Citations

Abstract Background Several bispecific antibodies (BsAbs), including mosunetuzumab, glofitamab, and epcoritamab, are approved for non-Hodgkin lymphoma (NHL). However, real-world patient-centered data evaluating treatment-related time burden and preferences are lacking. Methods We conducted an online survey of 120 patients with relapsed/refractory follicular lymphoma (FL; N = 60) and diffuse large B-cell lymphoma (DLBCL; N = 60) receiving BsAbs. Participants reported all-cause healthcare visits and time spent on cancer-related healthcare resource utilization over the past 30 days, including travel, treatment administration, recovery, and impact on daily activities. Participants also evaluated two hypothetical treatment profiles to assess preference for fixed-duration versus treat-to-progression therapy. Results Participants with FL reported a mean of 2.5 healthcare visits in the past 30 days, with significantly fewer visits for mosunetuzumab versus epcoritamab (1.7 vs 3.3, respectively; P < .01). In DLBCL, the mean was 2.6 visits, with fewer visits for glofitamab versus epcoritamab (2.2 vs 3.0; P =.01). Although epcoritamab visits were shorter in FL, more frequent visits and longer recovery time resulted in significantly lower monthly time burden with mosunetuzumab versus epcoritamab (31.2 vs 61.9 hours; P < .05). Similarly, monthly time burden was also lower with glofitamab than epcoritamab in DLBCL (43.0 vs 87.7 hours; P < .05). Most participants reported little to moderate impact on daily activities. Across treatment groups, ≥92% preferred a hypothetical fixed-duration regimen over a treat-to-progression therapy. Conclusion Our real-world data, including novel aspects of time toxicity, demonstrate clinically meaningful differences in time burden associated with BsAbs and emphasize the importance of incorporating patient convenience and preference into shared decision-making in NHL.

Abstract Background Several BsAbs with different treatment (Tx) approaches have been approved by the FDA for Tx of lymphoma, including: fixed-duration and less frequently dosed mosunetuzumab (mosun) and glofitamab (glofit) (Option 1 Tx approach); and treat to progression and more frequently dosed epcoritamab (epcor) (Option 2 Tx approach). Differences in Tx approaches have implications for time spent receiving care, known as “time toxicity”. We previously reported that mosun and glofit were associated with about 2 weeks lower time toxicity vs epcor over the first year in R/R FL and DLBCL, based on registrational trial protocols (Torka et al. Blood 2024; Ma et al. Value in Health 2025). In this study, we assessed time toxicity from the perspective of patients (pts) receiving BsAbs for R/R FL or DLBCL. Methods An online survey was conducted aiming for input from 120 pts with R/R FL or DLBCL, who have received BsAb for ≥1 month in the US. Time toxicity was measured by pts recalling time spent on healthcare contacts related to BsAb Tx, cancer management, and any other reasons in the past 30 days. Pts' preferences were assessed through direct elicitation of choice between 2 hypothetical Tx profiles with different Tx approaches and time toxicity, assuming the same efficacy and safety. The survey was pre-tested and refined based on input from 3 BsAb pts with R/R DLBCL to ensure relevance and comprehension. Descriptive analyses were performed on pts characteristics, mean and standard deviation (SD) of time spent per pt per month, and the proportion of pts preferring the convenience of different Tx profiles. Results At this interim analysis, 101 pts receiving BsAbs responded to the survey: 48 pts with R/R FL (mosun n=28; epcor n=20) and 53 pts with R/R DLBCL (glofit n=32; epcor n=21). Most pts with R/R FL lived in urban/suburban areas (87.5% vs 12.5% in rural areas) and had a shorter one-way travel time to receive care vs pts in rural areas (mean±SD: 28.2±13.5 vs 60.3±30.2 