Faculty Bibliography

PURPOSE/OBJECTIVE:Burkitt lymphoma (BL) has unique biology and clinical course but lacks a standardized prognostic model. We developed and validated a novel prognostic index specific for BL to aid risk stratification, interpretation of clinical trials, and targeted development of novel treatment approaches. METHODS:We derived the BL International Prognostic Index (BL-IPI) from a real-world data set of adult patients with BL treated with immunochemotherapy in the United States between 2009 and 2018, identifying candidate variables that showed the strongest prognostic association with progression-free survival (PFS). The index was validated in an external data set of patients treated in Europe, Canada, and Australia between 2004 and 2019. RESULTS:In the derivation cohort of 633 patients with BL, age ≥ 40 years, performance status ≥ 2, serum lactate dehydrogenase > 3× upper limit of normal, and CNS involvement were selected as equally weighted factors with an independent prognostic value. The resulting BL-IPI identified groups with low (zero risk factors, 18% of patients), intermediate (one factor, 36% of patients), and high risk (≥ 2 factors, 46% of patients) with 3-year PFS estimates of 92%, 72%, and 53%, respectively, and 3-year overall survival estimates of 96%, 76%, and 59%, respectively. The index discriminated outcomes regardless of HIV status, stage, or first-line chemotherapy regimen. Patient characteristics, relative size of the BL-IPI groupings, and outcome discrimination were consistent in the validation cohort of 457 patients, with 3-year PFS estimates of 96%, 82%, and 63% for low-, intermediate-, and high-risk BL-IPI, respectively. CONCLUSION/CONCLUSIONS:The BL-IPI provides robust discrimination of survival in adult BL, suitable for use as prognostication and stratification in trials. The high-risk group has suboptimal outcomes with standard therapy and should be considered for innovative treatment approaches.

B-cell non-Hodgkin lymphoma cell survival depends on poorly understood immune evasion mechanisms. In melanoma, the composition of the gut microbiota (GMB) is associated with immune system regulation and response to immunotherapy. We investigated the association of GMB composition and diversity with lymphoma biology and treatment outcome. Patients with diffuse large B-cell lymphoma (DLBCL), marginal zone (MZL), and follicular lymphoma (FL) were recruited at Mayo Clinic, Minnesota, and Perlmutter Cancer Center, NYU Langone Health. The pretreatment GMB was analyzed using 16S ribosomal RNA gene sequencing. We examined GMB compositions in 3 contexts: lymphoma patients (51) compared with healthy controls (58), aggressive (DLBCL) (8) compared with indolent (FL, MZL) (18), and the association of GMB with immunochemotherapy treatment outcomes (8 responders, 6 nonresponders). Respectively, we found that the pretreatment GMB in lymphoma patients had a distinct composition compared with healthy controls (P < .001); GMB compositions in DLBCL patients were significantly different than indolent patients (P = .01) with a trend toward reduced microbial diversity in DLBCL patients (P = .08); and pretreatment GMB diversity and composition were significant predictors of treatment responses (P = .01). The impact of these pilot results is limited by our small sample size, and should be considered a proof of principle. If validated, our results could lead toward improved treatment outcomes by improving medication stewardship and informing which GMB-targeted therapies should be tested to improve patient outcomes.

CONTEXT.—:The diagnostic workup of lymphoma continues to evolve rapidly as experience and discovery led to the addition of new clinicopathologic entities and techniques to differentiate them. The optimal clinically effective, efficient, and cost-effective approach to diagnosis that is safe for patients can be elusive, in both community-based and academic practice. Studies suggest that there is variation in practice in both settings. OBJECTIVE.—:To develop an evidence-based guideline for the preanalytic phase of testing, focusing on specimen requirements for the diagnostic evaluation of lymphoma. DESIGN.—:The American Society for Clinical Pathology, the College of American Pathologists, and the American Society of Hematology convened a panel of experts in the laboratory workup of lymphoma to develop evidence-based recommendations. The panel conducted a systematic review of literature to address key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation approach, recommendations were derived based on the available evidence, strength of that evidence, and key judgements as defined in the Grading of Recommendations Assessment, Development, and Evaluation Evidence to Decision framework. RESULTS.—:Thirteen guideline statements were established to optimize specimen selection, ancillary diagnostic testing, and appropriate follow-up for safe and accurate diagnosis of indolent and aggressive lymphoma. CONCLUSIONS.—:Primary diagnosis and classification of lymphoma can be achieved with a variety of specimens. Application of the recommendations can guide decisions on specimen suitability, diagnostic capabilities, and correct use of ancillary testing. Disease prevalence in patient populations, availability of ancillary testing, and diagnostic goals should be incorporated into algorithms tailored to each practice environment.

