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Background: Contemporary questions about treatment and outcomes of patients (pts) living with multiple myeloma (MM) demand efficient and timely evidence generation methods, where real-world/ everyday practice data can play an important role. Relevant potential applications include understanding and addressing disparities in treatment access, mitigating toxicities of novel therapies while maintaining quality of life, appropriately sequencing treatments within long-term management strategies, and disseminating and appropriately using surrogate endpoints in practice, such as minimal residual disease. However, existing real-world data (RWD) repositories are limited by an inability to implement interventions in response to issues identified through retrospective data analysis, which is pivotal for the use of newer therapies. The ASH Research Collaborative (ASH RC) MM Data Hub Program was developed to address these gaps. Methods: We developed a multicenter network of US-based tertiary academic medical centers, engaging site clinicians, patients, biostatisticians, informaticians, and data scientists. Initial activities included constructing a shared real-world MM data model comprised of consensus core data elements. Pt data from each site, dating back to at least 2019, is currently being entered through electronic case report forms, batch uploaded utilizing existing institutional data repositories, and soon direct electronic health record import in standard data acquisition formats. Data are aggregated in the Data Hub and shared in a confidential Site Portal with each site. The Portal allows sites to track their own pts, analyze outcomes, and identify ways to improve the quality of care provided to individuals living with MM. We also developed an innovative evidence generation learning community of site clinicians who meet monthly and collaborate on the “COVID-19 OutcomeS in Myeloma and the Impact of VaCcines (COSMIC)” study, a prospective, decentralized observational study that rapidly accrued pts and collects relevant practice information. The group also shares best practices in study conduct to accelerate study enrollment and execution. Results: The MM Data Hub Program now contains twelve centers: Memorial Sloan Kettering Cancer Center, Mayo Clinic, Icahn School of Medicine at Mount Sinai, University of California San Francisco, University of California Davis, Medical College of Wisconsin, Barbara Ann Karmanos Cancer Institute, University of North Carolina Medical Center at Chapel Hill, Emory University Hospital, Washington University School of Medicine in St. Louis, Dana-Farber Cancer Institute, and Atrium Health. From this Network, six centers have contributed data from 8,824 pts (2,825 with sufficiently complete data are included in this analysis). The median age at time of MM diagnosis is 63, and of the 627 deceased pts, the median age at death is 70.6 years, with median time to death from first MM diagnosis of 6 years. The proportions of pts by decade of diagnoses are 34.9% from 2020-2024; 57.6% from 2010-2019; 7.3% from 2000-2009; and 0.9% prior to 2000. 83.1% of pts had a diagnosis of plasma cell myeloma (non-light chain), and 14.4% of pts had a diagnosis of light chain myeloma. 42.3% of pts are female, and the self-reported patient races are: 85.0% white; 9.2% black or African; and 4.3% all other races (race was not documented in 1.5% of pts). 2.8% of pts are of Hispanic ethnicity. Participant data files are currently undergoing completion and cleaning procedures; the analysis will include updated results at the meeting, and a Network-wide analytic data set will be available for initial retrospective data analyses in early 2025. The COSMIC study opened for enrollment on January 22, 2024, and completed enrollment of 200 pts on May 17, 2024. Conclusions: The ASH RC Data Hub MM Program launched in 2023 and is comprised of 12 sites that collectively have contributed participant files for 8,824 pts thus far. Utilizing the structure of the Network, we successfully implemented and established the feasibility of collecting data directly from pts electronically to monitor SARS-CoV-2 vaccines and COVID-19 related outcomes. The Program serves as a successful proof-of-concept model, providing an enduring RWD resource and a prospective evidence generation platform for the myeloma community.

Background: Rituximab, gemcitabine, and oxaliplatin (R-GemOx) is a commonly utilized chemoimmunotherapy regimen for relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL), especially for patients ineligible for autologous stem cell transplant (ASCT) or chimeric antigen receptor T cell therapy (CAR T). R-GemOx is used as a comparator arm in several active phase III clinical trials for R/R DLBCL, including the POLARGO (polatuzumab vedotion and R-GemOx), STARGLO (glofitamab and GemOx), SUNMO (mosunetuzumab and polatuzumab vedotin), LOTIS-5 (loncastuximab tesirine and rituximab), and EPCORE DLBCL-1 (epcoritamab) studies. However, real-world data are limited to understand the patterns of use and outcomes of R-GemOx in the US. Methods: We developed a retrospective multicenter US cohort (known as LEO CReWE) of patients with R/R DLBCL and other aggressive B-cell lymphomas at the eight US academic centers participating in the LEO Cohort Study (NCT02736357). Patients first diagnosed with DLBCL (including transformed and high-grade B-cell lymphoma) from 2007 - 2022 who received second line (2L) or later therapy for R/R DLBCL with R-GemOx were included. Baseline characteristics, treatment, and follow-up data were abstracted by chart review. Index line of therapy was defined as the first receipt of R-GemOx therapy in the 2L or later setting. Intent for CAR T and/or ASCT was evaluated at each line of therapy based on medical records at the time of treatment initiation. Subgroup analyses were pre-planned in groups of special interest, including those treated with R-GemOx without intent for ASCT or CAR T, those treated as a bridge to CAR T, and those aged 70 and older. Results: 183 patients with R/R DLBCL treated with R-GemOx were included. At time of initiation of R-GemOx, median age was 68 years (range 21-88), with 71 patients (39%) aged 70+ and 18 (10%) aged 80+. Many patients had high risk features including 13% with high grade B-cell lymphoma and 56% with IPI 3 or greater. 