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Abstract Introduction: Anti-CD19 chimeric antigen receptor T-cell (CART) therapy is feasible with an acceptable safety profile in older patients (pts) with relapsed/refractory (RR) large B-cell lymphoma (LBCL) (Tun et al, AJH 2024). However, immune effector cell-associated neurotoxicity syndrome (ICANS) is a frequent and challenging toxicity in older pts, and its characteristics and associated risk factors are not well defined. Methods: Seven centers participated in this retrospective study. Pts aged ≥65 years (yrs) with RR LBCL treated with a commercial CART product were included. Baseline characteristics, treatment, CART toxicity, and outcomes were collected. ICANS was graded by the ASTCT criteria in most pts. Cumulative incidences of ICANS were estimated using deaths/progressions as competing risks, and associations between incidences and variables were assessed by Gray's test. A 30-day landmark was set after infusion to reduce immortal time bias. Progression-free survival (PFS; time from the landmark to disease progression or death) and overall survival (OS; time from the landmark to death) were analyzed with the Kaplan-Meier method. Statistical analyses were done in JMP v18. Results: A total of 224 pts were included. Median age at infusion was 71 yrs (range 65–89; ≥80 yrs, 12%. 142 (63%) were male and 27 (13%) had an ECOG PS scale of ≥2. The median HCT CI was 1 (range 0–6). LDH was elevated in 110 (51%) pts, 23 (19%) had bulky disease ≥7 cm, 176 (82%) had advanced-stage, and 145 (71%) had extranodal disease. Median number of prior treatments was 2 (range 1–8), and 44 (20%) had prior bendamustine. Prior stem cell therapy was done in 47 (21%) pts (autologous stem cell transplant [SCT], n = 45; allogeneic SCT, n=2). Axicabtagene ciloleucel (axi-cel) was most frequently used (58%; n=131) followed by lisocabtagene maraleucel (liso-cel) (16%, n=36) and tisagenlecleucel (tisa-cel) (25%, n=57). Median duration of ICANS was 6 days (interquartile range [IQR] 3–11; range 1–303). Median time to ICANS onset was 6 days (IQR 3.8–8.0; range 0–24). The 30-day cumulative incidence of all grade ICANS was 50.9% (95% confidence interval [CI] 44.7–57.9) and grade ≥3 ICANS was 29.8% (95% CI 24.0–37.0). There was no significant difference in incidence of all grade (P=0.39) and grade ≥3 (P=0.49) ICANS as well as duration of ICANS (≥14 vs <14 days; P=0.08) according to the age groups (≥65–69 vs ≥70–74 vs ≥75–79 vs ≥80–89). In contrast, pts with an ECOG PS scale of ≥2 were associated with a higher incidence of all grade (30-day estimate, 66.7% vs 47.0%; P=0.02) and grade ≥3 ICANS (30-day estimate, 53.8% vs 25.6%; P=0.002). In addition, pts with an elevated LDH level had a higher incidence of grade ≥3 ICANS than those without (30-day estimate, 37.5% vs 18.8%;P=0.004). The incidence of ICANS varied among various CART products, with 30-day estimates of 64.9% vs 33.3% vs 29.8% (P<0.0001) for all grades and 40.1% vs 13.2% vs 18.0% (P=0.004) for grade ≥3 ICANS in pts treated with axi-cel vs tisa-cel vs liso-cel, respectively. A trend toward higher grade ≥3 ICANS was seen in pts treated with ≥3 prior lines than those treated with 2 or 1 (30-day estimate, 35.7% vs 28.1% vs 10.5%; P = 0.07). ICANS was managed with steroids in 47 (41%) pts, levetiracetam +/- other agents in 46 (40%) pts, biologic agents +/- other drugs in 15 (13%) pts, and supportive care in 6 (5%) pts. Median follow-up from the 30-day landmark post-infusion was 17.2 months (95% CI 14.2–22.4). Median PFS was 10.5 months (95% CI 5.7–18.2) and OS was 18.2 months (95% CI 13.3 vs 27.5). There was no difference in PFS and OS in pts who experienced ICANS vs no ICANS (median PFS 14.7 vs 10.1 months; P=0.65 and median OS 18.2 vs 24.7 months; P=0.49). However, there was a trend toward inferior PFS and OS in pts who experienced high-grade ICANS compared to those who had grade 0-2 ICANS (median PFS 9.2 vs 21.2; P=0.14 and median OS 11.7 =vs 22.9; P=0.39). Conclusions: This large study of older pts with RR LBCL demonstrated acceptable risks of ICANS, comparable to that in pivotal registration trials, with a relatively higher rate of grade ≥3 ICANS. The risks of ICANS were similar regardless of patient age, including those aged ≥80 yrs, but different among CART products. Similar to younger pts, high tumor burden disease and poor performance status at CART infusion were associated with higher risks of ICANS. A comprehensive neurologic and frailty assessment is warranted to identify suitable CART candidates.