We examined adults with untreated Burkitt lymphoma (BL) from 2009 to 2018 across 30 US cancer centers. Factors associated with progression-free survival (PFS) and overall survival (OS) were evaluated in univariate and multivariate Cox models. Among 641 BL patients, baseline features included the following: median age, 47 years; HIV+, 22%; Eastern Cooperative Oncology Group (ECOG) performance status (PS) 2 to 4, 23%; >1 extranodal site, 43%; advanced stage, 78%; and central nervous system (CNS) involvement, 19%. Treatment-related mortality was 10%, with most common causes being sepsis, gastrointestinal bleed/perforation, and respiratory failure. With 45-month median follow-up, 3-year PFS and OS rates were 64% and 70%, respectively, without differences by HIV status. Survival was better for patients who received rituximab vs not (3-year PFS, 67% vs 38%; OS, 72% vs 44%; P < .001) and without difference based on setting of administration (ie, inpatient vs outpatient). Outcomes were also improved at an academic vs community cancer center (3-year PFS, 67% vs 46%, P = .006; OS, 72% vs 53%, P = .01). In multivariate models, age ≥ 40 years (PFS, hazard ratio [HR] = 1.70, P = .001; OS, HR = 2.09, P < .001), ECOG PS 2 to 4 (PFS, HR = 1.60, P < .001; OS, HR = 1.74, P = .003), lactate dehydrogenase > 3× normal (PFS, HR = 1.83, P < .001; OS, HR = 1.63, P = .009), and CNS involvement (PFS, HR = 1.52, P = .017; OS, HR = 1.67, P = .014) predicted inferior survival. Furthermore, survival varied based on number of factors present (0, 1, 2 to 4 factors) yielding 3-year PFS rates of 91%, 73%, and 50%, respectively; and 3-year OS rates of 95%, 77%, and 56%, respectively. Collectively, outcomes for adult BL in this real-world analysis appeared more modest compared with results of clinical trials and smaller series. In addition, clinical prognostic factors at diagnosis identified patients with divergent survival rates.

OBJECTIVES:The diagnostic workup of lymphoma continues to evolve rapidly as experience and discovery lead to the addition of new clinicopathologic entities and techniques to differentiate them. The optimal clinically effective, efficient, and cost-effective approach to diagnosis that is safe for patients can be elusive, in both community-based and academic practice. Studies suggest that there is variation in practice in both settings. THE AIM OF THIS REVIEW IS TO:develop an evidence-based guideline for the preanalytic phase of testing, focusing on specimen requirements for the diagnostic evaluation of lymphoma. METHODS:The American Society for Clinical Pathology, the College of American Pathologists, and the American Society of Hematology convened a panel of experts in the laboratory workup of lymphoma to develop evidence-based recommendations. The panel conducted a systematic review of the literature to address key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were derived based on the available evidence, the strength of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework. RESULTS:Thirteen guideline statements were established to optimize specimen selection, ancillary diagnostic testing, and appropriate follow-up for safe and accurate diagnosis of indolent and aggressive lymphoma. CONCLUSIONS:Primary diagnosis and classification of lymphoma can be achieved with a variety of specimens. Application of the recommendations can guide decisions about specimen suitability, diagnostic capabilities, and correct utilization of ancillary testing. Disease prevalence in patient populations, availability of ancillary testing, and diagnostic goals should be incorporated into algorithms tailored to each practice environment.

The treatment of lymphomas has undergone a shift in the last few decades, from traditional cytotoxic chemotherapy toward immune-targeting agents that supplement or, in some cases, even supplant direct tumor killing with activation of antitumor systemic immunity. Since the introduction of the first known immunomodulatory modality, allogeneic hematopoietic cell transplantation, multiple immunotherapeutic approaches have been developed including monoclonal antibodies (mABs), antibody-drug conjugates, bispecific T-cell engagers, checkpoint inhibitors, small molecule inhibitors, chimeric antigen receptor (CAR) T-cell therapies, and vaccines. Many of these agents, either as monotherapies or as a component of a combination strategy, have shown impressive results, combining efficacy with tolerability. Immunotherapy ranging from mABs to checkpoint inhibitors and CAR T-cell therapy are now integrated into lymphoma treatment from the earliest lines of therapy to the relapsed and refractory setting for both Hodgkin (HL) and non-Hodgkin lymphoma (NHL). Although further studies are needed to improve our understanding of the unique side effects of immunomodulation, to determine the optimal sequence and combinations of these agent with targeted therapies and standard chemotherapy, and to identify predictive biomarkers, they clearly represent a growing list of treatment options for both HL and NHL and an important step on our road toward cure of these diseases.

Introduction: There are few data about prognostication and outcomes in patients (pts) with HIV-BL treated in the cART era. Optimal treatment strategies to minimize treatment-related mortality (TRM) remain unclear and current recommendations are based on small studies. We conducted a multicenter international analysis to identify prognostic factors and outcomes in pts with HIV-BL treated in the cART era.
Method(s): This retrospective analysis included a subcohort from a recent study across 30 US sites (Evens et al. Blood 2020) augmented by data from 5 UK centers treated 2009-2018. Progression-free (PFS) and overall survival (OS) were estimated by Kaplan-Meier & differences assessed by log-rank test. Univariate (UVA) associations were derived via Cox model and multivariable (MVA) models were constructed by forward selection of significant variables with P<0.05.
