A20) (12%), TBL1XR1 (13%), SPEN (10%), CARD11 (7%), TET2 (7%) and CREBBP (6%)). We detected mutations in KLF2 (10 mutations in 8 EMZL patients) and PTPRD (7 mutations in 7 EMZL patients) that were previously suggested to be specific for splenic and nodal MZL, respectively. We also detected variants not previously reported in EMZL, including a transcriptional factor ZEB2, LRP1B,and others. The most frequently mutated gene in our study (25% of tumors) was IGLL5. Some mutations were limited to specific locations (e.g. ZEB2 mutations seen exclusively in gastric and salivary gland EMZL), while most were observed across all anatomic locations. There was no association between specific mutations and clonal IGHV, in contrast to previous reports. Using Enrichr tool, we observed enrichment of mutations in genes belonging to the B cell receptor activation, NOTCH signaling, Wnt-beta catenin signaling, NF-kB signaling , PI3K AKT signaling, DNA repair and other pathways. Chromosomal and copy number changes were also commonly observed including previously reported trisomy of chromosomes 3 and 18. Combining DNA mutations and CN alterations, the number of genetic lesions per tumor sample in the 174 mutated genes ranged from 0 to 95, with an average load of 17 lesions per case. RNA sequencing was successful in 159 EMZL tumors from 16 distinct anatomic locations. Unsupervised clustering using all genes with a median log2-normalized gene expression value greater than 5 and a standard deviation greater than 1 (1323 genes) demonstrated that the majority of gastric EMZL with and without H. pylori infections clustered together on 2 dendrograms as did most of the samples of OAMZL. Since the clustering could be forced by organ-specific and not tumor-specific gene expression, we next focused on the expression of the 345 genes from the LM22 matrix that passed our transcriptomic row filtering. Unsupervised clustering resulted in clustering of most gastric EMZL irrespective of H. pylori positivity together in the same dendrogram branch, accompanied by few additional EMZL from other anatomic locations. Most of the EMZL samples from other locations did not show preferential co-clustering together. On comparison of gene expression between gastric and OAMZL, there was enrichment of the B-cell receptor signaling pathway, B-cell activation, B-cell naïve and B-cell memory cells, B-cell proliferation and NF-kB signaling in the latter. Immune microenvironment analysis showed a statistically significant increase in resting mast cells and decrease in M1 macrophages in gastric EMZL and increase in regulatory T cells in salivary EMZL. The broad genomic studies reported here underscore the biological similarity of EMZL across anatomical sites with the potential exceptions of gastric EMZL (regardless of H. Pylori status). These data provide valuable genomic and transcriptomic resources to inform future diagnostic and therapeutic strategies.

Abstract Background: Multiple myeloma (MM) remains incurable, though key advances such as chimeric antigen receptor T-cells (CAR-T) and immunomodulatory agents, now evolving toward cereblon E3 ligase modulatory drugs (CELMoDs), have substantially improved the longevity and quality of life for patients (pts). Idecabtagene vicleucel (ide-cel) is a CAR-T targeting B-cell maturation antigen (BCMA), now US FDA-approved for pts who have received ≥2 prior lines of therapy including a proteasome inhibitor, immunomodulatory agent, and CD38 monoclonal antibody. Ide-cel was initially FDA-approved for ≥4 prior lines of therapy based on the KarMMa-1 study, which demonstrated a median progression-free survival (PFS) of 8.8 months across all cell doses and median overall survival (OS) of 19.4 months (Munshi et al., New Eng J Med 2021). Although promising, the fact that virtually all pts relapse post-ide-cel indicates that further progress is needed. To that end, iberdomide is an investigational CELMoD that in combination with dexamethasone has demonstrated a 30% response rate in early phase studies of triple class-refractory MM (Lonial et al., Lancet Haem 2022). Additionally, in laboratory-based correlative studies, iberdomide, at doses of ≤1 mg (well below the recommended phase 2 dose of 1.6 mg) was shown to augment immune function, including enhanced T-cell activation and cytotoxicity, and modulation of the cytokine milieu (Amatangelo et al., Cell Rep Med 2024). Iberdomide's combined properties of direct MM cytotoxicity and T-cell potentiation have clear, potential relevance to CAR-T clinically, providing the conceptual basis for the CADMIUM study (NCT06179888), exploring the effects of iberdomide as post-ide-cel maintenance therapy in MM. Study Design and Methods: This is a randomized phase II trial with a safety run-in to evaluate if treatment with iberdomide maintenance post-ide-cel can significantly improve PFS vs. standard of care (SOC) observation without therapy, in pts with relapsed/refractory MM with ≥4 prior lines of therapy, who have received ide-cel within 3 months of registration, and no evidence of MM progression or additional MM therapy since ide-cel. Pre-ide-cel iberdomide exposure is permissible but refractoriness is not. The safety run-in will confirm tolerability of the iberdomide dose to be carried forward, where doses to be tested include: iberdomide 1 mg orally on days 1-21 of a 28-day cycle (dose level 1; DL1) and iberdomide 0.7 mg on days 1-21 of a 28-day cycle (DL2). Dose-limiting toxicities (DLTs) include any of the following during the DLT period of a pt's first three months on iberdomide: prolonged Grade 3 non-hematologic toxicities, Grade 4 non-hematologic toxicities, prolonged Grade 4 neutropenia or thrombocytopenia, or any adverse event requiring iberdomide interruption for >4 weeks. Six pts will be enrolled onto DL1; if at most 1 of