Abstract Introduction There is currently no standard-of-care for patients (pts) who cannot tolerate full dose anthracycline regimens in frontline large B-cell lymphoma (LBCL). R-miniCHOP is a commonly used regimen that provides curative intent treatment with manageable toxicity. Despite this, lymphoma and treatment-related mortality are the leading causes of death in these pts. Additionally, many pts may not be eligible to receive R-miniCHOP due to comorbidity or frailty. There are limited clinical trial and real-world data focused on this population. Methods Pts with LBCL age 18 years (yrs) and older were identified from the Lymphoma Epidemiology of Outcomes (LEO) cohort, a prospective study of newly diagnosed pts with non-Hodgkin lymphoma enrolled from 2015-2020 at 8 academic medical centers in the US. Pts with LBCL were included in this analysis if they had received R-miniCHOP or a regimen that did not include an anthracycline (nonAC). NonAC regimens included R-CVP, BR, rituximab, radiation and lenalidomide and rituximab. Pts completed the Vulnerable Elders Survey (VES-13) and were considered vulnerable if they had a score >3. Event-free survival (EFS) was defined as the time from start of treatment until progression/relapse, retreatment, or death due to any cause; EFS at 24 months (EFS24) was a secondary endpoint. Overall survival (OS) was defined as the time from start of treatment until death due to any cause. EFS and OS for R-miniCHOP and non-IC groups, as well as vulnerable and not vulnerable by VES-13 were estimated using Cox models. Results A total of 190 pts received R-miniCHOP (N=139) or nonAC (N=51). R-miniCHOP-treated pts were older (median 82 vs 72 yrs) and more commonly female (55% vs 35%). The majority in both groups (86% vs 78%) received their treatment at a LEO center and did not receive therapy on a clinical trial (89% vs 100%). Most pts receiving R-miniCHOP had high-intermediate (32%) or high (30%) international prognostic index (IPI) score, while both high-intermediate (22%) and high (20%) IPI were lower in the nonAC-treated pts. Cell of origin was determined by immunohistochemistry as available clinically, with GCB 42% vs 31%, non-GCB 32% vs 29%, and not done/unknown 26% vs 39% in R-miniCHOP vs nonAC pts. Double-hit status by FISH was known in 115 pts and was positive in 13% of R-miniCHOP pts and 10% of nonAC pts. The diagnosis-to-treatment interval (DTI) was ≤14 days in 30% of R-miniCHOP pts and 24% of nonAC pts. Of pts who had a VES-13 score (N=119), vulnerable status trended higher in the R-miniCHOP (66%) vs the non-IC group (50%; p=0.15). With a median follow-up of 50.5 months, the median EFS was 37.1 months and median OS was 50.0 months. R-miniCHOP, compared with non-IC, was associated with improved EFS (unadjusted HR=0.54, 95% CI 0.36-0.81; p=0.003) and OS (unadjusted HR=0.58, 95% CI 0.38-0.88; p=0.011). When adjusted for age, IPI, LBCL subtype (diffuse large B-cell lymphoma, not otherwise specified vs other), DTI and VES-13, R-miniCHOP was strongly associated with improved EFS (HR=0.26, 95% CI 0.14-0.50; p<0.001) and OS (adjusted HR=0.29, 95% CI 0.15-0.57; p<0.001). EFS24 rate was 56% in all pts and was superior in pts treated with R-miniCHOP vs non-IC (62.7% vs 34.1%; p=0.001). In the R-miniCHOP group, vulnerable status (adjusted for IPI) was associated with inferior OS (HR=2.22, 95% CI 1.09-4.50; p=0.028) and trended towards inferior EFS (HR=1.76, 95% CI 0.93-3.32; p=0.083). In a competing-risk