minutes). The median age was 58 years for both mosun and epcor. Mean±SD Tx duration was 6.2±1.8 months for mosun vs 4.5±1.3 months for epcor. In the past 30 days, pts on mosun had fewer BsAb Tx visits vs epcor (mean±SD: 1.0±0.2 vs 2.0±1.2), and fewer all-cause healthcare contacts vs epcor (mean±SD: 1.7±0.8 vs 3.5±2.0). The mean±SD time spent per BsAb Tx visit was 5.0±1.4 hours for mosun vs 3.8±1.8 hours for epcor. Less time was spent per pt per month on recovery at home after Tx visit for mosun vs epcor (22.7±16.5 vs 43.2±47.6 hours). Less time was spent per pt per month on Tx and cancer management for mosun vs epcor (mean±SD: 30.5±16.9 vs 56.9±59.3 hours). Most pts with R/R DLBCL lived in urban/suburban areas (88.7% vs 11.5% in rural areas) and had a shorter one-way travel time to receive care vs pts in rural areas (mean±SD: 31.4±14.1 vs 103.3±19.4 minutes). The median age was 67 years for glofit and 66 years for epcor. The mean±SD Tx duration was 6.1±2.0 months for glofit vs 5.9±1.8 months for epcor. In the last 30 days, pts on glofit had fewer BsAb Tx visits vs epcor (mean±SD: 1.1±0.2 vs 1.7±0.5), and fewer all-cause healthcare contacts vs epcor (mean±SD: 2.2±1.3 vs 3.0±1.1). Irrespective of the route of administration, the time spent per BsAb Tx visit was similar (mean±SD: 5.1±1.6 hours for mosun; 5.6±1.2 hours for epcor). Less time was spent per pt per month on recovery at home after Tx visit for glofit vs epcor (mean±SD: 34.3±23.8 vs 69.3±39.4 hours). Less time was spent per pt per month on Tx visits and cancer management for glofit vs epcor (mean±SD: 43.0±25.9 vs 85.0±44.2 hours). Regardless of which BsAb pts received, most pts (93%) preferred the convenience of Option 1 Tx approach with less time required over Option 2 Tx approach with more time required. Conclusions This is the first study to directly measure pt-reported time toxicity from pts with R/R FL and DLBCL receiving BsAbs in a real-world setting. Fixed-duration less frequently dosed mosun and glofit (Option 1 Tx approach) had less pt-reported time toxicity, with less healthcare contact and less time spent per pt per month vs treat to progression more frequently dosed epcor (Option 2 Tx approach). Over 90% of pts preferred the convenience of a fixed-duration, less frequently dosed, and less time required Tx option, suggesting that time toxicity is a significant factor in shared Tx decision-making for pts with R/R FL and DLBCL. Analysis is ongoing to comprehensively measure pt-reported time toxicity.

Introduction: MM is an incurable disease with risk categorizations by cytogenetic abnormalities. Prognostic implications of chromosome translocation t(11;14)+ are important to inform development of biomarker-targeted therapies such as the B-cell lymphoma-2 (BCL-2) pathway inhibitors. This study aims to evaluate MM treatment (Tx) patterns and outcomes of t(11;14)+ compared with other cytogenetic cohorts in US routine clinical practice. Methods: A retrospective observational cohort study of the Flatiron Health database, which comprises de-identified electronic health record-derived patient (pt)-level data from over 280 community and academic cancer clinics in the US. Pts aged ≥18 years who received a first-line (1L) induction Tx within ≤60 days of MM diagnosis from 1/1/2011 to 1/31/2020, and were not enrolled in a clinical trial were identified at the start of each Tx line (index date) and followed up (f/u) until 1/31/2020. Only cytogenetic results by fluorescence in situ hybridization (FISH) were used to stratify the cohort into: t(11;14)+; standard risk, excluding t(11;14)+ (SR); and high risk, (HR; del 17p, t(4;14), t(14;16), t(14;20), chromosome 1 abnormalities as a proxy for 1q gain; and t(11;14) where it co-occurs). Descriptive analyses of pt characteristics and Tx were conducted. Kaplan-Meier analyses were used to evaluate median time to next treatment (TTNT) and overall survival (OS) with log-rank test for significance. The cohort was stratified by age ≤70/>70 years (yrs) as a proxy for transplant eligibility. Results: Of 10,703 pts with MM in the database, 5982, 3059 and 1595 pts were eligible for 1L, second-line (2L), and third-line (3L) analysis, of which 76%, 84%, and 86%, respectively, had FISH test results before Tx initiation. 