these pts has a DLT, DL1 will be carried forward to the randomized part of the study. Otherwise, 6 pts will be enrolled onto DL2. The randomized part of the trial will randomize 60 pts 1:1 to either iberdomide or SOC observation without therapy. A 1-sided log-rank test with α=0.15 has 81% power to detect a true hazard ratio (iberdomide/SOC) of 0.55 or less, corresponding to an improvement in median PFS to 16 vs. 8.8 months with SOC. One interim analysis for futility is planned. Secondary outcomes include OS, best response by International Myeloma Working Group (IMWG) criteria, and deepening of response, particularly conversion to complete response with a bone marrow minimal disease-negative state by Adaptive clonoSEQ (sensitivity 1e-6). Robust correlative studies will include CAR-T persistence, assays of T- and other immune cell function, and pathological analyses of whether BCMA expression on MM cells (prior to enrollment or at relapse) or other markers predict clinical outcomes. Study status: To date, 12 pts have been screened, with 7 pts enrolled on study as part of the safety run-in (1 patient replaced). Enrollment data will be updated at presentation. Notably, an amendment is forthcoming which will enhance correlative studies and broaden eligibility criteria to include patients who have received ≥2 prior lines of therapy, conforming with ide-cel's current FDA label. Study COI: BMS is supporting correlative studies. Study Support: U10CA180821, U10CA180882; BMS; U10CA180868 (NRG Oncology); http://acknowledgements.alliancefound.org

Abstract Background: Systemic mastocytosis (SM) comprises a spectrum of subtypes characterized by neoplastic mast cell (MC) infiltration of tissues and release of MC mediators. Non-advanced SM (NonAdvSM), including indolent SM (ISM), smoldering SM (SSM), and bone marrow mastocytosis (BMM) subtypes, is the most prevalent form of SM. NonAdvSM can be associated with debilitating symptomology which can significantly impair quality of life. The gain-of-function somatic KIT c.2447 C>T (p.D816V) mutation is found in up to 95% of patients with SM. Bezuclastinib (CGT9486) is an oral, potent, and selective type 1 tyrosine kinase inhibitor with activity against KIT D816V. Results from Summit (NCT05186753) Part 1 informed the recommended phase 2 dose (100 mg QD bezuclastinib) for Part 2. We report topline results from the 24-week assessment of Summit Part 2. Methods: Summit is a multi-center, randomized, double-blind, placebo (PBO)-controlled Phase 2 trial of bezuclastinib in patients with NonAdvSM who had inadequate symptom control despite best supportive care (BSC) medications. The primary endpoint was 24-week mean change from baseline in Mastocytosis Symptom Severity Daily Diary (MS2D2) total symptom score (TSS) (range 0–110), which is a fit-for-purpose patient-reported outcome measure of NonAdvSM symptom severity. Key secondary endpoints included the proportion of patients with ≥50% reduction in serum tryptase, KIT p.D816V variant allele frequency (VAF), bone marrow (BM) MC burden, and MS2D2 TSS, ≥30% TSS reduction. Patients were randomized 2:1 to receive 100mg QD bezuclastinib + BSC or PBO + BSC. Results: As of May 22, 2025, 179 patients were enrolled in Part 2: 119 were randomized to receive bezuclastinib and 60 to placebo. Patients enrolled were representative of the NonAdvSM population with moderate to severe symptoms. Median age (range) was 51 (23-78) years; 65.9% female; mean (SD) baseline MS2D2 TSS 55.6 (19.8); 82% of patients had ISM, 11% had BMM, and 7% had smoldering SSM. At baseline, median (range) KIT p.D816V VAF in whole blood, BM MC burden, and serum tryptase was 0.25% (0-34%), 10% (1-75%), and 40 (6-692) ng/mL, respectively. Bezuclastinib demonstrated statistically significant superiority to placebo on all primary and key secondary endpoints. At Week 24, bezuclastinib led to significantly greater symptom improvement vs placebo (LS mean [95% CI] MS2D2 TSS change: –24.3 [–27.6 to –21.1] vs –15.4 [–19.6 to –11.2]; placebo-adjusted difference: –8.9 points; P=0.0002). A ≥50% reduction in serum tryptase was achieved in 87.4% of bezuclastinib-treated patients vs 0% on placebo (P<0.0001). Significantly more patients receiving bezuclastinib achieved ≥50% reductions in KIT D816V VAF, serum tryptase, BM MCs (P<0.0001), MS2D2 TSS (P=0.01), and ≥30% reduction in MS2D2 TSS (P=0.0004). Most treatment-emergent adverse events (TEAEs) were low grade (gr; 70% Gr 1) and reversible. The most common TEAEs (≥10%) in any treatment group and occurring in greater frequency in the bezuclastinib arm were hair color changes (69.5% vs 5.0%), altered taste (23.7% vs 0%), nausea (22.0% vs 13.3%), increased ALT/AST (22.0% vs 6.6%), headache (17.8% vs 11.7%), alopecia (11.9% vs 3.3%), and increased ALP (10.2% vs 3.3%). TEAEs (≥10%) that occurred more often in the placebo group were diarrhea (13% vs 18%), dizziness (10% vs 12%), fatigue (7% vs 12%), and arthralgia (6% vs 15%). ALT/AST elevations ≥Gr 3 were experienced by 5.9% of patients. The only hepatic adverse events (AEs) reported were transient lab abnormalities; none required hospitalization. Treatment-related AEs requiring dose reductions occurred in 11% of patients receiving bezuclastinib. All discontinuations (5.9%) due to treatment-related AEs were due to transaminase elevations; all fully resolved. Conclusions: At 24-weeks, bezuclastinib 100 mg QD demonstrated statistically and clinically significant improvements in symptom burden and biomarkers of disease vs placebo in patients with NonAdvSM. The treatment was generally well-tolerated and effective across a population that is representative of the real-world NonAdvSM population, including SSM. These results support the use of bezuclastinib to reduce SM burden and symptoms in pts with NonAdvSM, and a potentially disease-modifying impact.