cumulative-incidence analysis, lymphoma was the leading cause of death for pts receiving R-miniCHOP at 2 (0.16, 95% CI 0.11-0.24) and 5 (0.20, 95% CI 0.14-0.28) yrs, as well as for those receiving non-IC at 2 (0.35, 95% CI 0.24-0.53) and 5 (0.38, 95% CI 0.26-0.56) yrs. Treatment-related mortality was similar in both groups. In the R-miniCHOP group, the 2-yr (0.20 vs 0.03) and 5-yr (0.20 vs 0.11) lymphoma-related mortality was higher in pts who were vulnerable vs not by VES-13, while there were no differences for mortality due to therapy or other causes by vulnerable status. Conclusions These data support R-miniCHOP as a curative regimen in older and frail pts with the majority achieving EFS24. R-miniCHOP compared to non-IC use is strongly associated with improved EFS and OS when adjusted for disease and patient related variables. Within the R-miniCHOP group, vulnerable status is associated with inferior OS. Additional research efforts are needed to optimize outcomes for this group of pts.

Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Abstract Cyclin D1, encoded by CCND1, is a cell cycle regulator, overexpressed in ~15% of multiple myeloma (MM) cases via CCND1::IGH super-enhancer juxtaposition through t(11;14). Cyclin D1 also plays a non-canonical role in transcriptional regulation, but in t(11;14) MM its function in gene regulation remains undefined. We investigated the global transcriptional and epigenomic consequences of CCND1overexpression in t(11;14) MM. To define a CCND1 signature, RNA-seq from two independent primary MM patient cohorts, CoMMpass and Mayo, was utilized to compare high CCND1 t(11;14) cases (≥300 transcripts-per-million [TPM], n=271) vs. low CCND1 hyperdiploid cases (<30 TPM, n=233). Two CCND1 knockout (KO) clones in t(11;14) MM U266B1 were also generated by CRISPR/Cas9, introducing a frameshift insertion (A) after chr11:69641478 (hg38) in exon 1. ATAC-seq and ChIP-seq (H3K4me3, H3K4me1, and H3K27ac) were performed in duplicates, and RNA-seq in triplicates in U266B1 wild-type (WT) and KO. Libraries were sequenced on Illumina NextSeq 2000 (2x51 bp for ChIP/ATAC, 2x150 bp for RNA-seq). Reads were mapped to hg38 by BWA (ChIP/ATAC) or STAR (RNA-seq), peaks called by MACS2 (FDR< 0.01), peak and gene raw counts estimated by featureCounts. Differential peaks (fold-change ≥1.5) and differentially expressed genes (fold-change ≥2) were identified by edgeR (FDR<0.05), including peaks detected in ≥2 samples and genes with TPM ≥0.1 in ≥1 sample. Interactions between promoters and distal regulatory regions were identified using publicly available chromatin interaction data in blood cell types. Pathway analysis was performed using Enrichr. Co-immunoprecipitation was performed in t(11;14) KMS12BM cells. Differential analysis comparing CCND1-high t(11;14) and CCND1-low MM cases in the two patient cohorts identified 21 upregulated and 21 downregulated genes associated with CCND1 expression which were also captured in the wild-typevs. CCND1 KO U266 cells. Enriched pathways (p<0.05) included Notch signaling, early/late estrogen response, epithelial-mesenchymal transition and reduced mitotic spindle and myogenesis. Dysregulated genes included those related to apoptosis, ubiquitin-proteosome, extracellular matrix, adhesion, and immune response, demonstrating a broader role for cyclin D1 in MM beyond cell cycle control. To explore the epigenomic basis of this transcriptional regulation, for each of the 42 differentially