21% had an ECOG performance status of 2 or greater. Patients received a median of 2 lines of therapy prior to the index line of R-GemOx (range 1-7). 52% of patients did not achieve a complete response (CR) to first-line therapy, and 20% relapsed <12 months from an initial CR. In all patients receiving R-GemOx, the overall response rate (ORR) was 45% (29% CR). At a median follow-up of 39 months, median EFS was 2.3 months (95% CI: 1.8-3.2), with 12-month EFS of 21% and a 24-month EFS of 15%. Median OS was 13.5 months (95% CI: 9.6-18.1), with a 12-month OS of 52% and a 24-month OS of 38%. In patients treated without intent for ASCT or CAR T, ORR was 33% (18% CR). Median EFS was 2.0 months (95% CI: 1.6-2.5) with 12- and 24-month EFS of 14% and 9%, respectively. Median OS was 9.5 months (95% CI: 6.6-16.1) with 12- and 24-month OS of 45% and 29%, respectively. In patients receiving R-GemOx as bridging to ASCT or CAR T, ORR was 57% (35% CR). 35% received CAR T and 14% received ASCT, while the remainder did not receive the intended therapy as part of this line. Median EFS was 3.6 months (95% CI: 1.8-5.2) with 12- and 24-month EFS of 28% and 25%, respectively. Median OS was 17.4 months (95% CI: 13.4-NR); 12- and 24-month OS were 61% and 50%, respectively. In patients aged 70+, ORR was 53% (33% CR). Median EFS was 2.3 months (95% CI: 1.6-5.2), with 12- and 24-month EFS of 20% and 18%, respectively. Median OS was 13.9 months (95% CI: 8.6-30.2); 12- and 24-month OS were 57% and 39%, respectively. Conclusion: This study represents the largest reported cohort of patients treated with R-GemOx in US academic centers to date. The ORR of 45% and CR rate of 29% CR, as well as median EFS and OS of 2.3 and 13.5 months, respectively, are consistent with findings from previous phase II studies; these results highlight that responses to R-GemOx are not durable and the vast majority of patients require additional therapy. This study demonstrates real-world evidence of the efficacy of R-GemOx in a large cohort of patients with R/R DLBCL from the US over a long period, including both transplant-eligible and -ineligible patients, and patients treated in the CAR T era. These data aid in providing a benchmark for active clinical trials in the rapidly evolving landscape of R/R DLBCL therapies and allow potential comparison to a real-world cohort of patients with a broad range of clinical characteristics.

Background: TP53-mutated (TP53mut) myeloid neoplasms (MN) have particularly poor survival. Discrepancies in defining TP53mut MN have impact on diagnostic work up, therapeutic decisions, and clinical trial enrolment. Methods: MN cases harboring TP53mut (variant allele frequency, VAF ≥2%) were classified based on bone marrow (BM) and peripheral blood (PB) blast % using the 4th revision of the WHO classification (WHO-4R). Biallelic loss was defined as (i) ≥2 mutations each with VAF ≥2%; (ii) single TP53mut VAF ≥2% plus 17p loss detected on karyotype, FISH, or SNP; or (iii) single TP53mut VAF ≥50%, whereas monoallelic loss was defined as single TP53mut VAF <50% without 17p loss. Primary endpoint was overall survival (OS) from diagnosis. Conditional Inference Trees (CIT) analysis was used to determine the true effect of a predictor. Results: We identified 580 cases including WHO-4R defined acute myeloid leukemia (AML, BM/PB blasts ≥20%, n=219, 37.8%), myelodysplastic syndrome (MDS) with excess blasts-2 (EB-2, BM 10-19% or PB 5%-19%, n=92, 15.9%), MDS with excess blasts-1 (EB-1, BM 5-9% or PB 2-4%, n=75, 12.9%), and the remaining were MDS with low blasts (-LB, BM <5% and PB ≤1%, n=194, 33.4%). Of the 578 cases evaluable for allelic status, 437 (75.6%) and 141 (24.4%) had biallelic and monoallelic TP53 loss, respectively. Higher frequency of biallelic loss was observed with increasing blasts. 63.2%, 73.3%, 78% and 86.3% of cases with MDS-LB, MDS-EB1, MDS-EB2, and AML had bi-allelic TP53 loss (P<0.0001). In a multivariable analysis, WHO-4R categories, VAF ≥10%, and biallelic loss were independent predictors of poor survival. CIT analysis further stratified the cohort into 4 groups with distinct survival: (1) MDS-LB (n=194, 33.4%); (2) MDS-EB1/EB2 and AML with VAF <10% (n=38, 6.6%); (3) MDS-EB1/EB2 with VAF ≥10% (n=149, 25.7%); and (4) AML with VAF ≥10% (n=199, 34.3%). MDS-LB cases could be further stratified based on allelic status and complex karyotype (CK): OS was poor for cases with biallelic TP53 loss and monoallelic TP53mut with CK compared to monoallelic TP53mut without CK, who had the most favorable survival (12.7 vs. 13 vs. 34.8 months, P<0.0001).MDS-EB1/EB2/AML with VAF<10% could also be stratified by CK: MDS-EB1/EB2/AML with VAF<10% cases without CK had the favorable survival compared to their counterparts with CK and MDS-EB1/EB2 with VAF ≥10% cases (26.2 vs. 5.6 vs. 6.3 months, P=0.003).MDS-EB1/EB2 with VAF ≥10% was a homogenous subgroup: Biological characteristics including the proportion of cases with biallelic TP53 loss, CK (P>0.9), monosomal karyotype (MK, P>0.9), del 5q (P=0.6), del 7q (P=0.4), and del 17p (P=0.2) were comparable between MDS-EB1 and -EB2 with VAF ≥10%. Importantly, median OS of MDS-EB1 and EB2 with VAF ≥10% was comparable (9.6 vs. 7.2 months, P=0.12). OS in this group was comparable regardless of the blast %, allelic status, or presence of CK.AML with VAF ≥10% had extremely poor survival: Median OS was 3.9 months. Survival of AML was equally poor irrespective of the mono- or biallelic (3.6 vs. 3.9, P=0.89) and non-CK vs. CK (1.8 vs. 3.9 months, P=0.09). Combined, our model would acknowledge poor survival of 514 (89.1%) cases. In contrast, retrospective application of the 5th edition of the WHO classification (WHO-5) and International Consensus Classification (ICC) would classify only 211 (36.4%) and 468 (80.7%) cases as biallelic/multi-hit TP53mut MN, respectively. Finally, the Harrell's c-index of the proposed model, WHO-5, and ICC was 0.66, 0.571, and 0.617, respectively. Conclusion: We provide evidence for subsequent refinements in classifying MN harboring TP53mut. Our salient findings include: (i) acknowledgement of CK as ‘biallelic equivalent’ in MDS-LB; as well as EB1/EB2/AML with VAF 2 to <10% cases; and (ii) demonstration of poor survival of MDS-EB1 and -EB2 with VAF ≥10% regardless of the allelic status. In conclusion, our proposed model acknowledged poor survival of a higher proportion of cases as TP53mut MN compared to the current models with a higher c- index.

Introduction: Patients with non-Hodgkin Lymphoma (NHL), especially adolescents and young adults, can face late effects from treatment, including decreased fertility. Due to time constraints prior to treatment initiation and sometimes financial limitations, implementing fertility counseling and referral-based guideline care remains challenging. We aim to understand the occurrence and predictors of fertility counseling and preservation in patients with NHL in the Lymphoma Epidemiology of Outcomes (LEO) cohort study. Methods: The LEO cohort prospectively enrolled newly diagnosed patients with NHL from 2015-2020 at 8 academic medical centers in the US. Clinical. Treatment data were abstracted from medical records, pathology was reviewed and classified by a LEO pathologist, and participants completed a self-administered questionnaire. Participants were then prospectively followed to identify outcomes and collect additional patient reported data, including a survivorship questionnaire at follow-up 3 years (FU3) after diagnosis that included items on fertility counseling and preservation. The questionnaire contained two fertility questions analyzed: whether healthcare providers discussed the impact of lymphoma treatment on fertility, and whether providers discussed the process of fertility preservation. This analysis was based on participants aged 18-50 years at enrollment and who completed the fertility questions at FU3. Women who had undergone natural or procedural menopause and men who had undergone vasectomy pre-treatment were excluded. We estimated the association of demographic and clinical factors with fertility preservation using odds ratios (ORs) and 95% confidence intervals (CI) from univariate and multivariable logistic regression models. Results: Seventy-seven patients were included in the analysis: 36 females (46%) and 41 males (53%). The median age of diagnosis was 40 years (IQR 30-45), and 36 (47%) participants were in the age 18-39-year category. Participant self-identified race/ethnicity was 69% non-Hispanic White, 22% Hispanic, 4% Black and 3% Asian. Sixty (78%) patients were treated with alkylators, 12 (15.6%) with non-alkylators, and 5 (6.5%) with radiation. Fifty-five (71%) of the patients were classified as having aggressive lymphoma, with follicular, extranodal marginal zone, primary cutaneous follicle center, and nodal marginal zone B-cell lymphoma defined as indolent and remaining subtypes aggressive. Around 6% of female patients underwent fertility preservation after lymphoma diagnosis, compared to 12.2% of male patients. All the patients who had undergone fertility preservation after lymphoma diagnosis were in the 18-39-year age group. On univariate analysis, females were more likely to have undergone fertility toxicity and preservation discussions compared to males, with 72% of females and 59% of males recalling a discussion regarding fertility (OR 1.8, 95% CI 0.7-4.9, p=0.21). Those age 18-39 were significantly more likely to have undergone fertility discussion compared to those aged 40-50 (OR 10.2, 95% CI 3.3-39.2, p<0.001). Patients treated with alkylating therapy were significantly more likely to undergo fertility discussion when compared to those on non-alkylating therapy (OR 9.0, 95% CI 2.3-45.5, p<0.01). In addition, 75% of those with aggressive lymphoma compared to 41% of patients with indolent lymphoma had fertility discussion (OR 4.2, 95% CI 1.5-12.4, p=0.01). White patients were significantly less likely than Hispanic, Black and Asian patients to have fertility discussion (OR 0.2, 95% CI 0.04-0.6, p<0.01). In the multivariable analysis, alkylating therapy (OR 8.9, 95% CI 1.6-66.7) and age 18-39 years (OR 10.9, 95% CI 2.9-55.3) remained significant predictors of fertility discussion; White race was also trending towards significance (OR 0.2, 95% CI 0.04-1.0, p=0.08). Aggressive lymphoma subtype was not a significant predictor of fertility discussion. Conclusions: In this cohort of lymphoma survivors 3 years post-diagnosis, we found that Hispanic patients, those diagnosed at a younger age and exposed to alkylating chemotherapy agents were significantly more likely to undergo discussions regarding the effects of lymphoma treatment on fertility. Our study highlights the importance of all cancer patients of childbearing age having the opportunity to address fertility concerns during clinic visits.