Result(s): 249 (US: 140 & UK: 109) pts with newly diagnosed HIV-BL were included. Clinical features included median age 43 (IQR 35-50 years [yrs]); male sex: 84%; ECOG PS: 2-4: 48%; elevated LDH: 85% (> 3x upper limit of normal (ULN) 49% & >5xULN 39%); >1 extranodal (EN) site: 60%; any CNS involvement (CNSinv) 25%; and +bone marrow (BM) 46%. MYC rearrangement was reported in 93% of pts with t(8;14) in 49%, break-apart probe in 41% and MYC-light chain in 3%; the rest had classical BL with negative MYC testing (4%) or missing result (3%) (otherwise classical BL). Median CD4 count was 217 (IQR 90-392 cells/microL) with 68% pts having CD4>100 cells/microL. At BL diagnosis, HIV viral load was detectable in 55%; 39% of pts were on cART. Baseline features were similar between the US & UK cohorts with significant differences only in ECOG PS 2-4 (32% vs 65%; P<0.001) & baseline CNSinv (30% vs 17%, respectively; P=0.02). Tx regimens included: CODOX-M/IVAC (Magrath) 60%, DA-EPOCH 25%, HyperCVAD/MA 13%, & other 1%; most pts (87%) received rituximab (R). Similar regimens were used in pts with baseline CNSinv: Magrath 64%, DA-EPOCH 24% & HyperCVAD 12%. In the US, pts most frequently received DA-EPOCH (42%) followed by Magrath (32%) & HyperCVAD/MA (24%), whereas in the UK, 96% received Magrath. R was more frequently given in the US (94% vs 79%, P<0.001). Similar baseline features were seen in US pts selected for DA-EPOCH as those selected for Magrath or HyperCVAD/MA except for lower median CD4 count (144 vs 260 cells/microL; P=0.04). Overall response to Tx was: CR 70%, PR 9%, PD 14%, not evaluable 7%. TRM was 18% following HyperCVAD/MA, 13% after DA-EPOCH & 7% in patients treated with Magrath. Overall, 33% of pts had a relapse of HIV-BL with 23% systemic only & 10% CNS. With median follow-up of 4.5 yrs, 3-yr PFS & OS were 61% & 66%, respectively, and nearly identical in both countries (Fig A). Pts with CD4>100 cells/microL had better 3-yr PFS (Fig B) & OS (68% vs 57% P=0.03). We observed significantly worse outcomes in pts with baseline CNSinv (3-yr PFS 36% vs 69%, P<0.001; OS 41% vs 73%, P<0.001; Fig C). Magrath was associated with the highest 3-yr PFS (66%) compared with 63% after HyperCVAD/MA & 51% after DA-EPOCH, but the difference was not significant (P=0.13; Fig D). Pts receiving R had numerically higher PFS, but also not statistically significant (63% vs 53% P=0.16). We observed poor outcomes in pts with baseline CNSinv regardless of frontline Tx (3-yr PFS HyperCVAD/MA 40%, Magrath 39%, DA-EPOCH 32%; P=0.93; Fig E). The incidence of CNS recurrence at 3 yr across all Tx was 11%. Higher incidence was observed with DA-EPOCH (P=0.032 vs other regimens; Fig F) with no difference according to CD4 count. Variables associated with PFS & OS on UVA included: ECOG PS 2-4, >1 EN, +BM, baseline CNSinv, LDH>ULN, CD4 <100 cells/microL. On MVA, the variables independently associated with inferior PFS were ECOG PS 2-4 (HR 1.87 P=0.007); baseline CNSinv (HR 1.70, P=0.023); LDH >5xULN (HR 2.09, P<0.001); and >1 EN sites (HR 1.58 P=0.043). The same variables were significant on MVA for OS. Adjusting for all of the prognostic variables, Tx with Magrath was associated with longer PFS (adjusted HR, 0.45, P=0.005).
Conclusion(s): These data represent the largest analysis of HIV-BL to date. There were favorable tolerance and outcomes with intensive R-containing regimens with Magrath being associated with lower TRM and the highest PFS. In addition, prognostic factors for pt outcomes were associated with lymphoma characteristics rather than with HIV-related features. Pts with baseline CNSinv represent a high-risk group with unmet therapeutic needs. [Formula presented] Disclosures: Alderuccio: Oncinfo: Honoraria; Puma Biotechnology: Other: Family member; ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees; OncLive: Honoraria; Inovio Pharmaceuticals: Other: Family member; Foundation Medicine: Other: Family member; Forma Therapeutics: Other: Family member; Agios Pharmaceuticals: Other: Family member. Olszewski: Spectrum Pharmaceuticals: Research Funding; TG Therapeutics: Research Funding; Adaptive Biotechnologies: Research Funding; Genentech, Inc.: Research Funding. Evens: Epizyme: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria; Merck: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Mylteni: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria; Research To Practice: Honoraria, Speakers Bureau; Novartis: Consultancy, Honoraria. Collins: Gilead: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding; Taekda: Consultancy, Honoraria, Other: travel, accommodations, expenses, Speakers Bureau; BeiGene: Consultancy; Roche: Consultancy, Honoraria, Other: travel, accommodations, expenses, Speakers Bureau; Celleron: Consultancy, Honoraria, Research Funding; ADC Therapeutics: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Speakers Bureau; Celgene: Research Funding; Amgen: Research Funding; Pfizer: Honoraria. Danilov: Astra Zeneca: Consultancy, Research Funding; Verastem Oncology: Consultancy, Research Funding; Takeda Oncology: Research Funding; Gilead Sciences: Research Funding; Bayer Oncology: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; TG Therapeutics: Consultancy; Nurix: Consultancy; Celgene: Consultancy; Aptose Biosciences: Research Funding; Bristol-Myers Squibb: Research Funding; Rigel Pharmaceuticals: Consultancy; Karyopharm: Consultancy; Pharmacyclics: Consultancy; BeiGene: Consultancy; Abbvie: Consultancy. Jagadeesh: Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Debiopharm Group: Research