expressed genes we examined the changes of histone marks and chromatin accessibility in promoter and the interacting distal regulatory regions in the U266 KO model. Ten of the 21 genes upregulated in CCND1-high (downloaded in KO; e.g., argininosuccinate synthase 1 [ASS1], PMAIP1, MYEOV, CCR7, and DTX1) and 12 of the 21 genes downregulated in CCND1-high (upregulated in KO; e.g., UACA, RASAL2, PTPRZ1, PPT2, and IL23R) showed concordant changes in histone marks and/or chromatin accessibility, predominantly in distal regulatory regions, suggesting a chromatin-mediated mechanism of gene regulation by cyclin D1. The most prominent changes involved H3K27ac, a mark defining active enhancers. As H3K27ac is deposited by histone acetyltransferases CBP, we tested for the possible cyclin D1-CBP interaction. Co-IP confirmed this interaction, suggesting a role for this complex in chromatin remodeling and transcriptional control in t(11;14) MM. One gene notably upregulated in association with CCND1 is ASS1, which encodes a urea cycle enzyme responsible for endogenous arginine synthesis. Metabolomic studies demonstrated KO cells had elevated aspartate and citrulline and lowered arginine and ornithine compared to WT cells (p<0.01) demonstrating impaired urea cycle function. Further, KO cells displayed significantly reduced ASS1 protein expression, cell growth and S-phase entry compared to WT cells in arginine-replete conditions, with both WT and KO cell types further inhibited by arginine depletion (p<0.05). Together, a cyclin D1-associated gene signature was identified supporting its role in t(11;14) MM beyond the CDK4/6 mediated cell cycle control, including a role in metabolic plasticity and survival under arginine depleted conditions. These findings highlight cyclin D1 as a therapeutic vulnerability and open new avenues for personalized treatment strategies.

Abstract Background: Pulmonary function tests, forced expiratory volume in 1 s (FEV₁) and diffusing capacity for carbon monoxide (DLCO), are integral to pre-transplant evaluation of allogeneic hematopoietic cell transplantation (HCT) candidates because they estimate the risk of early post-HCT death and respiratory failure. Interpretation has historically relied on race-specific Global Lung Function Initiative equations from 2012 (GLI-2012). In 2021 the Initiative released race-neutral equations (GLI-Global). The influence of adopting GLI-Global on risk stratification, outcome prediction, and transplant eligibility is unknown. Methods: We retrospectively analyzed 8808 adults who underwent first allogeneic HCT at four United States centers between 1999 and 2021. FEV₁ values were converted to z-scores with both GLI-2012 and GLI-Global, whereas DLCO z-scores were calculated with GLI-2017 which is a race neutral equation. Pulmonary impairment was graded with the Lung Function Score (LFS); each component [FEV₁ and DLCO] receives 1 to 6 points based on percent predicted (> 80 % = 1, 70-79 % = 2, 60-69 % = 3, 50-59 % = 4, 40-49 % = 5, < 40 % = 6) and the sum of 2 to 12 maps to grades I (2), II (3-5), III (6-9), and IV (10-12). Primary endpoints were non-relapse mortality (NRM) at 120 days and 2 years, intensive care unit admission, and invasive mechanical ventilation. Prediction was assessed with Cox proportional hazards models and Harrell c-statistics. Results: Switching to GLI-Global reclassified 4.2 % of patients (368 of 8808) across LFS strata. Reclassification was racially asymmetric: 