Introduction: Oncologists increasingly recognize the need to evaluate the impact of cancer therapies on patients' time, known as “treatment-related time toxicity”, which is measured as the number of days of contact with the healthcare system (Gupta A et al. J Clin Oncol 2022). Current standard-of-care options for patients with TCE RRMM require frequent clinic visits for treatment administration. Reducing treatment-related time toxicity of treatment without compromising efficacy or safety may have an impact on patients' quality of life and influence treatment choice. BCMA-directed bispecific antibodies (BCMA bsAbs) provide a novel treatment option for TCE RRMM, with response-adapted dosing frequency allowing for extended dosing intervals for patients. The frequency of extended dosing intervals varies between BCMA bsAbs according to their prescribing information or pivotal trial protocol. The aim of this analysis was to evaluate the impact of BCMA bsAbs' extended dosing intervals on treatment-related contact (TRC) days corresponding to treatment administration as a component of time toxicity. Methods: An Excel-based longitudinal model was developed to quantify the number of TRC days experienced by patients with TCE RRMM within the healthcare system when receiving treatment with BCMA bsAbs (linvoseltamab, teclistamab, or elranatamab) over 1-2 years. TRC days included all planned treatment administration days. Model inputs were sourced from product labels or pivotal trial protocols for bsAbs, as well as the published literature. To allow for a comparison of total dosing regimens, it was assumed that patients continued receiving treatment throughout the study period with no discontinuation. Dosing intervals for each product during the first 6 months were once weekly (QW), except for linvoseltamab (QW for Weeks 1-14, then once every 2 weeks [Q2W] from Weeks 16-24, per Phase 2 trial protocol). The extended dosing interval for linvoseltamab was Q4W for patients reaching very good partial response or better at or after 24 weeks, and Q2W for both teclistamab patients who maintained a complete response (CR) or better for ≥6 months and for elranatamab patients who reached partial response or better at or after 6 months. Two switching scenarios were considered for teclistamab: an earliest possible switch (at Week 26), and a time-varying switch based on digitized time to CR data from MajesTEC-1 (Usmani SZ et al. ASCO 2023). Results were calculated to evaluate the difference in TRC days between the scenarios with and without extended dosing intervals for each treatment. Results: In the first year of treatment, the total number of TRC days with and without extended dosing intervals was lowest with linvoseltamab. TRC days with linvoseltamab were reduced from 33 to 26 days with extended dosing intervals. Next lowest was elranatamab (53 to 39 days), followed by teclistamab (54 to 41 days for earliest possible switch and 54 to 50 days with time-varying switching). Over 2 years, linvoseltamab had the lowest number of TRC days (59 to 39 days), followed by elranatamab (105 to 65 days) and teclistamab (106 to 67 days for earliest possible switch and 106 to 80 days with time-varying switching). Conclusions: Extended dosing intervals with BCMA bsAbs can substantially reduce time toxicity for patients with RRMM. Linvoseltamab had the lowest number of TRC days among BCMA bsAbs.