Funding; MEI Pharma: Research Funding; Verastem: Membership on an entity's Board of Directors or advisory committees; Regeneron: Research Funding. Reddy: Genentech: Research Funding; Abbvie: Consultancy; BMS: Consultancy, Research Funding; Celgene: Consultancy; KITE Pharma: Consultancy. Farooq: Kite, a Gilead Company: Honoraria. Bond: Seattle Genetics: Honoraria. Khan: Celgene: Research Funding; Janssen: Honoraria; Pharmacyclics: Honoraria; Bristol Myers Squibb: Research Funding; Seattle Genetics: Research Funding. Yazdy: Bayer: Honoraria; Genentech: Research Funding; Octapharma: Consultancy; Abbvie: Consultancy. Karmali: Karyopharm: Honoraria; Takeda: Research Funding; AstraZeneca: Speakers Bureau; BeiGene: Speakers Bureau; BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau. Martin: Janssen: Consultancy; Regeneron: Consultancy; Bayer: Consultancy; Sandoz: Consultancy; I-M Consultancy; Beigene: Consultancy; Cellectar: Consultancy; Incyte: Consultancy; Kite: Consultancy; Morphosys: Consultancy; Celgene: Consultancy; Teneobio: Consultancy; Karyopharm: Consultancy, Research Funding. Diefenbach: Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding; Genentech, Inc.: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Trillium: Research Funding. Klein: Takeda: Membership on an entity's Board of Directors or advisory committees. Haverkos: Viracta THerapeutics: Consultancy. Epperla: Verastem Oncology: Speakers Bureau; Pharmacyclics: Honoraria. Caimi: Amgen: Other: Advisory Board; Bayer: Other: Advisory Board; Kite Pharma: Other: Advisory Board; ADC Therapeutics: Other: Advisory Board, Research Funding; Celgene: Speakers Bureau; Verastem: Other: Advisory Board. Kamdar: Roche: Research Funding. Feldman: Eisai: Research Funding; Pfizer: Research Funding; Kyowa Kirin: Consultancy, Research Funding; Portola: Research Funding; Janssen: Speakers Bureau; AstraZeneca: Consultancy; Trillium: Research Funding; Cell Medica: Research Funding; Amgen: Research Funding; Pharmacyclics: Honoraria, Other, Speakers Bureau; Abbvie: Honoraria; Bayer: Consultancy, Honoraria; Viracta: Research Funding; Rhizen: Research Funding; Corvus: Research Funding; BMS: Consultancy, Honoraria, Research Funding; Kite: Honoraria, Other: Travel expenses, Speakers Bureau; Celgene: Honoraria, Research Funding; Takeda: Honoraria, Other: Travel expenses; Seattle Genetics, Inc.: Consultancy, Honoraria, Other: Travel expenses, Research Funding, Speakers Bureau. Smith: AstraZeneca: Consultancy; Millenium/Takeda: Consultancy; Karyopharm: Consultancy; Beigene: Consultancy; Seattle Genetics: Research Funding; Ayala: Research Funding; Bayer: Research Funding; AstraZeneca: Research Funding; Acerta Pharma BV: Research Funding; Bristol Meyers Squibb: Research Funding; Portola: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Incyte: Research Funding; Ignyta: Research Funding; Genentech: Research Funding; De Novo Biopharma: Research Funding. Portell: Amgen: Consultancy; Pharmacyclics: Consultancy; AbbVie: Research Funding; Janssen: Consultancy; TG Therapeutics: Research Funding; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; Xencor: Research Funding; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Research Funding. Naik: Celgene: Other: advisory board; Sanofi: Other: advisory board. Lossos: Janssen Biotech: Honoraria; Verastem: Consultancy, Honoraria; Stanford University: Patents & Royalties; NCI: Research Funding; Seattle Genetics: Consultancy, Other; Janssen Scientific: Consultancy, Other. Cwynarski: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Atara: Consultancy, Membership on an entity's Board of Directors or advisory committees; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau.
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[Formula presented] Background. BL is a rare, high-grade B-cell lymphoma that is often studied in trials with small sample sizes. Historical definitions of "low-risk BL" vary between studies, use arbitrary cutoffs for lactate dehydrogenase (LDH), and identify a small favorable group, leaving >80-90% of patients (pts) in an undifferentiated "high-risk" category. A validated prognostic index will help compare study cohorts and better define good-prognosis pts for whom reduced treatment would be appropriate vs a poor-prognosis group in need of new approaches. Herein, we constructed and validated a simplified prognostic model for BL applicable to diverse clinical settings across the world. Methods. We derived the BL-IPI from a large real-world evidence cohort of US adults treated for BL in 2009-2018 (Evens A, Blood 2020). Progression-free survival (PFS) from diagnosis until BL recurrence, progression, death, or censoring was the primary outcome. We first determined the best prognostic cutoffs for age, LDH (normalized to local upper limit normal, ULN), hemoglobin (Hgb), and albumin. Independent risk factors were ascertained by forward stepwise selection into Cox regression from candidate variables: age, sex, HIV+ status, ECOG performance status (PS) >=2, advanced stage (3/4), involvement of >1 extranodal site, bone marrow, central nervous system (CNS), values of LDH, Hgb, and albumin. Derivation models used multiple imputation to mitigate bias from missing data and reported hazard ratios (HR) with 95% confidence interval (CI). BL-IPI groups, defined by inspection of survival curves, were compared using log-rank test for trend. We validated performance of the BL-IPI in an external retrospective dataset of BL pts treated contemporaneously in centers from the United Kingdom, Scandinavia, Canada, and