Abstract: Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02735707

Abstract: The longer-term effects of therapies for the treatment of critically ill patients with COVID-19 are unknown. Objective To determine the effect of multiple interventions for critically ill adults with COVID-19 on longer-term outcomes. Design, Setting, and Participants Prespecified secondary analysis of an ongoing adaptive platform trial (REMAP-CAP) testing interventions within multiple therapeutic domains in which 4869 critically ill adult patients with COVID-19 were enrolled between March 9, 2020, and June 22, 2021, from 197 sites in 14 countries. The final 180-day follow-up was completed on March 2, 2022. Interventions Patients were randomized to receive 1 or more interventions within 6 treatment domains: immune modulators (n = 2274), convalescent plasma (n = 2011), antiplatelet therapy (n = 1557), anticoagulation (n = 1033), antivirals (n = 726), and corticosteroids (n = 401). Main Outcomes and Measures The main outcome was survival through day 180, analyzed using a bayesian piecewise exponential model. A hazard ratio (HR) less than 1 represented improved survival (superiority), while an HR greater than 1 represented worsened survival (harm); futility was represented by a relative improvement less than 20% in outcome, shown by an HR greater than 0.83. Results Among 4869 randomized patients (mean age, 59.3 years; 1537 [32.1%] women), 4107 (84.3%) had known vital status and 2590 (63.1%) were alive at day 180. IL-6 receptor antagonists had a greater than 99.9% probability of improving 6-month survival (adjusted HR, 0.74 [95% credible interval {CrI}, 0.61-0.90] ) and antiplatelet agents had a 95% probability of improving 6-month survival (adjusted HR, 0.85 [95% CrI, 0.71-1.03]) compared with the control, while the probability of trial-defined statistical futility (HR & amp;gt;0.83) was high for therapeutic anticoagulation (99.9%; HR, 1.13 [95% CrI, 0.93-1.42]), convalescent plasma (99.2%; HR, 0.99 [95% CrI, 0.86-1.14] ), and lopinavir-ritonavir (96.6%; HR, 1.06 [95% CrI, 0.82-1.38]) and the probabilities of harm from hydroxychloroquine (96.9%; HR, 1.51 [95% CrI, 0.98-2.29] ) and the combination of lopinavir-ritonavir and hydroxychloroquine (96.8%; HR, 1.61 [95% CrI, 0.97-2.67]) were high. The corticosteroid domain was stopped early prior to reaching a predefined statistical trigger; there was a 57.1% to 61.6% probability of improving 6-month surviva l across varying hydrocortisone dosing strategies. Conclusions and Relevance Among critically ill patients with COVID-19 randomized to receive 1 or more therapeutic interventions, treatment with an IL-6 receptor antagonist had a greater than 99.9% probability of improved 180-day mortality compared with patients randomized to the control, and treatment with an antiplatelet had a 95.0% probability of improved 180-day mortality compared with patients randomized to the control. Overall, when considered with previously reported short-term results, the findings indicate that initial in-hospital treatment effects were consistent for most therapies through 6 months.

Abstract: Background: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy approved for the treatment of R/R large B-cell lymphoma and follicular lymphoma (FL), both after ≥2 lines of systemic therapy. ZUMA-5 is a Phase 2, multicenter, single-arm study evaluating axi-cel in patients with R/R iNHL (including FL and marginal zone lymphoma [MZL]). In the primary analysis of ZUMA-5 (N=104; 17.5 months median follow-up), the overall response rate (ORR) was 92% (76% complete response [CR] rate), and median peak CAR T-cell levels were numerically greater in patients with FL who were in ongoing response at data cutoff than in those who relapsed (Jacobson et al. ASH 2020. Abstract 700). Here, we report updated clinical and pharmacologic outcomes from ZUMA-5. Methods: Adult patients with R/R FL or MZL after ≥2 lines of therapy (including an anti-CD20 mAb plus an alkylating agent) underwent leukapheresis and conditioning chemotherapy followed by a single axi-cel infusion at 2×10 6 CAR T cells/kg. The primary endpoint was centrally assessed ORR per Lugano classification. The updated efficacy analysis occurred when ≥80 consecutively treated patients with FL had ≥2 years of follow-up post-infusion and included patients with MZL who had ≥4 weeks of follow-up post-infusion. Results: As of March 31, 2021, 149 patients with iNHL (124 FL; 25 MZL) were treated with axi-cel. Of those, 110 patients (86 FL; 24 MZL) were eligible for efficacy analyses. Among eligible patients with FL, median follow-up was 30.9 months (range, 24.7-44.3). Centrally assessed ORR was 94% in patients with FL (79% CR rate). At data cutoff, 57% of eligible patients with FL had ongoing responses; 68% of patients who achieved a CR had ongoing responses. The estimated duration of response (DOR) and progression-free survival (PFS) medians were 38.6 months and 39.6 months in patients with FL, respectively. Among patients