Background Emerging evidence has demonstrated rare subacute to late neurological toxicities (NTs) after BCMA CAR T-cell therapy (CAR-T) in multiple myeloma (MM). These adverse events can be categorized as: 1) Parkinsonism (PD), 2) cranial nerve (CN) palsies, and 3) peripheral neuropathies/Guillan Barré syndrome (GBS). These toxicities can cause significant morbidity, but given their relative rarity in clinical trials, there is limited data regarding evaluation and treatment. To our knowledge, this is the largest and only global registry of delayed NTs after BCMA CAR-T. Methods We retrospectively established a registry of NTs via the Immune Therapy Working Committee of the International Myeloma Working Group (IMWG). We gathered data pertaining to demographics, MM characteristics, MM response, NT signs/symptoms, diagnostic workup, and treatment. Result A total of 52 patients with delayed neurotoxicity were included from 14 institutions and 6 countries; 92% received ciltacel, 4% idecel, and 4% investigational CAR-T. Median age at CAR-T infusion was 65 years; 69% were male and 88% were Caucasian. Median bone marrow plasma cell (PC) burden was 15% prior to CAR-T (range 0-95%). Patients received a median of 4 prior lines of therapy (LOT), with 67% progressing on last LOT. Seventeen percent had pre-existing neurological diagnoses (including stroke, epilepsy, migraines). We identified sixteen cases of PD (94% with movement disorder, 69% with cognitive impairment, 75% with personality changes), occurring at a median of 26 days (range: 15-87) after CAR-T. Ninety four percent had CRS (grade (G)1 50%, G2 38%, G3 6%, G4 0%), while 19% had ICANS (G1 13%, G2 6%, G3-G4 0%). Median peak absolute lymphocyte count (ALC) was 9.5 x 109/L, peak C-reactive protein (CRP) 60.9 mg/L, and peak ferritin 1893.5 ug/L within the first 30 days. Concurrently, 3 upper respiratory infections (URIs) and 2 low-level HHV7 in the cerebrospinal fluid (CSF) were detected. A median of 73% of T-cells in the CSF were CAR-T, based on a flow cytometry assay. Ten patients received steroids (median 19 days after symptoms, 70% partial response, 20% no response, 10% unknown), 2 received intrathecal (IT) methotrexate-based therapy (median 32 days after symptoms, 1 with no response, 1 unknown), 5 received intravenous (IV) cyclophosphamide (median 31 days after symptoms, 40% full response, 20% partial response, 40% no response), 4 received high-dose IVIG ≥1g/kg for one or more dose (50% partial response, 50% no response), and 6 received dopamine agonists. There were 37 CN palsies (76% CN7, 15% CN6, 7% CN5, 2% CN3), occurring at a median of 37.5 days (range: 7-482) after CAR-T. Eighty one percent had CRS (G1 68%, G2 14%, G3-G4 0%); 11% had G1 ICANS (G2-G4 0%). Median peak ALC was 4.1 x 109/L, CRP 25.4 mg/L, and ferritin 543 ug/L within the first 30 days. We identified 2 concurrent URIs, 4 CMV viremia (50% with viral load >1500 IU/mL), 1 HHV6 viremia, and 1 HSV in the CSF. Thirty-two (86%) received steroids for a median duration of 12 days, 50% with full response, 3% with no response, and 47% with partial response (of which 43% had later full recovery without further intervention). One received IT methotrexate and another received IV cyclophosphamide without response. Thirteen (41%) received IVIG, of which 38% was high-dose IVIG. Four patients with CN palsies developed peripheral neuropathy/GBS. Eight patients (15%) in this cohort were not heavily pre-treated (≤1 prior LOT); 7 developed CN palsies (6 after ciltacel, 1 after investigational CAR-T) and 1 PD (after idecel). These patients had median <5% PC; none had extramedullary disease. Median ALC was 4.14 x 109/L, CRP 33 mg/L, and ferritin 448.5 ug/L within the first 30 days. Conclusions Delayed NT requires prompt recognition, evaluation for alternative causes, and treatment. In our cohort, the majority of patients were male and Caucasian, suggesting that sex and race may impact the likelihood of developing NT. Individuals with PDs had greater inflammatory response (CRS, ALC, CRP, ferritin) compared to those with CN palsies. CN palsies responded to steroids and/or IVIG, whereas PD had at best partial response to steroids, prompting additional therapy. These toxicities notably did occur in less heavily pre-treated patients, perhaps driven by immune fitness and greater circulating T-cells rather than MM burden. At the time of the annual meeting, data will be updated with additional NTs from less heavily pre-treated patients.

Aim: The definition of high-risk (HR) in Multiple Myeloma (MM) is ever evolving with the discovery of new genomic abnormalities and increasing therapeutic options. There are various stratification models incorporating laboratory and genetic features with different definitions of high-risk and varied emphasis on individual risk factors. Recognized high-risk cytogenetic abnormalities (HRCA) include t(4;14), t(14;16), t(14;20), del(17p) with recent inclusion of del(1p) and gain/amplification (amp) of 1q (+1q) . In addition to del(17p), the presence of biallelic del(1p) and ≥2 HRCAs (“double-” or “triple-hit”) appear to confer poorer outcomes. A new definition proposed by the International Myeloma society (IMS) defines HR as the presence of del(17p) and/or TP53 mutation; an IgH translocation - t(4;14), t(4;16) or t(14;20) along with +1q and/or del(1p); monoallelic del(1p32) along with +1q; bi-allelic del(1p32); or β2 microglobulin ≥5.5 with normal creatinine (<1.2mg/dL). Herein, we report real-world outcomes on these HRCAs and the new IMS consensus definition of HR MM. Method: We retrospectively reviewed newly diagnosed MM patients from the Australian and New Zealand Myeloma and Related Diseases Registry across 4 Australian states. Patients with FISH and/or SNP microarray testing for IgH translocations, 1q21 (CKS1B), del(1p32) (CDKN2C) and del(17p) (TP53) were identified. Positive threshold was 30%. We used Kaplan-Meier methods to compare progression free survival (PFS) and overall survival (OS) between groups and first performed univariate analysis (UA) for each HRCA. We next analyzed patients with gain1q vs amp1q and monoallelic vs biallelic del(1p). In the final analysis, two risk groups were formed: cases meeting the new IMS-defined HR criteria were considered IMS-HR and the rest were considered standard risk (IMS-SR). Indeterminate cases with missing variables that could influence risk classification were excluded. Results: Of 839 newly diagnosed patients (pts) included, 31% had ISS (International staging system) stage 3 disease. High-risk IgH translocations