Australia. Results. Characteristics of pts in the derivation (N= 633) and validation (N=457) cohorts are shown in the Table. Age >=40 years (yr), LDH >3xULN, Hgb <11.5 g/dL, and albumin <3.5 g/dL were determined as optimal prognostic cutoffs. Age >=40 yr, PS >=2, stage 3/4, involvement of marrow, CNS, LDH >3xULN, low Hgb, and low albumin were associated with inferior PFS in univariate tests. In the multivariable model age >=40 yr, LDH >3xULN, PS >=2, and CNS involvement were selected as 4 independent prognostic factors; adding stage did not enhance the model. The model was simplified to 3 groups with 0 (low risk; 18% of pts), 1 (intermediate risk; 36% of pts; HR=3.14; 95%CI, 1.61-6.14), or 2-4 factors (high risk; 46% of pts; HR=6.52; 95%CI, 3.48-12.20; Fig A) with 3 yr PFS of 92%, 72%, and 53%, respectively (P<.001, Fig. B); median PFS was reached only in the high-risk group (46 months, 95%CI, 19-53). BL-IPI was similarly prognostic for overall survival (OS, P<.001; Fig. C). Among pts with stage III/IV (historically classified as "high-risk" and constituting 78% of all pts in the cohort), the BL-IPI further discriminated subgroups with 3 yr PFS of 87%, 71%, and 52%, respectively (P<.001; Fig. D), and OS of 95%, 75%, and 57%, respectively (P<.001; Fig. E). In addition, BL-IPI was prognostic regardless of HIV status, in the subcohort treated with rituximab (3 yr PFS: 92%, 73%, and 55%, respectively, P<.001), and among pts treated with specific regimens: CODOX-M/IVAC+/-R (3 yr PFS: 88%, 67%, 61%, respectively, P=.004), DA-EPOCH-R (3 yr PFS, 87%, 73%, 51%, respectively, P<.001), or hyperCVAD/MA+/-R (3yr PFS: 100%, 80%, 54%, respectively, P<.001). In the international validation cohort, fewer pts had CNS involvement; most received CODOX-M/IVAC+R; and PFS/OS estimates at 3 yr were higher. BL-IPI categories were of similar size (low-risk 15%, intermediate-risk 35%, high-risk 50%), and provided similar risk discrimination (Harrell's C=.65 in both datasets). PFS at 3 yr was 96%, 82%, and 63%, respectively (P<.001; Fig. F), and OS was 99%, 85%, and 64%, respectively (P<.001; Fig. G). In the validation cohort, BL-IPI remained prognostic in the subsets receiving rituximab (P<.001) and in advanced stage (P<.001). Conclusions. BL-IPI is a novel prognostic index specific to BL, which was validated to allow for simplified stratification and comparison of risk distribution in geographically diverse cohorts. The index identified a low-risk group with PFS >90-95%, which could be targeted with future strategies for treatment de-escalation. Conversely, only about 55-60% of pts in the high-risk group achieved cure with currently available immunochemotherapy. [Formula presented] Disclosures: Olszewski: Spectrum Pharmaceuticals: Research Funding; Genentech, Inc.: Research Funding; TG Therapeutics: Research Funding; Adaptive Biotechnologies: Research Funding. Jakobsen: Takeda: Honoraria. Collins: ADC Therapeutics: Consultancy, Honoraria; Celleron: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Speakers Bureau; Amgen: Research Funding; BeiGene: Consultancy; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Gilead: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding; Taekda: Consultancy, Honoraria, Other: travel, accommodations, expenses, Speakers Bureau; Roche: Consultancy, Honoraria, Other: travel, accommodations, expenses, Speakers Bureau; Pfizer: Honoraria; Celgene: Research Funding. Cwynarski: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Atara: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support, Speakers Bureau. Bachanova: Incyte: Research Funding; Karyopharma: Membership on an entity's Board of Directors or advisory committees; BMS: Research Funding; FATE: Research Funding; Kite: Membership on an entity's Board of Directors or advisory committees; Gamida Cell: Membership on an entity's Board of Directors or advisory committees, Research Funding. Danilov: Abbvie: Consultancy; BeiGene: Consultancy; Nurix: Consultancy; Celgene: Consultancy; Gilead Sciences: Research Funding; Takeda Oncology: Research Funding; Pharmacyclics: Consultancy; Bayer Oncology: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; TG Therapeutics: Consultancy; Astra Zeneca: Consultancy, Research Funding; Verastem Oncology: Consultancy, Research Funding; Karyopharm: Consultancy; Aptose Biosciences: Research Funding; Bristol-Myers Squibb: Research Funding; Rigel Pharmaceuticals: Consultancy. Diefenbach: Trillium: Research Funding; Millenium/Takeda: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Genentech, Inc.: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; Denovo: Research Funding. Epperla: Pharmacyclics: Honoraria; Verastem Oncology: Speakers Bureau. Farooq: Kite, a Gilead Company: Honoraria. Feldman: Pfizer: Research Funding; Portola: Research Funding; Janssen: Speakers Bureau; AstraZeneca: Consultancy; Cell Medica: Research Funding; Seattle Genetics, Inc.: Consultancy, Honoraria, Other: Travel expenses, Research Funding, Speakers Bureau; Viracta: Research Funding; Trillium: Research Funding; Rhizen: Research Funding; Corvus: Research Funding; BMS: Consultancy, Honoraria, Research Funding; Kite: Honoraria, Other: Travel expenses, Speakers Bureau; Celgene: Honoraria, Research Funding; Takeda: Honoraria, Other: Travel expenses; Amgen: Research Funding; Pharmacyclics: Honoraria, Other, Speakers Bureau; Abbvie: Honoraria; Bayer: Consultancy, Honoraria; Eisai: Research Funding; Kyowa Kirin: Consultancy, Research Funding. Gerrie: AbbVie: Consultancy, Honoraria, Research