12.2 % of Black patients moved to higher-risk grades whereas 3.9 % of White patients moved to lower-risk grades. C-statistics for FEV₁ z-scores were nearly identical with GLI-Global versus GLI-2012: 2-year NRM 0.544 vs 0.542, 120-day NRM 0.566 vs 0.568, intensive care admission 0.545 vs 0.538, and mechanical ventilation 0.605 vs 0.605; confidence intervals overlapped for every comparison. Continuous z-score models consistently outperformed categorical cut-offs for each outcome: 2-year NRM 0.544 vs 0.518, 120-day NRM 0.566 vs 0.523, intensive care admission 0.545 vs 0.515, and mechanical ventilation 0.605 vs 0.529; confidence intervals did not overlap for every comparison. The composite LFS outperformed models that used FEV₁ or DLCO alone. Extrapolating cohort reclassification rates to 38,606 adults aged 40 to 84 who received allogeneic HCTs reported to the Center for International Blood and Marrow Transplant Research between 2009 and 2018 predicts that 1521 patients, including 509 Black adults, would shift LFS grades and could face altered transplant eligibility. Conclusions: Race-neutral GLI-Global equations modestly change pulmonary risk categorization, disproportionately raising scores for Black HCT candidates, yet maintain predictive accuracy for early mortality, respiratory failure, and intensive care use. Continuous dual-variable models and the composite LFS provide superior prediction. Although race-neutral interpretation aligns with current society guidelines, its tendency to classify Black individuals as higher risk highlights the need for refined continuous models that limit unnecessary reclassification and increased disparities in transplant eligibility.

Abstract Introduction: While newly diagnosed patients (pts) with acute myeloid leukemia (AML) who are ineligible for intensive chemotherapy have prolonged survival outcomes with venetoclax plus azacitidine (VEN+AZA) over AZA alone (2-year overall survival rate: 37.5% vs 16.9%), more can be done to further enhance outcomes (Pratz et al., 2024). CD123 is overexpressed on AML blasts and leukemia stem cells in AML. Pivekimab sunirine (PVEK) is a first-in-class antibody-drug conjugate comprised of a high-affinity anti-CD123 antibody, a cleavable linker, and an indolinobenzodiazepine pseudodimer payload. Previously, in pts with CD123-positive AML, PVEK combined with VEN+AZA demonstrated robust response rates with a manageable safety profile (Daver et al., 2023). Here we report a subgroup analysis from a preliminary cohort of frontline (1L)-treated pts with AML. Methods: Data are from the dose expansion phase of an ongoing, open-label, multicenter, fully enrolled, Phase 1b/2 study of PVEK+VEN+AZA in adults with 1L unfit AML deemed CD123-positive by investigator. Unfit pts were aged ≥75 years (yr), or aged <75 yr with Eastern Cooperative Oncology Group performance status (ECOG PS) score 2–3, or ≥1 defined comorbidity. Pts received PVEK (0.045 mg/kg, intravenous [IV]) on Day (D) 7 plus VEN (400 mg equivalent, oral) daily in a 28-D cycle (cohort 1 received ≥14 D of VEN; cohort 2 received 28 D of VEN) plus AZA (up to 75 mg/m2, subcutaneous or IV) on D1–7. Bone marrow assessments were performed by D12–14 (cohort 1) or D18–21 (cohort 2) to determine VEN duration in cycle 1 and at the end of every subsequent cycle to assess responses and myelosuppression. The primary endpoint was antileukemia activity (complete remission [CR] rate) and measurable residual disease (MRD) assessments. Responses were determined using the modified European LeukemiaNet 2017 criteria (plus CR + partial hematologic recovery [CRh]). MRD-negativity was defined centrally as <0.1% using multiparameter flow cytometry. Safety was assessed as a secondary endpoint. Results: Among 1L unfit pts with CD123-positive AML (n=49), the median (range) age was 77 (58–85) yr, with most pts aged ≥75 yr (n=36 [74%]). Forty-two (86%) pts reported an ECOG PS ≤1, 14% (n=7) had secondary AML, and 20% (n=10) and 51% (n=25) had intermediate or adverse cytogenetic risk, respectively; 65% (n=32) and 35% (n=17) were reported as TP53wt or TP53mut, respectively. Eight (16%) pts bridged to stem cell transplant. The median (range) number of treatment cycles and duration of treatment were 4 (1–20) and 5.5 (0.7–22.7) months (mo), respectively, for PVEK; 4 (1–20) and 5.1 (0.9–22.9) mo for VEN; and 4 (1–21) and 5.7 (0.9–23.4) mo for AZA. For cohort 1 (n=10), the median (range) duration of VEN was 4.5 (2.1–22.9) mo, and for cohort 2 (n=39), the median (range) duration of VEN was 5.7 (0.9–15.2) mo. With a median (range) follow-up of 10 (1.2–26.7) mo, 63.3% (95% CI: 48.3%–76.6%) of pts achieved CR, 79.6% (95% CI: 65.7%–89.8%) achieved CR/CR with incomplete hematologic recovery (CRi), and 73.5% (95% CI: 58.9%–85.1%) achieved CR/CRh; morphologic leukemia free state was achieved in 4% (n=2) of pts. Of pts who achieved CR or CR/CRi with a MRD-evaluable sample, 92% (23/25) and 90% (27/30) achieved flow cytometry MRD-negativity (<0.1%) respectively. The most common (≥50% of pts) any grade treatment-emergent adverse events (AEs) were neutropenia/neutrophil count decreased and thrombocytopenia/platelet count decreased (both 69%); constipation (61%); and peripheral edema (51%). Three pts (6%) experienced AEs leading to discontinuation (myocardial infarction/soft tissue infection/thrombocytopenia) and 2 pts had AEs leading to death (respiratory failure/pancytopenia). Conclusions: Unfit pts with newly diagnosed CD123-postive AML demonstrated high CR rates with PVEK+VEN+AZA. These robust response rates were observed across the select mutational profiles tested. Follow up with duration of response and survival estimates among all pts, by molecular subgroups and MRD negativity status, are being evaluated. Triplet therapy in unfit 1L pts with CD-123–positive AML was well-tolerated, and no new safety signals were observed. These data highlight the need to further evaluate this regimen in a randomized trial.

Abstract Background: Prolonged cytopenias are a well-recognized complication following CAR-T therapy, leading to increased morbidity and healthcare utilization. Autologous SCB offers a potential strategy to promote hematologic recovery. We conducted a retrospective multi-institutional analysis across 18 centers comparing outcomes of SCB versus supportive care alone in RRMM patients who experienced prolonged cytopenias >30 days after CAR-T infusion. Methods: Patients were included if they received SCB within 1 year after commercial CAR-T between 6/2021 and 3/2024. To identify matched controls, we reviewed other CAR-T recipients from the same consortium and selected those with an absolute neutrophil count (ANC) of <0.72x109/L and platelet count of <21K at day 30 post-infusion-thresholds representing the 75th percentile of cytopenia severity in the SCB cohort. These criteria ensured control patients had comparable hematologic toxicity but without SCB. Hematologic recovery in