t(4;14) and t(14;16) were present in 8% and 4%. Secondary HRCAs del(17p), del(1p), gain1q and amp1q were present in 9%, 14%, 30% and 11% respectively. In this cohort, 41% received ASCT. Of the transplant eligible pts, 41% received triplet therapy (PI, IMiD and corticosteroid) and 57% received PI-based induction. Of the transplant ineligible pts, 31% received triplet therapy, 47% PI-based and 19% IMiD-based therapy. Frontline Anti-CD38 antibody use was <1%. Median follow up was 35 months[m] (IQR 18-60). On UA, the risk of progression and/or death was increased with ISS III vs I, amp1q, del(17p), t(14;16), del(1p) and gain1q in descending order by hazard ratio. The risk remained significant in ISS III, del(17p), amp1q and gain1q after multi-variate analysis (MVA). The risk of death was increased with ISS III vs I, del(17p), amp1q, del(1p) and t(14;16), ISS II vs I in descending order by hazard ratio. After MVA, the risk remained significant for ISS stage III, del(17p), amp1q and t(14;16). Of the 117 pts with del(1p32), 108 had monoallelic and 9 had biallelic loss. Pts with biallelic del(1p32) had an inferior PFS (median 16.3 vs 23.2m, p<0.001) and OS (median 24.8m vs NR, p<0.001) compared to those with monoallelic del(1p32). In pts with 1q+, pts with amp1q had an inferior PFS (median 16.3 vs 27.5m, p<0.001) and OS (median 37.0m vs NR, p<0.001) vs pts with gain1q. Based on the new definition of HR myeloma - 385 pts met the criteria for IMS-HR and 216 for IMS-SR. There were 238 indeterminate cases due to missing data. The IMS-HR group had an inferior PFS (median 20.2 vs 39.7m, p<0.001) and OS (median 44.2m vs NR, p<0.001) when compared to IMS-SR. Noting that the IMS-HR group had a higher median age, poorer performance status and lower rates of ASCT use, adjusted analysis for these variables still showed an inferior PFS (aHR 1.68; 95% CI 1.30-2.16, p<0.001) and OS [aHR 1.72; 95% CI 1.21-2.44, p=0.002). Conclusion: ISS III, del(17p), amp1q are the strongest predictor of OS and PFS. Differentiating between monoallelic vs biallelic del(132p) and gain vs amp1q21 has important prognostic value. The IMS- HR definition which takes into account del(1p), “double-” and “triple-hit” disease predicts for a group of patients with a PFS of ~20 months and inferior OS, and provides a standardized approach to risk stratification in MM.

Background: Financial toxicity (FT), or the negative impact of medical expenses experienced by patients, is a known adverse effect of cancer treatment that result in worse health outcomes for patients. However, there is limited literature investigating FT in lymphoma with even less data on predictors such as age, gender, and socioeconomic factors. As lymphoma treatment options expand, it is vital to understand the impact of these treatments on patients' financial well-being. We investigate FT through patient reported outcomes from the Lymphoma Epidemiology of Outcomes (LEO), a large multi-institution prospective cohort study of non-Hodgkin lymphoma (NHL). Methods: Patients with newly diagnosed NHL were enrolled into the LEO cohort from 2015-2020. Clinical, pathology and treatment data were abstracted from medical records, and participants were offered self-administered surveys at enrollment and selected follow-up time points. Participants were included if they completed at least four of six survey questions on FT adapted from the Medical Expenditure Panel Survey (MEPS) within the first year after diagnosis. Questions focused on either material hardship (unable to cover costs; file for bankruptcy; borrow money; work extra job or hours) or psychological stress (worried about paying large medical bills). We evaluated FT as answering positively to any question (any vs none). Associations with FT were evaluated using chi-squared tests. All analyses were performed using R (v4.2.2). Results: 3202 patients completed at least four survey questions relating to FT. Mean age at diagnosis was 62 years (18-94), 56% were male, and majority identified as white (90%). Characteristics associated with FT are reported (p<0.001). FT was more likely in younger patients: 18-25 years (64%, 30/47), 26-44 years (73%, 299/313), and 45-64 years (58%, 799/1375) as compared to those 65-79 years (36%, 459/1272) and ≥80 years (35%, 69/195). FT was highest in patients without a high school diploma (54%, 45/84), followed by patients with a high school diploma (52%, 209/402), and an associate's degree (57%, 358/627). It was lowest in patients with a bachelor's (45%, 224/296) or post-graduate degree (39.6%, 216/545). Higher FT was seen in those receiving disability income (65%, 47/72); whereas less FT was seen in retired patients (36%, 299/828). FT rates inversely correlated with income: 65% for income < $21,000 (184/283), 61% for $21,000- $39,999 (224/370) and 60% for $40,000-$65,999 (293/491). Lower FT noted for income range of $66,000-$106,000 (47%, 323/681) or > $106,000 (37%, 324/872). Patients separated from a partner (82.9%, 19/23) had the highest FT, followed by patients living with a partner (64%, 48/75), divorced (56%, 103/184), and never married (53.4%, 79/148). Patients who were married (47%, 793/1672) or widowed (41%, 60/146) reported the lowest FT. Higher FT was reported in DLBCL (55%, 631/1146), MCL (55%, 172/315), and TCL (53%, 119/226) when compared to FL (44%, 327/746), MZL (44%, 137/316), and other NHL (44%, 200/453). This is likely related to treatment as more FT was seen in patients who received an anthracycline and/or alkylator containing therapy (54%, 1066/1963) versus non-systemic (43%, 120/278) and observation (35%, 168/483). In multivariable analyses, FT strongly correlated with age at diagnosis, household income, and treatment type. The odds ratio and 95% confidence intervals for the most significant category within each variable are as follows: age per 1 year (0.96, [0.95-0.97]), income > $106,000 vs < $21,000 (0.28, [0.21-0.38]), and observation vs anthracycline and/or alkylator (0.56, [0.44-0.71]). Conclusion: Nearly 50% of patients with lymphoma experience FT, seen as material hardship and psychological stress, within the first year of diagnosis. Patients with a younger age (18-44), less education, and lower household income reported higher levels of FT; whereas those who were retired or married/widowed reported lower FT. Lymphoma subtypes that require more anthracycline and/or alkylator containing therapy imposed higher FT. Understanding these risk factors can help clinicians identify patients who may benefit from additional resources during lymphoma management.