Funding; Astrazeneca: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Roche: Research Funding; Sandoz: Consultancy. Jagadeesh: Regeneron: Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Debiopharm Group: Research Funding; MEI Pharma: Research Funding; Verastem: Membership on an entity's Board of Directors or advisory committees. Kamdar: BMS: Consultancy; Abbvie: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; AstraZeneca: Consultancy; Pharmacyclics: Consultancy; Seattle Genetics: Speakers Bureau. Karmali: Takeda: Research Funding; AstraZeneca: Speakers Bureau; BeiGene: Speakers Bureau; Karyopharm: Honoraria; BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau. Khan: Seattle Genetics: Research Funding; Janssen: Honoraria; Pharmacyclics: Honoraria; Bristol Myers Squibb: Research Funding; Celgene: Research Funding. Klein: Takeda: Membership on an entity's Board of Directors or advisory committees. Lossos: Verastem: Consultancy, Honoraria; Stanford University: Patents & Royalties; Seattle Genetics: Consultancy, Other; Janssen Biotech: Honoraria; NCI: Research Funding; Janssen Scientific: Consultancy, Other. Lunning: ADC Therapeutics: Consultancy; Legend: Consultancy; Acrotech: Consultancy; AstraZeneca: Consultancy, Honoraria; Aeratech: Consultancy, Honoraria; Beigene: Consultancy, Honoraria; Verastem: Consultancy, Honoraria; TG Therapeutics: Research Funding; Novartis: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Curis: Research Funding; Bristol Meyers Squibb: Consultancy, Honoraria, Research Funding. Martin: I-M Consultancy; Celgene: Consultancy; Teneobio: Consultancy; Karyopharm: Consultancy, Research Funding; Janssen: Consultancy; Sandoz: Consultancy; Bayer: Consultancy; Beigene: Consultancy; Cellectar: Consultancy; Incyte: Consultancy; Kite: Consultancy; Morphosys: Consultancy; Regeneron: Consultancy. Martinex-Calle: Abbvie: Other: Travel grant. Naik: Celgene: Other: advisory board; Sanofi: Other: advisory board. Palmisiano: Genentech: Research Funding; AbbVie: Research Funding. Phillips: Beigene: Honoraria; Roche: Research Funding. Phillips: Seattle Genetics: Consultancy; Incyte: Consultancy, Other: travel expenses; AstraZeneca: Consultancy; Karyopharm: Consultancy; Beigene: Consultancy; Bayer: Consultancy, Research Funding; BMS: Consultancy; Pharmacyclics: Consultancy; Abbvie: Consultancy, Research Funding; Cardinal Health: Consultancy. Portell: Roche/Genentech: Consultancy, Research Funding; Infinity: Research Funding; Bayer: Consultancy; Amgen: Consultancy; TG Therapeutics: Research Funding; AbbVie: Research Funding; Pharmacyclics: Consultancy; Janssen: Consultancy; Kite: Consultancy, Research Funding; Acerta/AstraZeneca: Research Funding; Xencor: Research Funding; BeiGene: Consultancy, Research Funding. Reddy: Celgene: Consultancy; BMS: Consultancy, Research Funding; Genentech: Research Funding; Abbvie: Consultancy; KITE Pharma: Consultancy. Yazdy: Abbvie: Consultancy; Genentech: Research Funding; Octapharma: Consultancy; Bayer: Honoraria. Smith: Bristol Meyers Squibb: Research Funding; Ayala: Research Funding; Seattle Genetics: Research Funding; Portola: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Incyte: Research Funding; Ignyta: Research Funding; Genentech: Research Funding; De Novo Biopharma: Research Funding; AstraZeneca: Consultancy; Millenium/Takeda: Consultancy; Beigene: Consultancy; Bayer: Research Funding; AstraZeneca: Research Funding; Acerta Pharma BV: Research Funding; Karyopharm: Consultancy. Cheah: Celgene, F. Hoffmann-La Roche, Abbvie, MSD: Research Funding; Celgene, F. Hoffmann-La Roche, MSD, Janssen, Gilead, Ascentage Pharma, Acerta, Loxo Oncology, TG therapeutics: Honoraria. El-Galaly: F. Hoffmann-La Roche: Current Employment, Other: Support of parent study and funding of editorial support. Evens: Research To Practice: Honoraria, Speakers Bureau; Mylteni: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Merck: Consultancy, Honoraria, Research Funding; Epizyme: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria.
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Sarit Assouline and Won Seog Kim contributed equally. Introduction: Follicular lymphoma (FL) is considered an indolent yet incurable disease characterized by recurrent relapses: disease-free intervals shorten, and refractoriness increases with each relapse. Patients (pts) with FL who have received at least two prior systemic therapies typically have a poor prognosis. This is particularly true for those who have progression of disease within 24 months of front-line treatment (POD24), or are refractory to multiple agent classes; such patients are left with limited treatment options. Mosunetuzumab is a full-length, fully humanized immunoglobulin G1 CD20/CD3 bispecific antibody that redirects T cells to engage and eliminate malignant B cells. GO29781 (NCT02500407) is an ongoing open-label, multicenter, Phase I/Ib, dose-escalation and expansion study evaluating the safety, efficacy and pharmacokinetics of mosunetuzumab in pts with relapsed/refractory (R/R) B-cell lymphoma. Here, we present updated clinical data from pts with R/R FL treated with mosunetuzumab after at least two prior systemic therapies.
Method(s): Data are presented from Group B, in which pts received intravenous mosunetuzumab monotherapy as step-up doses in Cycle 1 on Days 1 and 8 and the target dose administered on Day 15. Mosunetuzumab was given on Day 1 of each subsequent 21-day cycle for 8 cycles in pts with a complete response (CR), and up to 17 cycles in those with a partial response (PR) or stable disease (SD).