14% of pts with FISH test results were t(11;14)+, ~55% SR and ~35% HR. Included pts were predominately male (55%), ~90% treated in the community setting and ~16% African-American. Pts in the 3L cohort were younger at diagnosis with a median age (interquartile range) of 67 (59 ̶ 74) yrs compared with 69 (61 ̶ 76) yrs in both 1L and 2L. The 1L Tx pattern was consistent across cytogenetic cohorts with bortezomib (V), lenalidomide (R), dexamethasone (d) as the most common Tx (>42%). Together, VRd, Rd, Vd, and cyclophosphamide (Cy) in combination with Vd represented ≥90% of 1L Tx (Figure 1). Across 2L cytogenetic cohorts, the most common Tx regimens (≥25%) were VRd and Rd. The use of regimens containing carfilzomib (K) and daratumumab (D) was emerging in 2L: KRd in 8% of t(11;14)+ and HR and 5% in SR; Kd 5% in all groups; DRd in 4% of t(11;14)+ and 3% in SR and HR (Figure 1). 3L Tx pattern was fragmented with different Tx regimens. Rd was the most common 3L Tx option: 9% in t(11;14)+, 10% in SR and 7% in HR (Figure 1). Across all lines of Tx, t(11;14)+ had similar Tx outcomes to SR, and HR had poorest outcomes (Table 1). Pts TTNT shortened as they advanced to later lines of Tx (Table 1). Although TTNT did not differ by age across lines of Tx, OS was superior in pts <70 yrs across all 3 cytogenetic risk cohorts, especially in 1L where transplant in those ≤70 yrs vs >70 yrs at diagnosis was 44% vs 11% for t(11;14)+, 47% vs 10% for SR and 49% vs 9% for HR. Conclusions: This study identified cytogenetic subgroups across 1L to 3L in a predominately community setting in the US. MM t(11;14)+ pts had similar 1L and 2L Tx patterns to SR and HR. Across all lines of Tx, the outcomes of t(11;14)+ and SR pts were comparable and better than HR pts. TTNT was reduced as pts advanced to later lines of Tx. Pts continuing to 3L Tx were younger at diagnosis, but there was not a clear-cut standard of care. While TTNT did not differ by age across lines of Tx, OS was superior in pts <70 yrs across all 3 cytogenetic risk cohorts. This study sets the benchmark for novel treatment options, such as BCL-2 pathway inhibitors, primarily wherever available biomarker-driven therapy is considered appropriate. Disclosures Atrash: Takeda, Amgen, Karyopharm, BMS, Sanofi, Cellactar, Janssen and Celgene: Honoraria; BMS, Jansen oncology, Sanofi: Speakers Bureau; Amgen, GSK, Karyopharm.: Research Funding. Flahavan:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Roche Products Ltd.: Current Employment. Xu:F. Hoffmann-La Roche Ltd: Current Employment, Other: All authors received support for third party writing assistance, furnished by Scott Battle, PhD, provided by F. Hoffmann-La Roche, Basel, Switzerland.. Ma:Genentech, Inc.: Current Employment, Current equity holder in publicly-traded company. Karve:AbbVie: Current Employment, Current equity holder in publicly-traded company. Hong:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Jirau-Lucca:Genentech, Inc.: Current Employment; AbbVie: Current equity holder in publicly-traded company; BMS: Current equity holder in publicly-traded company; Celgene: Divested equity in a private or publicly-traded company in the past 24 months. Nixon:Genentech, Inc.: Current Employment, Current equity holder in publicly-traded company; F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Ailawadhi:Takeda: Honoraria; Pharmacyclics: Research Funding; Cellectar: Research Funding; BMS: Research Funding; Medimmune: Research Funding; Phosplatin: Research Funding; Amgen: Research Funding; Celgene: Honoraria; Janssen: Research Funding.