with FL who progressed & lt;2 years after initial chemoimmunotherapy (POD24; n=49), median DOR was 38.6 months, while median DOR was not reached for those without POD24 (n=29). Median PFS in patients with FL and POD24 was 39.6 months, whereas median PFS was not reached in those without POD24. Median time to next treatment (TTNT) was 39.6 months in all eligible patients with FL. Median overall survival (OS) was not reached, with an estimated OS rate at 24 months of 81%. Among eligible patients with MZL, median follow-up was 23.8 months (range, 7.4-39.4). The ORR was 83% in patients with MZL (63% CR rate), with 50% of eligible patients in ongoing response and 73% of patients with a CR in ongoing response at data cutoff. Medians for DOR and TTNT were not reached in patients with MZL; 24-month rates were not estimable and 51%, respectively. Median PFS was 17.3 months in patients with MZL and median OS was not reached (70% OS rate at 24 months). Common Grade ≥3 AEs in all treated patients with iNHL were consistent with prior reporting: neutropenia (33%), decreased neutrophil count (28%), and anemia (25%). Grade ≥3 cytopenias present ≥30 days post-infusion were reported in 34% of patients with iNHL (33% FL; 36% MZL). Consistent with previous reports, Grade ≥3 cytokine release syndrome (CRS) and neurologic events (NEs) occurred in 7% of patients (6% FL; 8% MZL) and 19% of patients (15% FL; 36% MZL), respectively. Most CRS cases (120/121) and NEs (82/87) of any grade resolved by data cutoff. Among patients with FL who had evaluable samples, 76% (65/86) had detectable CAR gene-marked cells at low levels by 12 months post-infusion; 53% (23/43) had detectable cells 24 months post-infusion. Among evaluable patients with MZL, 67% (8/12) had detectable CAR gene-marked cells 12 months post-infusion; 60% (3/5) had detectable cells 24 months post-infusion. B-cell reconstitution was detectable in 59% of evaluable patients with FL (49/83) and 42% of those with MZL (5/12) by 12 months post-infusion. By 24 months, B cells were detectable in 61% of evaluable patients with FL (25/41) and 50% of those with MZL (2/4). Conclusions: With long-term follow-up in ZUMA-5, axi-cel demonstrated substantial and continued benefit in patients with iNHL. In FL, high response rates translated to durability, with a median DOR of 38.6 months and 57% of eligible patients in ongoing response at data cutoff. In MZL, efficacy outcomes appeared to improve with longer follow-up, with the median DOR and OS not yet reached. Axi-cel maintained a manageable safety profile, with no new safety signals . Disclosures Neelapu: Kite, a Gilead Company, Merck, Bristol Myers Squibb, Novartis, Celgene, Pfizer, Allogene Therapeutics, Cell Medica/Kuur, Incyte, Precision Biosciences, Legend Biotech, Adicet Bio, Calibr, Unum Therapeutics and Bluebird Bio: Honoraria; Takeda Pharmaceuticals and related to cell therapy: Patents & Royalties; Kite, a Gilead Company, Bristol Myers Squibb, Merck, Poseida, Cellectis, Celgene, Karus Therapeutics, Unum Therapeutics (Cogent Biosciences), Allogene, Precision BioSciences, Acerta and Adicet Bio: Research Funding; Kite, a Gilead Company, Merck, Bristol Myers Squibb, Novartis, Celgene, Pfizer, Allogene, Kuur, Incyte, Precision BioSciences, Legend, Adicet Bio, Calibr, and Unum Therapeutics: Other: personal fees. Chavez: Merk: Research Funding; MorphoSys, Bayer, Karyopharm, Kite, a Gilead Company, Novartis, Janssen, AbbVie, TeneoBio, and Pfizer: Consultancy; MorphoSys, AstraZeneca, BeiGene, Genentech, Kite, a Gilead Company, and Epizyme: Speakers Bureau; AstraZeneca: Research Funding; ADC Therapeutics: Consultancy, Research Funding; BMS: Speakers Bureau. Sehgal: Juno/Celgene: Research Funding; Kite/Gilead: Research Funding. Epperla: Genzyme: Honoraria; Karyopharm: Other: Ad Board; Beigene: Speakers Bureau; Verastem: Speakers Bureau. Bachy: Kite, a Gilead Company: Honoraria; Novartis: Honoraria; Daiishi: Research Funding; Roche: Consultancy; Takeda: Consultancy; Incyte: Consultancy. Munshi: Kite, a Gilead Company, and Incyte: Honoraria; Kite, a Gilead Company, and Incyte: Speakers Bureau. Casulo: Genentech: Research Funding; BMS: Research Funding; Verastem: Research Funding; Gilead: Research Funding. Maloney: Kite, a Gilead Company, Juno, and Celgene: Research Funding; A2 Biotherapeutics: Consultancy; BioLineRx, Juno, Celgene, Kite, a Gilead Company, Gilead, Novartis, and Pharmacyclics: Honoraria; A2 Biotherapeutics: Divested equity in a private or publicly-traded company in the past 24 months; Juno: Patents & Royalties. Reshef: Bayer: Consultancy; BMS, Regeneron, TScan, Synthekine, Atara, Jasper, Bayer: Consultancy; ilead, BMS, Precision, Immatics, Atara, Takeda, Shire, Pharmacyclics, Incyte: Research Funding; Gilead and Novartis: Honoraria. Leslie: Pharmacyclics: Consultancy, Honoraria, Speakers Bureau; Merck: Consultancy; Abbvie: Consultancy, Honoraria; Kite, a Gilead Company: Consultancy, Honoraria, Speakers Bureau; Epizyme: Consultancy, Honoraria, Speakers Bureau; Celgene/BMS: Consultancy, Honoraria, Speakers Bureau; BeiGene: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Karyopharm Therapeutics: Honoraria, Speakers Bureau; PCYC/Janssen: Consultancy, Honoraria, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Speakers Bureau; TG Therapeutics: Consultancy, Honoraria, Speakers Bureau; Seagen: Consultancy, Honoraria, Speakers Bureau; ADC Therapeutics: Consultancy. Oluwole: Pfizer: Consultancy; Curio Science: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding; Janssen: Consultancy. Yakoub-Agha: Jazz Pharmaceuticals: Honoraria. Rosenblatt: Synergys: Patents & Royalties; BioGraph 55: Research Funding. Sherman: Kite, a Gilead Company: Current Employment; Gilead: Current equity holder in publicly-traded company. Dong: Kite, a Gilead Company: Current Employment; Gilead: Current equity holder in publicly-traded company; GliaCure/Tufts: Consultancy, Patents & Royalties. Giovanetti: Kite, a Gilead Company: Current Employment, Current equity holder in publicly-traded company. Yang: Kite, a Gilead Company: Current Employment. Lui: Gilead Sciences: Other: stock or other ownership; Kite, a Gilead Company: Current Employment, Other: travel support. Bashir: Kite, a Gilead Company: Ended employment in the past 24 months; OmniacPharmConsult Ltd: Other: stock or other ownership. Jung: Amgen, Kura, Gilead, and Turning Point: Current equity holder in publicly-traded company; Kite, a Gilead Company: Current Employment. Jacobson: Lonza: Consultancy, Honoraria, Other: Travel support; Kite, a Gilead Company: Consultancy, Honoraria, Other: Travel support; AbbVie: Consultancy, Honoraria; Nkarta: Consultancy, Honoraria; Novartis Pharmaceuticals Corporation: Consultancy, Honoraria, Other: Travel support; Pfizer: Consultancy, Honoraria, Other: Travel support, Research Funding; Precision Biosciences: Consultancy, Honoraria, Other: Travel support; Celgene: Consultancy, Honoraria, Other: Travel support; Humanigen: Consultancy, Honoraria, Other: Travel support; Axis: Speakers Bureau; Clinical Care Options: Speakers Bureau.

Abstract: e18600 Background: Allogeneic stem cell transplant (allo SCT) is a potentially curative therapy for hematological malignancies but is associated with high treatment related non-relapse mortality (NRM). Post-transplant care requires large amount of healthcare and patient resources, imposing higher burden on patients with lower socio-economic status (SES). Adverse health outcomes have been noted in males from lower SES background. We analyzed the effects of social factors on post-transplant survival and NRM in the diverse patient population treated at our institution. Methods: We retrospectively reviewed patients who underwent allo SCT at our program in 2015-2021. We collected baseline patient (demographics, KPS, HCT-CI), disease (diagnosis, risk index) and transplant characteristics (donor type, conditioning intensity). We extracted neighborhood level income data from US Census. Primary outcomes were survival and NRM. We used Fisher’s Exact, Wilcoxon Ranksum tests and logistic regressions. Results: 210 patients (116 males and 94 females) were included in the analysis. Neighborhood level estimated household income range was $26,041-163,074. Both 1 year OS and NRM, but not 100 days OS, significantly correlated with income. Patients who were alive at 1 year follow up (74.8% pts) had median income of $72K, compared to $62K for patients who died before 1 year (25.2% pts) and 60.5K for patients who died before 1 year without disease progression (13.3% pts) (p 0.032). The effect of income on NRM remained significant on multivariable analysis, adjusted for year of transplant, age, race, ethnicity, donor type, KPS, comorbidity index, regimen intensity, and disease risk. Increased conditioning intensity and haplo donor were also associated with increased 1 year NRM, while race and ethnicity did not have significant effect on 1 year NRM on multivariable analysis. The effect of income on NRM was dramatically different in male vs female patients. In men, a $10K increase in neighborhood income reduced the odds of NRM substantially (OR = 0.46, 95% CI 0.28-0.75), while in women there was no effect (OR 1.02, 95% CI 0.71-1.45). 1 year NRM in men was 9% vs 24% for higher vs lower neighborhood income (p 0.036), and in women 8% vs 13% (p 0.52). Conclusions: Our study identifies male patients residing in lower income neighborhoods as a subgroup at increased risk for NRM after allo SCT, after adjustment for the biological variables. The negative effects of lower neighborhood income and male gender become apparent with 1 year but not 100 days follow up, reflecting increasing difficulties with high resourses utilization over prolonged time period. Careful evaluation of controllable risk factors and optimizing social support may reduce the rate of complications. Further research into the factors mediating the relationship of neighborhood income with gender on survival and treatment-related mortality post allo SCT seems necessary.