Background: Indolent non-Hodgkin lymphomas (iNHL) are incurable and disproportionately affect adults age >65 in whom frailty and functional impairment can impact disease management. The Vulnerable Elders Survey (VES-13) is a 13-item screening tool that incorporates age, self-rated health, physical function limitations, and functional disabilities to identify vulnerable older community-dwelling adults. Adults with a VES-13 score of >3 have a fourfold increased risk of death or functional decline over 2 years as compared to adults with a score <3 (Saliba et al, JAGS 2001). Our team previously showed that VES-13 >3 was associated with a higher risk of 1-year mortality in NHL (OR 3.26, 95% CI 2.15-4.96, Fama et al, ASH 2019), including in adults age <65. In this study, we determined whether VES-13 scores >3 were associated with quality of life (QOL) changes in adults with iNHL across the age spectrum. Methods: We used the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study to identify adults enrolled from 2015-2020 with grade 1-3A follicular and marginal zone lymphoma (FL, MZL) who completed the VES-13 at enrollment and QOL surveys at enrollment and follow-up. The LEO Cohort Study enrolls participants within 6 months of diagnosis and collects information on disease status, QOL, health behaviors, and patient-reported functional assessment. For this analysis we included QOL measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1 and 2 post-enrollment. The FACT-G total score was the sum of 4 subscales (range): physical (PWB, 0-28), social/family (SFWB, 0-28), emotional (EWB, 0-24), and functional (FWB, 0-28) well-being. A higher FACT-G total score (range 0-108) indicated better overall QOL. VES-13 scores ranged from 0 (lowest risk for death or decline) to 10+ (highest risk). Generalized linear mixed models evaluated changes in QOL from baseline based on VES-13 score >3 (vulnerable) vs <3 (non-vulnerable), within groups by age at enrollment >65 and <65. Results: Our study included 1,186 participants: 42% age >65, 54% female, 84% non-Hispanic White, 10% Hispanic, 3.3% Black, and 1.4% Asian/Pacific Islander. Most (68%) were diagnosed with FL. FLIPI was high risk for 20%, and MALT-IPI was high risk for 23%. In the VES-13 <3 group, the mean (SD) baseline FACT-G total score was 86.5 (12.0), PWB 21.0 (3.5), SFWB 24.3 (4.3), EWB 18.8 (3.7), and FWB 22.3 (4.9). In the VES-13 >3 group, the mean (SD) baseline FACT-G total score was 70.4 (16.5), PWB 15.4 (5.6), SFWB 22.3 (5.5), EWB 17.5 (4.5), and FWB 15.3 (6.4); all significantly lower than the VES-13 >3 group (all p<0.01). In adults <65, 63 (9%) had a VES-13 >3, which was associated with a significant improvement from baseline in PWB at years 1 and 2 when compared to VES-13 <3 (changes in baseline PWB were 2.1, 2.9 for VES-13 >3 vs 0.2, 0.1 for VES-13 <3, all p<0.05). Similarly, we observed improvement in FWB from baseline at years 1 and 2 in the VES-13 >3 vs <3 group (2.4, 2.9 vs 0.4, -0.1, respectively all p<0.05). The VES-13 >3 group had a decline in their EWB at 1 year vs the VES <3 group (-0.5 vs 1.2, respectively, p=0.003). At year 2, total FACT-G improved from baseline in the VES-13 >3 group (5.6 for VES-13 >3 vs -0.5 for VES-13 <3, p=0.002). SFWB changes from baseline did not differ between groups. In adults >65, 83 (17%) had a VES-13 >3, which was associated with a significant improvement from baseline PWB (1.3, 1.5 for VES-13 >3 vs. 0.1, -0.1 for VES-13 <3), FWB (3.3, 2.2 for VES-13 >3 vs. 0.5, 0.1 for VES-13 <3), and total FACT-G score (5.2, 3.4 for VES-13 >3 vs. 1.0, -0.4 for VES-13 <3) when compared to VES-13 <3 at years 1 and 2 (all p<0.05). SFWB and EWB changes from baseline did not differ between groups. While there was improvement from baseline PWB and FWB in the VES-13 >3 group, QOL scores across all subscales remained below the VES-13 <3 group in the study period for both age groups. Statistical significance was maintained in models adjusted for baseline characteristics, including initial treatment strategy (observation, systemic, vs local) for both age groups. Conclusion: Although the vulnerable group reported worse QOL throughout the study period compared to the non-vulnerable group, survivors in the vulnerable group saw greater improvement in their physical and functional well-being at 1- and 2-years post-diagnosis. Additional analyses are underway to identify drivers of improvement in physical and functional well-being in vulnerable adults diagnosed with iNHL.