the SCB cohort was assessed using the CIBMTR engraftment criteria. For the non-SCB (nSCB) group, cell counts were analyzed cross-sectionally at day 90 post-CAR-T and compared to the SCB cohort with Kruskal Wallis tests. Progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan Meier methods. Results: Of the 590 CAR-T recipients, 91 patients (15.4%) developed prolonged cytopenias; 39 patients received SCB and 52 did not. SCB patients more frequently had ISS stage III disease (23.1% vs. 11.5%), exrtamedullary disease (59% vs. 46.2%) and penta-refractory status (43.6% vs. 34.6%). The median number of prior lines of therapy was 6 in both cohorts. Thirteen patients (33.3%) in the SCB and 11 (21.2%) in the nSCB received high intensity infusional chemotherapy (DCEP/PACE/HyperCVAD). Pre-CAR-T cytopenias tended to be less frequent in the SCB vs. nSCB cohort: ANC <1000 in 5.1% vs. 13.5%, Hgb <8 in 23.1% vs. 21.2%, and platelets <50K in 28.2% vs. 40.4%. Median plasmacytosis in the bone marrow prior to CAR-T in the SCB group was 35% and 47.5% in the nSCB group. In the SCB cohort, 2 patients harbored DNMT3A mutations, one of whom had CCUS. Ide-cel was administered in 64.8% and cilta-cel in 35.2% of all patients. The rates and grades of cytokine release syndrome did not differ between groups. Six patients (15.4%) had HLH in the SCB group vs. none in the control group. All (100%) SCB patients received growth factor support; 58% also received TPO agonists. In the nSCB group, 43 patients (82.7%) received growth factor, and 16 patients (30.8%) received TPO agonists. Out of 24 pre-SCB bone marrow biopsies available, only 1 patient had relapsed MM while the remainder had hypocellular marrows. Median CD34+ cell dose was 2.93 million/kg (range: 1.76-23.55) administered at a median of 53 days post-CAR-T (range 24-265). All but one patient (97.4%) in the SCB group achieved hematologic recovery; median time to recovery was 24 days (range 9-87). No new toxicities attributable to SCB were observed. On day 90 post CAR-T infusion, SCB patients had higher median ANC (2.12 vs. 1.59x109/L, p=0.277), Hgb (10.6 vs. 8.7g/dL, p=0.002), and platelet counts (135 vs. 35K/L (p<0.001). Minimal residual disease negativity was achieved in 82.4% (SCB) vs. 83.3% (nSCB). Infections occured in 53.8% and 48.1% of SCB and nSCB cohorts. All serious infections occurred prior to SCB. There were 12 deaths in the SCB group (7 from disease progression, 2 from infection, 1 from neurotoxicity (NT), and 1 unknown) and 27 in the nSCB group (22 from progression, 3 from infection, 1 from HLH, 1 from NT). After a median follow-up period of 12.6 months in the SCB cohort and 11.6 months in the nSCB arm, the mPFS was 11.0 months and 8.2 months, respectively. The mPFS was 10.6 months (SCB) and 5.8 months (nSCB) (p=0.216), and 11.0 months (SCB) and 10.9 months (nSCB), for ide-cel and cilta-cel treated-patients, respectively. Median OS was not reached vs.12.3 months in the SCB vs. nSCB groups, respectively. Conclusion: Overall, SCB was safe and effective in promoting rapid hematologic recovery in nearly all patients. Compared to controls, SCB recipeints had significantly higher Hgb and platelet levels by day 90 post-CAR-T infusion. SCB was associated wih a near doubling of PFS in patients who received ide-cel, though interpretation is limited by non-randomized design and small sample size. Further study is needed to optimize paient selection, timing, and integration of SCB into CAR-T care.