Background: Despite treatment advances, multiple myeloma (MM) remains a condition with high unmet medical need as patients (pts) relapse and become resistant to therapy. MM pts experience a range of serious disease-related symptoms and side effects impacting their functioning and health-related quality of life (HRQL). The median overall survival (OS) has improved with the advent of new treatments in the last two decades, however, the impact of newer combination treatments on pt quality of life remains unknown (Beckner, N et al. Cancer Res. 2011;183:25; Bharat, N et al. J Clin Oncol 2019;37:15(suppl):8039). Venetoclax is a novel, orally bioavailable small molecule inhibitor of BCL-2 activity in MM. In the Phase 3 double-blind, randomized clinical trial (M14-031, BELLINI) progression free survival (PFS) was studied in relapsed/refractory (RR) MM pts receiving venetoclax or placebo in combination with bortezomib and dexamethasone. In addition, patient-reported outcomes (PRO) data focused on physical functioning, pain, and fatigue from BELLINI were evaluated to better understand the overall impact on pt HRQL of adding venetoclax to bortezomib and dexamethasone-based doublet therapy. Methods: The BELLINI Phase 3 study (NCT01794520) enrolled patients ≥18 y old with R/R MM who had received 1-3 prior lines of therapy. The study met its primary endpoint of PFS (HR 0.63, 95% CI=0.44-0.89) but higher risk of death (HR 2.027, 95% CI=1.04-3.95) was observed in the treatment arm compared with placebo, although the OS data are not yet mature (Kumar, S et al. EHA Library. Jun 16 2019;273254:LB2601). The secondary HRQL endpoints included in this study were pain severity, fatigue, physical functioning (PF), and global health status, which were measured using the Brief Pain Inventory-Short Form (BPI-SF), PROMIS Fatigue Short Form surveys, and the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30). Change from baseline to day 1 of each cycle visit (up to 25 cycles or last treatment visit) was assessed for each measure in both the treatment and placebo groups. Summary analyses compared mean and median scores between arms at each cycle. The treatment effect was evaluated in a mixed effect model controlling for the patient's baseline score, total visits (or cycles of treatment), age (<65 or ≥65), prior therapy lines, and prior proteasome inhibitor exposure. The model also included an interaction term examining treatment by visits. Results: The intention-to-treat (ITT) dataset included 194 pts (median age: 66y; 53% with 2 or 3 prior lines of therapy) in the treatment group and 97 pts (median age: 65y; 55% with 2 or 3 prior lines of therapy) in the placebo group (2:1 randomization). There was no clear evidence for an independent effect of treatment on PF (P=0.522). Pain scores across multiple measures showed a similar trend, with a statistically non-significant improvement of unadjusted average "Worst Pain" scores for the venetoclax group (P=0.289; Figure B). Non-inferiority in pain results were replicated by the pain subscale of the QLQ-30 (P=0.778), the BPI pain severity index (P=0.418), and the related BPI pain interference subscale score (P=0.603). Fatigue scores likewise demonstrated no significant differences between treatment arms whether using PROMIS Cancer Fatigue t-scores (P=0.442), raw scores (P=0.568), or the 3-item QLQ-C30 subscale (P=0.959), although there was a positive trend across cycle summary scores for the treatment group compared with the placebo group. Unadjusted QLQ-C30 PF subscale scores showed declines from baseline that were generally worse in the placebo group across 25 treatment cycles, although differences were smaller and non-significant in the adjusted model (Figure A). Conclusions: Comparable HRQL in pain severity, fatigue, and PF was observed in RRMM pts receiving venetoclax in combination with bortezomib and dexamethasone compared to pts receiving bortezomib and dexamethasone. The summary scores showed outcomes that were comparable or slightly improved for those randomized to the venetoclax combination. Results of concurrent measures of the same or associated concepts reinforced confidence in these results. Additional analyses of subgroups are ongoing (eg, t(11;14), BCL-2 expression status) and may provide further insights surrounding HRQL in these populations. Figure Disclosures Gasparetto: BMS: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Celgene: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed ; Janssen: Consultancy, Honoraria, Other: Travel, accommodations, or other expenses paid or reimbursed . Popat:Takeda: Honoraria, Other: travel, accommodations, expenses; GSK: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel, accommodations, expenses; Janssen: Honoraria, Other: travel support to meetings; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. Cavo:celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accommodations, Speakers Bureau; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; novartis: Honoraria; sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; bms: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. de la Rubia:Janssen: Consultancy; AbbVie: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Takeda: Consultancy. Hungria:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Salwender:Sanofi: Honoraria, Other: Travel or accommodations; Amgen: Honoraria, Other: Travel or accommodations; Janssen Cilag: Honoraria, Other: Travel or accommodations; AbbVie: Honoraria; Bristol-Myers Squibb: Honoraria, Other: Travel or accommodations; Celgene: Honoraria, Other: Travel or accommodations; Takeda: Honoraria, Other: Travel or accommodations. Suzuki:Ono: Research Funding; BMS: Honoraria, Research Funding; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria. Maciel:Amgen: Other: funding for travel, teaching, participation in advisory boards; Janssen: Other: funding for travel, teaching, participation in advisory boards. Moreau:Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Harrison:Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: investigator on studies, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jia:AbbVie: Employment, Other: Stock/stock options. Karve:AbbVie: Employment, Other: stock/stock options. Ma:Genentech: Employment, Other: stock options; AbbVie: Other: Alliance Partner. Devine:Genentech: Employment, Other: stock options; AbbVie: Other: Alliance Partner. Benjamin:AbbVie: Employment, Other: stock/stock options.