Background: Epcoritamab (epcor) is a first-in-class CD3xCD20 bispecific antibody (bsAb) approved for the treatment of 3L+ LBCL and follicular lymphoma. In the single-arm, phase 1/2, EPCORE NHL-1 trial (NCT03625037), epcor given until disease progression or unacceptable toxicity, demonstrated deep and durable responses, a median overall survival (OS) of 18.5 months, and a manageable safety profile in R/R LBCL. A second CD3xCD20 bsAb given as fixed-treatment duration, glofitamab (glofit), also demonstrated durable responses, conferring a median OS of 11.5 months in the pivotal study. Understanding how long-term outcomes compare among bsAb agents remains an important knowledge gap. With over 2 years of follow-up, in the absence of a head-to-head study, it is now relevant to compare the efficacy of these agents via indirect comparison. This study evaluated OS, progression-free survival (PFS), and duration of complete response (DoCR) of epcor vs glofit in R/R LBCL using data from the respective pivotal trials. Methods: Two analyses were conducted to compare the efficacy of epcor and glofit. First, a matching-adjusted indirect treatment comparison (MAIC) was conducted using published OS and PFS data from the full cohort of the glofit pivotal trial (12.6 months of follow-up, Dickinson et al, 2022) and the epcor pivotal trial (EPCORE NHL-1). Piece-wise hazard ratios (HRs) were calculated when proportional hazards assumptions were not met. Baseline characteristic prognostic variables were selected based on literature, clinical judgement, and empirical statistical testing and were adjusted between epcor and glofit cohorts. Second, in sensitivity analyses, indirect comparisons were conducted using an updated analysis of glofit with longer follow-up that included DoCR, together with OS and PFS data starting at cycle (C) 3 with 32 months of follow-up (Hutchings et al, ASH 2023). Sensitivity analyses with longer follow-up could not be adjusted because glofit pt baseline characteristics were not presented. Aggregate OS and PFS curves for glofit were derived from subgroups of pts with complete response/partial response/no response (CR/PR/NR) at C3 (Hutchings et al, ASH 2023). Aggregate epcor OS and PFS curves were similarly derived for pts with CR/PR/NR at C3 without prior disease progression. Weighted Cox proportional-hazards models were used to estimate the OS and PFS HRs between the 2 comparators. The DoCR comparison included all glofit and epcor pts achieving CR. All comparisons used EPCORE NHL-1 data with a median of 37.1 months of follow-up. Results: Pts enrolled into the pivotal trials of epcor and glofit were comparable by several key baseline characteristics before adjustment: age ≥65 y; male gender; Ann Arbor disease stage III-IV; primary refractory disease; refractory to most recent anti-CD20 therapy; previous chimeric antigen receptor T-cell therapy (CAR T); refractory to CAR T; and previous autologous stem cell transplant (ASCT). MAIC analysis revealed no significant difference in OS benefit from C1 until month 6 (HR 1.08, 95% CI 0.71, 1.64; P=0.72), but a demonstrable OS advantage from 6 months onward (HR 0.60, 95% CI 0.37, 0.98; P=0.04) in favor of epcor. An OS comparison starting at C3 with longer glofit follow-up demonstrated a consistent survival advantage in favor of epcor (HR 0.68, 95% CI 0.46, 1.01; P=0.05). The proportion of pts who received CAR T or ASCT subsequent therapy were similar for epcor and glofit (CAR T: 7.0% vs 8.9%; ASCT: 6.4% vs 6.3%) (National Institute for Health and Care Excellence Glofit Single Technology Appraisal, 2023). The MAIC analysis showed comparable PFS between epcor and glofit (HR 1.06, 95% CI 0.79, 1.41; P=0.71), although there was substantial censoring in the glofit PFS curve due to immature follow-up. With longer follow-up in the analysis starting at C3, with less censoring, the glofit PFS curve remained similar to the epcor PFS curve from C3 until month 6 (HR 0.67, 95% CI 0.42, 1.07; P=0.10), where separation of the PFS curves were observed favoring epcor (HR 0.56, 95% CI 0.33, 0.97; P=0.04). Median DoCR was longer for epcor (36.1 months) vs glofit (26.9 months). Conclusion: These indirect treatment comparisons suggest that epcor may provide an overall survival benefit over glofit through longer PFS with more mature follow-up, potentially driven by longer DoCR. Survival data with longer follow-up in the full glofit cohort are needed to confirm these findings.