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 Marginal zone lymphoma (MZL) is an indolent and heterogenous disease. Several prognostic models have been proposed to assess outcomes in MZL, including FLIPI, IPI (primarily designed for overall survival [OS]), and MZL-specific scores such as MALT-IPI (event-free survival [EFS]) and MZL-IPI (progression-free survival). FLIPI24 is a recently developed prognostic index for patients with follicular lymphoma (FL) treated with first-line (1L) immunochemotherapy (IC), identifying a high-risk population with inferior survival and increased risk of lymphoma-related death. FLIPI24 has also demonstrated robust performance in the entire FL population, including patients under observation. This study aimed to evaluate the prognostic utility of FLIPI24 in patients with MZL and to compare its performance with other established indices (FLIPI, MZL-IPI, IPI, MALT-IPI). Methods We pooled harmonized data from newly diagnosed MZL patients with complete available FLIPI24 variables (age, white blood cell count [WBC], hemoglobin [HGB], serum lactate dehydrogenase [LDH], and beta-2-microglobulin [B2M] levels) treated with 1L IC. Data were collected from three prospective international cohorts: NiHiL (Czech Republic; n=897; enrolled 2005–2023), LEO (USA; n=62; 2015–2020), and MER (USA; n=32; 2010–2015), forming a pooled cohort of 991 1L IC-treated patients. The analysis was then extended to include all newly diagnosed MZL patients (n=2,116), regardless of treatment. The primary endpoint in the 1L IC-treated cohort was EFS at 24 months (EFS24), and for all MZL patients, it was OS. Secondary endpoints included OS24 for 1L IC treated cohort, lymphoma-related mortality by FLIPI24 risk groups, and comparative prognostic performance of FLIPI, IPI, and MALT-IPI, by C-statistics; performance of MZL-IPI was assessed on a subgroup of NiHiL patients with available data (n=877 all MZL, n=485 1L IC-treated). Results Among the 991 1L IC-treated patients, the median age at diagnosis was 66 years (range 22–94); 47% were male; 11% had ECOG performance status ≥2, 68% clinical stage III–IV, 42% elevated LDH, 40% IPI 3–5, 42% FLIPI 3–5, and 62% MALT-IPI 2–3. The median B2M level was 2.8 mg/L, WBC 7.0 × 10⁹/L, and HGB 13.1 g/dL. MZL subtypes were: 64% extranodal (EMZL), 22% nodal (NMZL), and 14% splenic (SMZL). Most common 1L IC regimens were R-CVP (46%), R-CHOP-like (32%), R-chlorambucil (9%), and B-R (9%). FLIPI24 stratified patients into low- (18%), intermediate- (37%), and high-risk (45%) groups. High-risk patients were older (median 54 vs 65 vs 71 years for low-, intermediate-, and high-risk groups, respectively; P<0.01), had more frequent adverse baseline features, and were more likely to have the SMZL subtype (2% vs 7% vs 25% for low-, intermediate-, and high-risk groups, respectively; P<0.01). After a median follow-up of 7.2 years, EFS24 was 89%, 85%, and 65% (P<0.01) across low-, intermediate-, and high-risk groups; OS at 2 years was 98%, 97%, and 79%; and OS at 5 years was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 13% in high-risk vs 6% in low-/intermediate-risk groups. FLIPI24 showed better prognostic accuracy for EFS compared with FLIPI, MZL-IPI, IPI and MALT-IPI (C-index: 0.640 vs 0.630, 0.622, 0.620 and 0.603, resp.), as well as for OS (C-index: 0.710 vs 0.672, 0.641, 0.663, 0.652, resp.). Prognostic performance was consistent across MZL subtypes. In the extended cohort of 2,116 newly diagnosed MZL patients (47% receiving IC, 17% rituximab monotherapy, 11% radiotherapy, 8% surgery, 2% antibiotics; 15% observed), FLIPI24 stratified patients into low- (24%), intermediate- (39%), and high-risk (37%) groups. OS at 2 year was 99%, 97%, and 83%, at 5 years it was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 12% in high-risk vs 4% in low-/intermediate-risk patients. FLIPI24 outperformed other indices (OS C-index: 0.754 vs MZL-IPI 0.654, FLIPI 0.700, MALT-IPI 0.694, IPI 0.699). Conclusion FLIPI24 demonstrates strong and consistent prognostic performance across all MZL subtypes, identifying ~40% of patients as high-risk with significantly worse survival and increased lymphoma-related mortality. The FLIPI24 outperforms FLIPI, MZL-IPI, IPI, and MALT-IPI in predicting outcomes and may serve as a practical tool to guide risk-adapted management and selection of patients for novel therapies in MZL. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.