Result(s): As of January 21, 2020, 62 pts with FL (with at least two prior systemic therapies), received mosunetuzumab at dose levels between 0.4/1.0/2.8mg and 1/2/13.5mg (Cycle 1 Day 1/8/15 dose levels). The median age was 59 (range 27-85) years, and median number of prior therapies was 3 (range 2-11). Thirty-three pts (53%) were refractory to both a prior anti-CD20 antibody and an alkylating agent (double refractory), 30 (48%) had POD24, and four (6%) had received prior chimeric antigen receptor T-cell (CAR-T) therapy. The overall response rate (ORR) was 68% (42/62), with 31 pts (50%) achieving CR (Figure). Consistent CR rates were observed in high-risk pt populations, including those with double refractory disease (18/33 [55%]), POD24 (16/30 [53%]), PI3Ki refractory (7/9 [78%]), and those who received prior CAR-T therapy (2/4 [50%]). With a median time on study of 14.4 months, 26 pts (62% of all responders; including 74% of pts who achieved CR) remained in remission at the data cut-off. The median duration of response (DOR) was 20.4 months (95% CI: 11.7 months, upper limit not reached) for all 42 responders. The median PFS was 11.8 months (95% CI: 7.3-21.9 months). Adverse events (AEs) were reported in 60 pts (97%); serious adverse events (SAE) were reported in 22 pts (35%). The most frequently reported (>10% of pts) grade (Gr) 3 or higher AEs included hypophosphatemia (23%; transient and clinically asymptomatic) and neutropenia (21%; with a low rate of febrile neutropenia [2%]). Overall, 14 pts (23%) experienced CRS; in four pts, CRS was classified as a SAE. CRS events were reversible, mostly of Gr 1 or 2 (Gr 1, n=11; Gr 2, n=2; Gr 3, n=1; Lee, et al. Blood 2014), and predominantly occurred during Cycle 1. No patient required tocilizumab, intensive care unit admission or use of vasopressors for CRS management. Neurologic AEs (NAEs; defined by any AEs reported as Preferred Terms in SOC Nervous System Disorders and SOC Psychiatric Disorders) were observed in 28 pts (45%); all were Gr 1 (n=18) or 2 (n=10). The most commonly reported NAEs were headache (24%), insomnia (15%) and dizziness (11%). No Gr >=3 NAEs or serious NAEs were reported.
Conclusion(s): Fixed-duration mosunetuzumab monotherapy results in high response rates and durable disease control with a tolerable safety profile in heavily pretreated patients with FL, including known high-risk subgroups. Updated pharmacodynamics and biomarker data will be presented at the meeting. [Formula presented] Disclosures: Assouline: BeiGene: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Research Funding; Pfizer: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Speakers Bureau. Kim: Mundipharma: Research Funding; Donga: Research Funding; Kyowa Kirn: Research Funding; Celltrion: Research Funding; JJ: Research Funding; Pfizer: Research Funding; F. Hoffmann-La Roche: Research Funding. Sehn: Genentech, Inc.: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Teva: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Chugai: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria; Verastem Oncology: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria. Schuster: AlloGene, AstraZeneca, BeiGene, Genentech, Inc./ F. Hoffmann-La Roche, Juno/Celgene, Loxo Oncology, Nordic Nanovector, Novartis, Tessa Therapeutics: Consultancy, Honoraria; Novartis, Genentech, Inc./ F. Hoffmann-La Roche: Research Funding. Cheah: Celgene, F. Hoffmann-La Roche, Abbvie, MSD: Research Funding; Celgene, F. Hoffmann-La Roche, MSD, Janssen, Gilead, Ascentage Pharma, Acerta, Loxo Oncology, TG therapeutics: Honoraria. Nastoupil: Karus Therapeutics: Research Funding; Gilead/KITE: Honoraria; TG Therapeutics: Honoraria, Research Funding; Merck: Research Funding; Novartis: Honoraria, Research Funding; Gamida Cell: Honoraria; Bayer: Honoraria; Pfizer: Honoraria, Research Funding; LAM Therapeutics: Research Funding; Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech, Inc.: Honoraria, Research Funding. Shadman: Fred Hutchinson / University of Washington: Current Employment; Abbvie, Genentech, Inc., AstraZeneca, Sound Biologics, Pharmacyclics, Verastem, ADC therapeutics, Beigene, Cellectar, BMS, Mophosys and Atara Biotherapeutics: Consultancy; Mustang Bio, Celgene, Pharmacyclics, Gilead, Genentech, Inc., Abbvie, TG therapeutics, Beigene, AstraZeneca, Sunesis: Research Funding. Yoon: Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Kyowahako Kirin: Research Funding; Janssen: Consultancy; F. Hoffmann-La Roche: Other: All authors received support for third-party writing assistance, furnished by Scott Battle, PhD, provided by F. Hoffmann-La Roche, Basel, Switzerland., Research Funding; YuhanPharma: Research Funding. Matasar: Daiichi Sankyo: Consultancy; IGM Biosciences: Research Funding; Immunovaccine Technologies: Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Teva: Consultancy; Rocket Medical: Consultancy, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding; GlaxoSmithKline: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; Juno Therapeutics: Consultancy; Takeda: Consultancy, Honoraria; Genentech, Inc.: Consultancy, Honoraria, Research Funding; Merck: Consultancy; Bayer: Consultancy, Honoraria, Research Funding. Diefenbach: Trillium: Research Funding; Millenium/Takeda: Research Funding; Merck: Consultancy, Research Funding; MEI: Research Funding; LAM Therapeutics: Research Funding; Incyte: Research Funding; Genentech, Inc.: Consultancy, Research Funding; Denovo: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding. Gregory: Janssen: Consultancy; F. Hoffmann-La Roche, Genentech, Inc., MSD, AbbVie, BeiGene, AstraZeneca, Celgene, BMS: Research Funding; F. Hoffmann-La Roche, Novartis, AbbVie: Speakers Bureau; F. Hoffmann-La Roche, Novartis, Sandoz, Gilead, AbbVie, MSD: Honoraria; F. Hoffmann-La Roche, Novartis, Sandoz, Gilead: Membership on an entity's Board of Directors or advisory committees. Bartlett: BMS/Celgene: Research Funding; Merck: Research Funding; Kite, a Gilead Company: Research Funding; Immune Design: Research Funding; Janssen: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium: Research Funding; Pharmacyclics: Research Funding; Seattle Genetics: Consultancy, Research Funding; Affimed Therapeutics: Research Funding; Autolus: Research Funding; Acerta: Consultancy; Roche/Genentech: Consultancy, Research Funding; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees, Research Funding; BTG: Consultancy; ADC Therapeutics: Consultancy; Forty Seven: Research Funding. Wei: Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Doral: Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Yin: Genentech, Inc.: Current Employment, Current equity holder in publicly-traded company. Negricea: F. Hoffmann-La Roche: Current Employment. Li: F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Penuel: Genentech, Inc./ F. Hoffmann-La Roche: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Huang: F. Hoffmann-La Roche: Current Employment. Budde: AstraZeneca: Speakers Bureau; Merck, Amgen, AstraZeneca, Mustang Therapeutics: Research Funding; F. Hoffmann-La Roche, Kite Pharma: Consultancy. OffLabel Disclosure: Mosunetuzumab (RG7828) is a full-length, fully humanized immunoglobulin G1 (IgG1) bispecific antibody targeting both CD3 (on the surface of T cells) and CD20 (on the surface of B cells). Mosunetuzumab redirects T cells to engage and eliminate malignant B cells. Mosunetuzumab is an investigational agent.
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BACKGROUND:Hodgkin lymphoma is potentially curable. However, 15-35% of older patients (ie, >60 years) have a lower response rate, worse survival outcomes, and greater toxicity than younger patients. Brentuximab vedotin and nivolumab exhibit activity in patients with relapsed or refractory Hodgkin lymphoma. We therefore aimed to evaluate the safety and efficacy of brentuximab vedotin and nivolumab in untreated older patients with Hodgkin lymphoma or in younger patients considered unsuitable for standard ABVD (ie, doxorubicin, bleomycin, vinblastine, and dacarbazine) therapy. METHODS:We did a multicentre, single-arm, phase 2 trial at eight cancer centres in the USA. Previously untreated patients with classic Hodgkin lymphoma were eligible for study enrolment if they were 60 years or older, or younger than 60 years but considered unsuitable for standard chemotherapy because of a cardiac ejection fraction of less than 50%, pulmonary diffusion capacity of less than 80%, or a creatinine clearance of 30 mL/min or more but less than 60 mL/min, or those who refused chemotherapy. Patients were also required to have an Eastern Cooperative Oncology Group (ECOG) performance status of 0-2. Patients received brentuximab vedotin at 1·8 mg/kg (dose cap at 180 mg) and nivolumab at 3 mg/kg both intravenously every 21 days for 8 cycles. The primary endpoint was the overall response, defined as a partial metabolic response or complete metabolic response at the end of 8 cycles of treatment. A per protocol analysis was done including all patients who received treatment in the activity and safety analyses. This study is registered with ClinicalTrials.gov, number NCT02758717. FINDINGS/RESULTS:Between May 13, 2016, and Jan 30, 2019, the study accrued 46 patients. The median age was 71·5 years (IQR 64-77), with two (4%) of 46 patients younger than 60 years. Median follow-up was 21·2 months (IQR 15·6-29·9), and 35 (76%) of 46 patients completed all 8 cycles of therapy. At the interim analysis on Oct 11, 2019, the first 25 evaluable patients had an overall response rate of 64% ([95% CI 43-82] 16 of 25 patients; 13 [52%] had a complete metabolic response and three [12%] had a partial metabolic response). The trial was closed to accrual on Oct 14, 2019, after the interim analysis failed to meet the predefined criteria. In all 46 evaluable patients, 22 (48%) patients achieved a complete metabolic response and six (13%) achieved a partial metabolic response (overall response rate 61% [95% CI 45-75]). 14 (30%) of 46 patients had 16 dose adjustments, primarily due to neurotoxicity. 22 (48%) of 46 patients had peripheral neuropathy (five [11%] patients had grade 3 peripheral neuropathy). Grade 4 adverse events included increased aminotranferases (one [2%] of 46), increased lipase or amylase (two [4%]), and pancreatitis (one [2%]). One (2%) patient died from cardiac arrest, possibly treatment related. INTERPRETATION/CONCLUSIONS:Although the trial did not meet the prespecified activity criteria, brentuximab vedotin plus nivolumab is active in older patients with previously untreated Hodgkin lymphoma with comorbidities. The regimen was also well tolerated in the majority of patients in this older population. Future trials should be based on optimising the dose and schedule, perhaps combined with other targeted agents that might permit chemotherapy-free strategies in older patients with Hodgkin lymphoma. FUNDING/BACKGROUND:Seattle Genetics and Bristol Myers Squibb.